Control of framed structures using intelligent monitoring networks

Directory of Open Access Journals (Sweden)

Foti Dora

2017-01-01

Full Text Available The paper proposes the integration of structural monitoring with Building Management Systems for electricity and gas distributions. To assess the state of damage of existing buildings the technics of Structural Health Monitoring (SHM is adopted. SHM as well as to record the occurrence of sudden structural damage resulting from exceptional events (earthquakes, explosions, shocks and collisions with vehicles, etc., allows the monitoring of the progressive damage and structural performance under operating conditions through the extraction of the modal parameters of the structure. This approach requires time to process acquired data that, depending on the size of the building and the number of monitored points, varies from minutes to hours. In this paper, an intelligent system is proposed to immediately communicate during an earthquake the overrun of a certain ground shaking threshold so that gas delivery and selected power loads are interrupted, as suggested by current national regulations on structures. The use of low-cost and reduced size accelerometric sensors integrated with Energy Monitoring Systems is proposed in both highrisk earthquake centers and in all “strategic” buildings that must ensure their operation use immediately after the earthquake. The procedure for calibrating the horizontal and vertical acceleration threshold is also sketched.

A new type of intelligent wireless sensing network for health monitoring of large-size structures

Science.gov (United States)

Lei, Ying; Liu, Ch.; Wu, D. T.; Tang, Y. L.; Wang, J. X.; Wu, L. J.; Jiang, X. D.

2009-07-01

In recent years, some innovative wireless sensing systems have been proposed. However, more exploration and research on wireless sensing systems are required before wireless systems can substitute for the traditional wire-based systems. In this paper, a new type of intelligent wireless sensing network is proposed for the heath monitoring of large-size structures. Hardware design of the new wireless sensing units is first studied. The wireless sensing unit mainly consists of functional modules of: sensing interface, signal conditioning, signal digitization, computational core, wireless communication and battery management. Then, software architecture of the unit is introduced. The sensing network has a two-level cluster-tree architecture with Zigbee communication protocol. Important issues such as power saving and fault tolerance are considered in the designs of the new wireless sensing units and sensing network. Each cluster head in the network is characterized by its computational capabilities that can be used to implement the computational methodologies of structural health monitoring; making the wireless sensing units and sensing network have "intelligent" characteristics. Primary tests on the measurement data collected by the wireless system are performed. The distributed computational capacity of the intelligent sensing network is also demonstrated. It is shown that the new type of intelligent wireless sensing network provides an efficient tool for structural health monitoring of large-size structures.

Modelling speech intelligibility in adverse conditions

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2013-01-01

Jørgensen and Dau (J Acoust Soc Am 130:1475-1487, 2011) proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII) in conditions with nonlinearly processed speech...... subjected to phase jitter, a condition in which the spectral structure of the intelligibility of speech signal is strongly affected, while the broadband temporal envelope is kept largely intact. In contrast, the effects of this distortion can be predicted -successfully by the spectro-temporal modulation...... suggest that the SNRenv might reflect a powerful decision metric, while some explicit across-frequency analysis seems crucial in some conditions. How such across-frequency analysis is "realized" in the auditory system remains unresolved....

Advancing satellite operations with intelligent graphical monitoring systems

Science.gov (United States)

Hughes, Peter M.; Shirah, Gregory W.; Luczak, Edward C.

1993-01-01

For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

Making intelligent systems team players. A guide to developing intelligent monitoring systems

Science.gov (United States)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Remote intelligent nuclear facility monitoring in LabVIEW

International Nuclear Information System (INIS)

Kucewicz, J.C.; Argo, P.E.; Caffrey, M.; Loveland, R.C.; McNeil, P.J.

1996-01-01

A prototype system implemented in LabVIEW for the intelligent monitoring of the movement of radioactive' material within a nuclear facility is presented. The system collects and analyzes radiation sensor and video data to identify suspicious movement of material within the facility. The facility system also transmits wavelet- compressed data to a remote system for concurrent monitoring. 2 refs., 2 figs

Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

Science.gov (United States)

Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

2017-04-01

With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications

Toward Intelligent Hemodynamic Monitoring: A Functional Approach

Directory of Open Access Journals (Sweden)

Pierre Squara

2012-01-01

Full Text Available Technology is now available to allow a complete haemodynamic analysis; however this is only used in a small proportion of patients and seems to occur when the medical staff have the time and inclination. As a result of this, significant delays occur between an event, its diagnosis and therefore, any treatment required. We can speculate that we should be able to collect enough real time information to make a complete, real time, haemodynamic diagnosis in all critically ill patients. This article advocates for “intelligent haemodynamic monitoring”. Following the steps of a functional analysis, we answered six basic questions. (1 What is the actual best theoretical model for describing haemodynamic disorders? (2 What are the needed and necessary input/output data for describing this model? (3 What are the specific quality criteria and tolerances for collecting each input variable? (4 Based on these criteria, what are the validated available technologies for monitoring each input variable, continuously, real time, and if possible non-invasively? (5 How can we integrate all the needed reliably monitored input variables into the same system for continuously describing the global haemodynamic model? (6 Is it possible to implement this global model into intelligent programs that are able to differentiate clinically relevant changes as opposed to artificial changes and to display intelligent messages and/or diagnoses?

Process monitoring for intelligent manufacturing processes - Methodology and application to Robot Assisted Polishing

DEFF Research Database (Denmark)

Pilny, Lukas

Process monitoring provides important information on the product, process and manufacturing system during part manufacturing. Such information can be used for process optimization and detection of undesired processing conditions to initiate timely actions for avoidance of defects, thereby improving...... quality assurance. This thesis is aimed at a systematic development of process monitoring solutions, constituting a key element of intelligent manufacturing systems towards zero defect manufacturing. A methodological approach of general applicability is presented in this concern.The approach consists...... of six consecutive steps for identification of product Vital Quality Characteristics (VQCs) and Key Process Variables (KPVs), selection and characterization of sensors, optimization of sensors placement, validation of the monitoring solutions, definition of the reference manufacturing performance...

Condition based monitoring, diagnosis and maintenance on operating equipments of a hydraulic generator unit

International Nuclear Information System (INIS)

Liu, X T; Feng, F Z; Si, A W

2012-01-01

According to performance characteristics of operating equipments in a hydraulic generator unit (HGU), the relative techniques on condition monitoring and fault diagnosis (CMFD) are introduced in this paper, especially the key technologies are emphasized, such as equipment monitoring, expert system (ES), intelligent diagnosis and condition based maintenance (CBM). Meanwhile, according to the instructor on CBM proposed by State electric power corporation, based on integrated mode, the main steps on implementation of CBM are discussed in this paper.

Welding station condition monitoring using bluetooth enabled sensors and intelligent data management

Energy Technology Data Exchange (ETDEWEB)

Eyers, D R; Grosvenor, R I; Prickett, P W [Intelligent Process Monitoring and Management (IPMM) Group, Cardiff School of Engineering, Cardiff University, Wales (United Kingdom)

2005-01-01

This paper reports on the first phase deployment of bluetooth enabled condition monitoring systems at a large multinational engineering company. The radio networking of sensor signals is a fast developing area and the facilities afforded by the Wisnet device were used in the monitoring of a welding station. This and any of the planned further monitoring systems had to comply to a carefully managed IT information plan at the company. For the example application, the development and testing of microcontoller-based pre-processing of data is reported. This includes further development of the Petri Net approach to provide event-based monitoring as a sensible alternative to the continuous transmission of the sensory data.

Intelligent IPv6 based iot network monitoring and altering system on ...

African Journals Online (AJOL)

Intelligent IPv6 based iot network monitoring and altering system on Cooja framework. ... Journal of Fundamental and Applied Sciences. Journal Home · ABOUT THIS ... Keywords: IoT; Cooja framework; Contiki OS; packet monitoring.

An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers

Directory of Open Access Journals (Sweden)

Jian Li

2016-05-01

Full Text Available Ultra-high-frequency (UHF partial discharge (PD online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intelligent sensor is qualified for the UHF PD online monitoring of power transformers. Additionally, three methods to improve the performance of intelligent sensors were proposed according to the principle of the level scanning method.

Pure intelligent monitoring system for steam economizer trips

Directory of Open Access Journals (Sweden)

Basim Ismail Firas

2017-01-01

Full Text Available Steam economizer represents one of the main equipment in the power plant. Some steam economizer's behavior lead to failure and shutdown in the entire power plant. This will lead to increase in operating and maintenance cost. By detecting the cause in the early stages maintain normal and safe operational conditions of power plant. However, these methodologies are hard to be achieved due to certain boundaries such as system learning ability and the weakness of the system beyond its domain of expertise. The best solution for these problems, an intelligent modeling system specialized in steam economizer trips have been proposed and coded within MATLAB environment to be as a potential solution to insure a fault detection and diagnosis system (FDD. An integrated plant data preparation framework for 10 trips was studied as framework variables. The most influential operational variables have been trained and validated by adopting Artificial Neural Network (ANN. The Extreme Learning Machine (ELM neural network methodology has been proposed as a major computational intelligent tool in the system. It is shown that ANN can be implemented for monitoring any process faults in thermal power plants. Better speed of learning algorithms by using the Extreme Learning Machine has been approved as well.

CAMAC-based intelligent subsystem for ATLAS example application: cryogenic monitoring and control

International Nuclear Information System (INIS)

Pardo, R.; Kawarasaki, Y.; Wasniewski, K.

1985-01-01

A subunit of the CAMAC accelerator control system of ATLAS for monitoring and, eventually, controlling the cryogenic refrigeration and distribution facility is under development. This development is the first application of a philosophy of distributed intelligence which will be applied throughout the ATLAS control system. The control concept is that of an intelligent subunit of the existing ATLAS CAMAC control highway. A single board computer resides in an auxiliary crate controller which allows access to all devices within the crate. The local SBC can communicate to the host over the CAMAC highway via a protocol involving the use of memory in the SBC which can be accessed from the host in a DMA mode. This provides a mechanism for global communications, such as for alarm conditions, as well as allowing the cryogenic system to respond to the demands of the accelerator system

Design and Development of Intelligent Electrodes for Future Digital Health Monitoring: A Review

Science.gov (United States)

Khairuddin, A. M.; Azir, K. N. F. Ku; Kan, P. Eh

2018-03-01

Electrodes are sensors used in electrocardiography (ECG) monitoring system to diagnose heart diseases. Over the years, diverse types of electrodes have been designed and developed to improve ECG monitoring system. However, more recently, with the technological advances and capabilities from the Internet of Things (IoT), cloud computing and data analytics in personalized healthcare, researchers are attempting to design and develop more effective as well as flexible ECG devices by using intelligent electrodes. This paper reviews previous works on electrodes used in electrocardiography (ECG) monitoring devices to identify the key ftures for designing and developing intelligent electrodes in digital health monitoring devices.

Ambient intelligence for monitoring and research in clinical neurophysiology and medicine: the MIMERICA* project and prototype.

Science.gov (United States)

Pignolo, L; Riganello, F; Dolce, G; Sannita, W G

2013-04-01

Ambient Intelligence (AmI) provides extended but unobtrusive sensing and computing devices and ubiquitous networking for human/environment interaction. It is a new paradigm in information technology compliant with the international Integrating Healthcare Enterprise board (IHE) and eHealth HL7 technological standards in the functional integration of biomedical domotics and informatics in hospital and home care. AmI allows real-time automatic recording of biological/medical information and environmental data. It is extensively applicable to patient monitoring, medicine and neuroscience research, which require large biomedical data sets; for example, in the study of spontaneous or condition-dependent variability or chronobiology. In this respect, AML is equivalent to a traditional laboratory for data collection and processing, with minimal dedicated equipment, staff, and costs; it benefits from the integration of artificial intelligence technology with traditional/innovative sensors to monitor clinical or functional parameters. A prototype AmI platform (MIMERICA*) has been implemented and is operated in a semi-intensive unit for the vegetative and minimally conscious states, to investigate the spontaneous or environment-related fluctuations of physiological parameters in these conditions.

FOREWORD: Structural Health Monitoring and Intelligent Infrastructure

Science.gov (United States)

Wu, Zhishen; Fujino, Yozo

2005-06-01

This special issue collects together 19 papers that were originally presented at the First International Conference on Structural Health Monitoring and Intelligent Infrastructure (SHMII-1'2003), held in Tokyo, Japan, on 13-15 November 2003. This conference was organized by the Japan Society of Civil Engineers (JSCE) with partial financial support from the Japan Society for the Promotion of Science (JSPS) and the Ministry of Education, Culture, Sport, Science and Technology, Japan. Many related organizations supported the conference. A total of 16 keynote papers including six state-of-the-art reports from different counties, six invited papers and 154 contributed papers were presented at the conference. The conference was attended by a diverse group of about 300 people from a variety of disciplines in academia, industry and government from all over the world. Structural health monitoring (SHM) and intelligent materials, structures and systems have been the subject of intense research and development in the last two decades and, in recent years, an increasing range of applications in infrastructure have been discovered both for existing structures and for new constructions. SHMII-1'2003 addressed progress in the development of building, transportation, marine, underground and energy-generating structures, and other civilian infrastructures that are periodically, continuously and/or actively monitored where there is a need to optimize their performance. In order to focus the current needs on SHM and intelligent technologies, the conference theme was set as 'Structures/Infrastructures Sustainability'. We are pleased to have the privilege to edit this special issue on SHM and intelligent infrastructure based on SHMII-1'2003. We invited some of the presenters to submit a revised/extended version of their paper that was included in the SHMII-1'2003 proceedings for possible publication in the special issue. Each paper included in this special issue was edited with the same

Intelligent vehicle based traffic monitoring – exploring application in South Africa

CSIR Research Space (South Africa)

Labuschagne, FJJ

2010-08-01

Full Text Available The paper details the anticipated benefits of an intelligent vehicle based traffic monitoring approach holds. The approach utilises advanced technology with the potential to reduce crashes and includes the monitor of vehicle speeds and flows...

Using Wireless Sensor Networks to Achieve Intelligent Monitoring for High-Temperature Gas-Cooled Reactor

Directory of Open Access Journals (Sweden)

Jianghai Li

2017-01-01

Full Text Available High-temperature gas-cooled reactors (HTGR can incorporate wireless sensor network (WSN technology to improve safety and economic competitiveness. WSN has great potential in monitoring the equipment and processes within nuclear power plants (NPPs. This technology not only reduces the cost of regular monitoring but also enables intelligent monitoring. In intelligent monitoring, large sets of heterogeneous data collected by the WSN can be used to optimize the operation and maintenance of the HTGR. In this paper, WSN-based intelligent monitoring schemes that are specific for applications of HTGR are proposed. Three major concerns regarding wireless technology in HTGR are addressed: wireless devices interference, cybersecurity of wireless networks, and wireless standards selected for wireless platform. To process nonlinear and non-Gaussian data obtained by WSN for fault diagnosis, novel algorithms combining Kernel Entropy Component Analysis (KECA and support vector machine (SVM are developed.

Predicting speech intelligibility in conditions with nonlinearly processed noisy speech

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2013-01-01

The speech-based envelope power spectrum model (sEPSM; [1]) was proposed in order to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII). The sEPSM applies the signal-tonoise ratio in the envelope domain (SNRenv), which was demonstrated...... to successfully predict speech intelligibility in conditions with nonlinearly processed noisy speech, such as processing with spectral subtraction. Moreover, a multiresolution version (mr-sEPSM) was demonstrated to account for speech intelligibility in various conditions with stationary and fluctuating...

Intelligent Performance Analysis with a Natural Language Interface

Science.gov (United States)

Juuso, Esko K.

2017-09-01

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

Optimizing acoustical conditions for speech intelligibility in classrooms

Science.gov (United States)

Yang, Wonyoung

High speech intelligibility is imperative in classrooms where verbal communication is critical. However, the optimal acoustical conditions to achieve a high degree of speech intelligibility have previously been investigated with inconsistent results, and practical room-acoustical solutions to optimize the acoustical conditions for speech intelligibility have not been developed. This experimental study validated auralization for speech-intelligibility testing, investigated the optimal reverberation for speech intelligibility for both normal and hearing-impaired listeners using more realistic room-acoustical models, and proposed an optimal sound-control design for speech intelligibility based on the findings. The auralization technique was used to perform subjective speech-intelligibility tests. The validation study, comparing auralization results with those of real classroom speech-intelligibility tests, found that if the room to be auralized is not very absorptive or noisy, speech-intelligibility tests using auralization are valid. The speech-intelligibility tests were done in two different auralized sound fields---approximately diffuse and non-diffuse---using the Modified Rhyme Test and both normal and hearing-impaired listeners. A hybrid room-acoustical prediction program was used throughout the work, and it and a 1/8 scale-model classroom were used to evaluate the effects of ceiling barriers and reflectors. For both subject groups, in approximately diffuse sound fields, when the speech source was closer to the listener than the noise source, the optimal reverberation time was zero. When the noise source was closer to the listener than the speech source, the optimal reverberation time was 0.4 s (with another peak at 0.0 s) with relative output power levels of the speech and noise sources SNS = 5 dB, and 0.8 s with SNS = 0 dB. In non-diffuse sound fields, when the noise source was between the speaker and the listener, the optimal reverberation time was 0.6 s with

Relationship between IQ, cultural intelligence and self-monitoring in the students of Birjand University of Medical Sciences

Directory of Open Access Journals (Sweden)

Aliakbar Esmaeili

2016-09-01

Full Text Available Background and Aim: Intelligence quotient (IQ, cultural intelligence, and self-monitoring are among important and influential parameters in learning-teaching process of students. Thus, the current study examined the relationship between these parameters in the students of Birjand University of Medical Science. Materials and Methods: The present study was a descriptive-analytic, cross-sectional type. The study population included all the students at Birjand University of Medical Sciences, selected through stratified randomized sampling method. In order to study IQ, cultural intelligence, and self-monitoring parameters R & B Cattell scale (Scale III, Erli’s Cultural Intelligence Inventory, and Snyder’s Self-monitoring Test were applied, respectively. The obtained data was fed into SPSS (V:21 software using Pearson correlation test, ANOVA, and t-test at the significant level of P≤0.05. Results: From a total of 171 subjects participating in the study, 53.2% were female. The average age of the participants was 21.3±2.7 years. The average IQ, cultural intelligence, and self-monitoring scores were 106±10.44, 85.73±17.31, and 12.35±3.20, respectively. There was a significant correlation between cultural intelligence and self-monitoring (P<0.000; r=0/37. However, there were no significant associations between cultural intelligence and IQ scores as well as between self-monitoring and IQ scores. Conclusion: Regarding the unfavorable cultural intelligence’ skills and abilities ;and their acquirable nature, it is suggested that University consider a significant position for educational and cultural programs in order to enhance cultural intelligence.

Relationship between IQ, cultural intelligence and self-monitoring in the students of Birjand University of Medical Sciences

Directory of Open Access Journals (Sweden)

Aliakbar Esmaeili

2016-12-01

Full Text Available Background and Aim: Intelligence quotient (IQ, cultural intelligence, and self-monitoring are among important and influential parameters in learning-teaching process of students. Thus, the current study examined the relationship between these parameters in the students of Birjand University of Medical Science. Materials and Methods: The present study was a descriptive-analytic, cross-sectional type. The study population included all the students at Birjand University of Medical Sciences, selected through stratified randomized sampling method. In order to study IQ, cultural intelligence, and self-monitoring parameters R & B Cattell scale (Scale III, Erli’s Cultural Intelligence Inventory, and Snyder’s Self-monitoring Test were applied, respectively. The obtained data was fed into SPSS (V:21 software using Pearson correlation test, ANOVA, and t-test at the significant level of P≤0.05. Results: From a total of 171 subjects participating in the study, 53.2% were female. The average age of the participants was 21.3±2.7 years. The average IQ, cultural intelligence, and self-monitoring scores were 106±10.44, 85.73±17.31, and 12.35±3.20, respectively. There was a significant correlation between cultural intelligence and self-monitoring (P<0.000; r=0/37. However, there were no significant associations between cultural intelligence and IQ scores as well as between self-monitoring and IQ scores. Conclusion: Regarding the unfavorable cultural intelligence’ skills and abilities ;and their acquirable nature, it is suggested that University consider a significant position for educational and cultural programs in order to enhance cultural intelligence.

A radioactive waste transportation package monitoring system for normal transport and accident emergency response conditions

International Nuclear Information System (INIS)

Brown, G.S.; Cashwell, J.W.; Apple, M.L.

1993-01-01

This paper addresses spent fuel and high level waste transportation history and prospects, discusses accident histories of radioactive material transport, discusses emergency responder needs and provides a general description of the Transportation Intelligent Monitoring System (TRANSIMS) design. The key objectives of the monitoring system are twofold: (1) to facilitate effective emergency response to accidents involving a radioactive waste transportation package, while minimizing risk to the public and emergency first-response personnel, and (2) to allow remote monitoring of transportation vehicle and payload conditions to enable research into radioactive material transportation for normal and accident conditions. (J.P.N.)

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Science.gov (United States)

2010-07-01

... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Monitoring and auditing of grants for the funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding...

Radiation monitoring of nuclear census intelligent data management and mobile monitoring data acquisition system

International Nuclear Information System (INIS)

Huang Libin; Zhong Zhijing; Zhou Yinhang; Guo Hongbo

2014-01-01

The system, employing advanced intelligent terminal, mobile applications, database technology, can achieve all kinds of field monitoring, mobile radiation monitoring data collected for laboratory analysis; employing GPS technology, can achieve the geographic information of the radiation monitoring data, time tagging and other anti-cheating measures; the system also established a mass database management system; the system is suitable for all types of nuclear-related units with special adaptive functions; system will be extended to GIS-based management capabilities of nuclear contamination distribution in latter stage. (authors)

A camac-based intelligent subsystem for ATLAS example application: cryogenic monitoring and control

International Nuclear Information System (INIS)

Pardo, R.; Kawarasaki, Y.; Wasniewski, K.

1985-01-01

A subunit of the CAMAC accelerator control system of ATLAS for monitoring and, eventually, controlling the cryogenic refrigeration and distribution facility is under development. This development is the first application of a philosophy of distributed intelligence which will be applied throughout the ATLAS control system. The control concept is that of an intelligent subunit of the existing ATLAS CAMAC control highway. A single board computer resides in an auxiliary crate controller which allows access to all devices within the crate. The local SBC can communicate to the host over the CAMAC highway via a protocol involving the use of memory in the SBC which can be accessed from the host in a DMA mode. This provides a mechanism for global communications, such as for alarm conditions, as well as allowing the cryogenic system to respond to the demands of the accelerator system

Reconfigurable intelligent sensors for health monitoring: a case study of pulse oximeter sensor.

Science.gov (United States)

Jovanov, E; Milenkovic, A; Basham, S; Clark, D; Kelley, D

2004-01-01

Design of low-cost, miniature, lightweight, ultra low-power, intelligent sensors capable of customization and seamless integration into a body area network for health monitoring applications presents one of the most challenging tasks for system designers. To answer this challenge we propose a reconfigurable intelligent sensor platform featuring a low-power microcontroller, a low-power programmable logic device, a communication interface, and a signal conditioning circuit. The proposed solution promises a cost-effective, flexible platform that allows easy customization, run-time reconfiguration, and energy-efficient computation and communication. The development of a common platform for multiple physical sensors and a repository of both software procedures and soft intellectual property cores for hardware acceleration will increase reuse and alleviate costs of transition to a new generation of sensors. As a case study, we present an implementation of a reconfigurable pulse oximeter sensor.

Realization of Intelligent Household Appliance Wireless Monitoring Network Based on LEACH Protocol

Directory of Open Access Journals (Sweden)

Weilong ZHOU

2014-06-01

Full Text Available The intelligent household appliance wireless monitoring network can real-time monitor the apparent power and power factor of various household appliances in different indoor regions, and can realize the real-time monitoring on the household appliance working status and performance. The household appliance wireless monitoring network based on LEACH protocol is designed in the paper. Firstly, the basic idea of LEACH routing algorithm is proposed. Aiming at the node-distribution feature of intelligent home, the selection of cluster head in the routing algorithm and the data transmission method at the stable communication phase is modified. Moreover, the hardware circuit of power acquisition and power factor measurement is designed. The realization of wireless monitoring network based on CC2530 is described, each module and the whole system were conducted the on-line debugging. Finally, the system is proved to meet the practical requirement through the networking test.

Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

OpenAIRE

Nalamvar, Hitesh Sanzhay; Ivanov, Maksim Anatoljevich; Baydali, Sergey Anatolievich

2017-01-01

The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the sys...

Experimental Study on Intelligent Control Scheme for Fan Coil Air-Conditioning System

Directory of Open Access Journals (Sweden)

Yanfeng Li

2013-01-01

Full Text Available An intelligent control scheme for fan coil air-conditioning systems has been put forward in order to overcome the shortcomings of the traditional proportion-integral-derivative (PID control scheme. These shortcomings include the inability of anti-interference and large inertia. An intelligent control test rig of fan coil air-conditioning system has been built, and MATLAB/Simulink dynamics simulation software has been adopted to implement the intelligent control scheme. A software for data exchange has been developed to combine the intelligence control system and the building automation (BA system. Experimental tests have been conducted to investigate the effectiveness of different control schemes including the traditional PID control, fuzzy control, and fuzzy-PID control for fan coil air-conditioning system. The effects of control schemes have been compared and analyzed in robustness, static and dynamic character, and economy. The results have shown that the developed data exchange interface software can induce the intelligent control scheme of the BA system more effectively. Among the proposed control strategies, fuzzy-PID control scheme which has the advantages of both traditional PID and fuzzy schemes is the optimal control scheme for the fan coil air-conditioning system.

Intelligent Component Monitoring for Nuclear Power Plants

International Nuclear Information System (INIS)

Tsoukalas, Lefteri

2010-01-01

Reliability and economy are two major concerns for a nuclear power generation system. Next generation nuclear power reactors are being developed to be more reliable and economic. An effective and efficient surveillance system can generously contribute toward this goal. Recent progress in computer systems and computational tools has made it necessary and possible to upgrade current surveillance/monitoring strategy for better performance. For example, intelligent computing techniques can be applied to develop algorithm that help people better understand the information collected from sensors and thus reduce human error to a new low level. Incidents incurred from human error in nuclear industry are not rare and have been proven costly. The goal of this project is to develop and test an intelligent prognostics methodology for predicting aging effects impacting long-term performance of nuclear components and systems. The approach is particularly suitable for predicting the performance of nuclear reactor systems which have low failure probabilities (e.g., less than 10 -6 year -1 ). Such components and systems are often perceived as peripheral to the reactor and are left somewhat unattended. That is, even when inspected, if they are not perceived to be causing some immediate problem, they may not be paid due attention. Attention to such systems normally involves long term monitoring and possibly reasoning with multiple features and evidence, requirements that are not best suited for humans.

Towards intelligent video understanding applied to plasma facing component monitoring

Energy Technology Data Exchange (ETDEWEB)

Martin, V.; Bremond, F. [INRIA, Pulsa team-project, Sophia Antipolis (France); Travere, J.M. [CEA IRFM, Saint Paul-lez-Durance (France); Moncada, V.; Dunand, G. [Sophia Conseil Company, Sophia Antipolis (France)

2011-07-01

Infrared thermography has become a routine diagnostic in many magnetic fusion devices to monitor the heat loads on the plasma facing components (PFCs) for both physics studies and machine protection. The good results of the developed systems obtained so far motivate the use of imaging diagnostics for control, especially during long pulse tokamak operation (e.g. lasting several minutes). In this paper, we promote intelligent monitoring for both real-time purposes (machine protection issues) and post event analysis purposes (PWI understanding). We propose a vision-based system able to automatically detect and classify into different pre-defined categories phenomena as localized hot spots, transient thermal events (e.g. electrical arcing), and unidentified flying objects (UFOs) as dusts from infrared imaging data of PFCs. This original vision system is made intelligent by endowing it with high-level reasoning (i.e. integration of a priori knowledge of thermal event spatial and temporal properties to guide the recognition), self-adaptability to varying conditions (e.g. different plasma scenarios), and learning capabilities (e.g. statistical modelling of thermal event behaviour based on training samples). This approach has been already successfully applied to the recognition of one critical thermal event at Tore Supra. We present here latest results of its extension for the recognition of others thermal events (e.g., B{sub 4}C flakes, impact of fast particles, UFOs) and show how extracted information can be used during plasma operation at Tore Supra to improve the real time control system, and for further analysis of PFC aging. This document is composed of an abstract followed by the slides of the presentation. (authors)

iAssist: a software framework for intelligent patient monitoring.

Science.gov (United States)

Brouse, Christopher; Dumont, Guy; Yang, Ping; Lim, Joanne; Ansermino, J Mark

2007-01-01

A software framework (iAssist) has been developed for intelligent patient monitoring, and forms the foundation of a clinical monitoring expert system. The framework is extensible, flexible, and interoperable. It supports plugins to perform data acquisition, signal processing, graphical display, data storage, and output to external devices. iAssist currently incorporates two plugins to detect change point events in physiological trends. In 38 surgical cases, iAssist detected 868 events, of which clinicians rated more than 50% as clinically significant and less than 7% as artifacts. Clinicians found iAssist intuitive and easy to use.

Intelligent monitoring-based safety system of massage robot

Institute of Scientific and Technical Information of China (English)

胡宁; 李长胜; 王利峰; 胡磊; 徐晓军; 邹雲鹏; 胡玥; 沈晨

2016-01-01

As an important attribute of robots, safety is involved in each link of the full life cycle of robots, including the design, manufacturing, operation and maintenance. The present study on robot safety is a systematic project. Traditionally, robot safety is defined as follows: robots should not collide with humans, or robots should not harm humans when they collide. Based on this definition of robot safety, researchers have proposed ex ante and ex post safety standards and safety strategies and used the risk index and risk level as the evaluation indexes for safety methods. A massage robot realizes its massage therapy function through applying a rhythmic force on the massage object. Therefore, the traditional definition of safety, safety strategies, and safety realization methods cannot satisfy the function and safety requirements of massage robots. Based on the descriptions of the environment of massage robots and the tasks of massage robots, the present study analyzes the safety requirements of massage robots; analyzes the potential safety dangers of massage robots using the fault tree tool; proposes an error monitoring-based intelligent safety system for massage robots through monitoring and evaluating potential safety danger states, as well as decision making based on potential safety danger states; and verifies the feasibility of the intelligent safety system through an experiment.

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

Science.gov (United States)

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

The development report of an intelligent neutron fluence integration monitor

International Nuclear Information System (INIS)

Jiang Zongbing; Wei Ying

1996-10-01

An intelligent neutron fluence integration monitor is introduced. It is used to measure the received neutron fluence of the monocrystalline silicon in reactor radiation channel. The significance of study and specifications of the instrument are briefly described. The emphasis is on the working principle, structure and characteristics of the instrument is intelligent due to use of monolithic microcomputer. It has many advantages proved in the actual practice, such as powerful function, high accuracy, diversity of application, high level automatization, easy to operate, high reliability, etc. After using this instrument the monocrystalline silicon radiation technology is improved and the efficiency of production is raised. (1 fig.)

Modeling speech intelligibility in adverse conditions

DEFF Research Database (Denmark)

Dau, Torsten

2012-01-01

) in conditions with nonlinearly processed speech. Instead of considering the reduction of the temporal modulation energy as the intelligibility metric, as assumed in the STI, the sEPSM applies the signal-to-noise ratio in the envelope domain (SNRenv). This metric was shown to be the key for predicting...... understanding speech when more than one person is talking, even when reduced audibility has been fully compensated for by a hearing aid. The reasons for these difficulties are not well understood. This presentation highlights recent concepts of the monaural and binaural signal processing strategies employed...... by the normal as well as impaired auditory system. Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII...

Development of an integrated condition monitoring system for meeting license renewal criteria

International Nuclear Information System (INIS)

Jarrell, D.B.; Stratton, R.C.

1991-01-01

A project for developing a methodology that facilitates an artificial intelligence (AI) approach to the integration of component condition monitoring, fault diagnostics, and component failure root cause analysis is in progress at PNL. Using model-based reasoning with an object oriented schematic representation, these combined elements provide a real-time interactive means to systematically investigate, understand and auto-document the mitigation of age-related component degradation. A common Data Acquisition System contains component parameter and machinery history data as well as a knowledge of the plant system configuration. The unique aspect of this system is that it integrates this component parametric, diagnostic, and failure history knowledge to determine a more complete computerized specification of the component condition than was previously possible. This condition specification is then compared to degradation process models for behavioral similitude, thereby identifying the active degradation mechanism. Based on the monitored trends and the degradation model, an accurate estimate of projected equipment service life can then be projected. (author)

Computational intelligence in nuclear engineering

International Nuclear Information System (INIS)

Uhrig, Robert E.; Hines, J. Wesley

2005-01-01

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several Changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations

Artificial intelligence and finite element modelling for monitoring flood defence structures

NARCIS (Netherlands)

Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

2011-01-01

We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

Intelligent environmental sensing

CERN Document Server

Mukhopadhyay, Subhas

2015-01-01

Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection.

Science.gov (United States)

Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

2017-06-12

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan-Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities.

Internet-based intelligent information processing systems

CERN Document Server

Tonfoni, G; Ichalkaranje, N S

2003-01-01

The Internet/WWW has made it possible to easily access quantities of information never available before. However, both the amount of information and the variation in quality pose obstacles to the efficient use of the medium. Artificial intelligence techniques can be useful tools in this context. Intelligent systems can be applied to searching the Internet and data-mining, interpreting Internet-derived material, the human-Web interface, remote condition monitoring and many other areas. This volume presents the latest research on the interaction between intelligent systems (neural networks, adap

Intelligent energy management control of vehicle air conditioning system coupled with engine

International Nuclear Information System (INIS)

Khayyam, Hamid; Abawajy, Jemal; Jazar, Reza N.

2012-01-01

Vehicle Air Conditioning (AC) systems consist of an engine powered compressor activated by an electrical clutch. The AC system imposes an extra load to the vehicle's engine increasing the vehicle fuel consumption and emissions. Energy management control of the vehicle air conditioning is a nonlinear dynamic system, influenced by uncertain disturbances. In addition, the vehicle energy management control system interacts with different complex systems, such as engine, air conditioning system, environment, and driver, to deliver fuel consumption improvements. In this paper, we describe the energy management control of vehicle AC system coupled with vehicle engine through an intelligent control design. The Intelligent Energy Management Control (IEMC) system presented in this paper includes an intelligent algorithm which uses five exterior units and three integrated fuzzy controllers to produce desirable internal temperature and air quality, improved fuel consumption, low emission, and smooth driving. The three fuzzy controllers include: (i) a fuzzy cruise controller to adapt vehicle cruise speed via prediction of the road ahead using a Look-Ahead system, (ii) a fuzzy air conditioning controller to produce desirable temperature and air quality inside vehicle cabin room via a road information system, and (iii) a fuzzy engine controller to generate the required engine torque to move the vehicle smoothly on the road. We optimised the integrated operation of the air conditioning and the engine under various driving patterns and performed three simulations. Results show that the proposed IEMC system developed based on Fuzzy Air Conditioning Controller with Look-Ahead (FAC-LA) method is a more efficient controller for vehicle air conditioning system than the previously developed Coordinated Energy Management Systems (CEMS). - Highlights: ► AC interacts: vehicle, environment, driver components, and the interrelationships between them. ► Intelligent AC algorithm which uses

Intelligent Learning System using cognitive science theory and artificial intelligence methods

Energy Technology Data Exchange (ETDEWEB)

Cristensen, D.L.

1986-01-01

This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.

An intelligent and networking solution of radiation monitoring system for LHC

International Nuclear Information System (INIS)

Shao Beibei; Gong Guanghua

2001-01-01

The LHC (the Large Hadron Collider), the largest accelerator in the world, is under designing and construction at CERN. It shares the 27 km LEP tunnel and is expected to be on the air in 2005. The Radiation Monitoring System of LEP was a central system with non-intelligent detectors. While as the proposed new RMS for LHC is a distributing intelligent networked system. Around 350 detectors will be employed. To save the cost, the design should make the old LEP's non-intelligent detectors reusable. To allow the detector controller automatic reports the detector database and net location through the world Fip bus, 1 wire components are embedded into the detectors and the network sockets. The radiation tolerance and the reliability of the communication of the wire components have been tested in a strong radiation field at CERN. The low cost components based position detection technique is valuable for most networked control system

Proposal of an intelligent wayside monitoring system for detection of critical ice accumulations on railway vehicles

Science.gov (United States)

Michelberger, Frank; Wagner, Adrian; Ostermann, Michael; Maly, Thomas

2017-09-01

At railway lines with ballasted tracks, under unfavourable conditions, the so-called flying ballast can occur predominantly for trains driving at high speeds. Especially in wintertime, it is highly likely that the causes are adhered snow or ice deposits, which are falling off the vehicle. Due to the high kinetic energy, the impact can lead to the removal of ballast stones from the structure of the ballasted track. If the stones reach the height of vehicles underside, they may be accelerated significantly due to the collision with the vehicle or may detach further ice blocks. In the worst case, a reinforcing effect occurs, which can lead to considerable damage to railway vehicles (under-floor-area, vehicle exteriors, etc.) and infrastructure (signal masts, noise barriers, etc.). Additionally the flying gravel is a significant danger to people in the nearby area of the tracks. With this feasibility study the applicability and meaningfulness of an intelligent monitoring system for identification of the critical ice accumulation to prevent the ballast fly induced by ice dropping was examined. The key findings of the research are that the detection of ice on railway vehicles and the development of an intelligent monitoring seem to be possible with existing technologies, but a proof of concept in terms of field tests is necessary.

[Intelligent watch system for health monitoring based on Bluetooth low energy technology].

Science.gov (United States)

Wang, Ji; Guo, Hailiang; Ren, Xiaoli

2017-08-01

According to the development status of wearable technology and the demand of intelligent health monitoring, we studied the multi-function integrated smart watches solution and its key technology. First of all, the sensor technology with high integration density, Bluetooth low energy (BLE) and mobile communication technology were integrated and used in develop practice. Secondly, for the hardware design of the system in this paper, we chose the scheme with high integration density and cost-effective computer modules and chips. Thirdly, we used real-time operating system FreeRTOS to develop the friendly graphical interface interacting with touch screen. At last, the high-performance application software which connected with BLE hardware wirelessly and synchronized data was developed based on android system. The function of this system included real-time calendar clock, telephone message, address book management, step-counting, heart rate and sleep quality monitoring and so on. Experiments showed that the collecting data accuracy of various sensors, system data transmission capacity, the overall power consumption satisfy the production standard. Moreover, the system run stably with low power consumption, which could realize intelligent health monitoring effectively.

Integrated environmental control and monitoring in the intelligent workplace. Final report

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-31

This project involved the design and engineering of the control and monitoring of environmental quality - visual, thermal, air - in the Intelligent Workplace. The research objectives were to study the performance of the individual systems, to study the integration issues related to each system, to develop a control plan, and to implement and test the integrated systems in a real setting. In this project, a control strategy with related algorithms for distributed sensors, actuators, and controllers for negotiating central and individual control of HVAC, lighting, and enclosure was developed in order to maximize user comfort, and energy and environmental effectiveness. The goal of the control system design in the Intelligent Workplace is the integration of building systems for optimization of occupant satisfaction, organizational flexibility, energy efficiency and environmental effectiveness. The task of designing this control system involves not only the research, development and demonstration of state-of-the-art mechanical and electrical systems, but also their integration. The ABSIC research team developed functional requirements for the environmental systems considering the needs of both facility manager and the user. There are three levels of control for the environmental systems: scheduled control, sensor control, and user control. The challenges are to achieve the highest possible levels of energy effectiveness simultaneously with the highest levels of user satisfaction. The report describes the components of each system, their implementation in the Intelligent Workplace and related control and monitoring issues.

A multi-agent approach to intelligent monitoring in smart grids

Science.gov (United States)

Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

2014-04-01

In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection †

Science.gov (United States)

Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

2017-01-01

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan–Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities. PMID:28604628

Dealing with distributed intelligence in monitoring and control systems

International Nuclear Information System (INIS)

McLaren, R.A.

1981-01-01

The Euorpean Hybrid Spectrometer is built up of many individual detectors, each having widely varying monitoring and control requirements. With the advent of cheap microprocessor systems a shift from the concept of a single monitoring and control computer of that of distributed intelligent controllers has been economically feasible. A detector designer can now thoroughly test and debug a complete monitoring and control system on a local, dedicated micro-computer, while during operation, the central computer can be relieved of many simple repetitive tasks. Rapidly, however, it has become obvious that the designers of these systems have to take into account the final operational environment and build into both the hardware and software, features allowing easy integration into a central monitoring and control chain. In addition, the problems of maintenance and enventual modification have to be taken into consideration early in the development. Examples of currently operational systems will be briefly described to demonstrate how a set of basic guidelines plus standardisation of hardware/software can minimise the problems of integration and maintenance. Based on practical experience gained in the European Hybrid Spectrometer, investigations are proceeding on various possible alternatives for future micro-computer based monitoring and control systems. (orig.)

Intelligent Wireless Sensor Networks for System Health Monitoring

Science.gov (United States)

Alena, Rick

2011-01-01

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of

Time temperature indicators as devices intelligent packaging

Directory of Open Access Journals (Sweden)

Adriana Pavelková

2013-01-01

Full Text Available Food packaging is an important part of food production. Temperature is a one of crucial factor which affecting the quality and safety of food products during distribution, transport and storage. The one way of control of food quality and safety is the application of new packaging systems, which also include the intelligent or smart packaging. Intelligent packaging is a packaging system using different indicators for monitoring the conditions of production, but in particular the conditions during transport and storage. Among these indicators include the time-temperature indicators to monitor changes in temperature, which is exposed the product and to inform consumers about the potential risks associated with consumption of these products. Time temperature indicators are devices that show an irreversible change in a physical characteristic, usually color or shape, in response to temperature history. Some are designed to monitor the evolution of temperature with time along the distribution chain and others are designed to be used in the consumer packages.

Automation of neutral beam source conditioning with artificial intelligence techniques

International Nuclear Information System (INIS)

Johnson, R.R.; Canales, T.W.; Lager, D.L.

1985-01-01

This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

Automation of neutral beam source conditioning with artificial intelligence techniques

International Nuclear Information System (INIS)

Johnson, R.R.; Canales, T.; Lager, D.

1986-01-01

This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

The Effect of Multicultural Experience in Conflicts Management Styles: Mediation of Cultural Intelligence and Self-Monitoring

Directory of Open Access Journals (Sweden)

Gabriela Gonçalves

2015-03-01

Full Text Available Conflict is an inevitable reality both in personal and in organizational life. For being inevitable, the conflict must be managed Defined as a process that occurs when one party feels adversely affected by another (e.g., De Dreu, 1997 the conflict management styles can be analysed as a function of personality variables. In this respect the cultural intelligence, self-monitoring and self-interdependent seem to be relevant variables, since characterised by flexibility and interest in other aspects present in conflict management styles. In this study, we propose that cultural intelligence, associated with the self-interdependent and self-monitoring, can have a positive impact on the choice of most effective interpersonal conflict resolution styles. Being cultural intelligence an attribute of extreme importance, we still sought to determine how the quantity and quality of intercultural contact and self-interdependent present themselves as predictors of it. With a sample of 399 individuals, the proposed model suggests that high levels of cultural intelligence mediated by a high self-monitoring and selfinterdependent positively affect and predict the conflict resolution styles adopted. Given the need to develop abilities aimed at increasing the skills of conflict resolution, this study adds to the existing literature new predictors, contributing to the welfare and performance of human resources, and consequently to success and organizational effectiveness.

Intelligent monitoring of YAG laser welding on steam generator tubes

International Nuclear Information System (INIS)

Hosaka, Shigetaka; Nagura, Yasumi; Ishide, Takashi; Nagashima, Tadashi; Akaba, Takashi

1992-01-01

The 'KASHIKOKI' intelligent device for monitoring the YAG laser welding of steam generator tubes is described in this paper. The 'KASHIKOKI', it monitors the series of six channels, for example, the reflected laser beam and the welding speed, etc. It learns the normal criteria and the anomalous criteria of welding, and discriminates between normal and anomalous welding using the learned criteria, and distinguishes the anomaly into several types. As the results of evaluation test, the degree of correspondence between this device and an expert is about 90%. This paper describes the new methods the multi-variate analysis model for discriminating between normal and anomalous welding, and a neural network model for distinguishing the types of anomaly. (author)

Overnight non-contact continuous vital signs monitoring using an intelligent automatic beam-steering Doppler sensor at 2.4 GHz.

Science.gov (United States)

Batchu, S; Narasimhachar, H; Mayeda, J C; Hall, T; Lopez, J; Nguyen, T; Banister, R E; Lie, D Y C

2017-07-01

Doppler-based non-contact vital signs (NCVS) sensors can monitor heart rates, respiration rates, and motions of patients without physically touching them. We have developed a novel single-board Doppler-based phased-array antenna NCVS biosensor system that can perform robust overnight continuous NCVS monitoring with intelligent automatic subject tracking and optimal beam steering algorithms. Our NCVS sensor achieved overnight continuous vital signs monitoring with an impressive heart-rate monitoring accuracy of over 94% (i.e., within ±5 Beats-Per-Minute vs. a reference sensor), analyzed from over 400,000 data points collected during each overnight monitoring period of ~ 6 hours at a distance of 1.75 meters. The data suggests our intelligent phased-array NCVS sensor can be very attractive for continuous monitoring of low-acuity patients.

An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

Science.gov (United States)

Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

2012-01-01

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

Directory of Open Access Journals (Sweden)

Yen-Lin Chen

2012-08-01

Full Text Available This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

BUSINESS INTELLIGENCE INSTRUMENTS FOR HR MONITORING

Directory of Open Access Journals (Sweden)

Radulescu Magdalena

2009-05-01

Full Text Available Business Intelligence is the combination of the information from several sources, and presenting results in a form that can be used in taking business decisions. Processed and presented in an intelligent way, this information gives the company the advanta

Intelligence and treaty ratification

International Nuclear Information System (INIS)

Sojka, G.L.

1990-01-01

What did the intelligence community and the Intelligence Committee di poorly in regard to the treaty ratification process for arms control? We failed to solve the compartmentalization problem/ This is a second-order problem, and, in general, analysts try to be very open; but there are problems nevertheless. There are very few, if any, people within the intelligence community who are cleared for everything relevant to our monitoring capability emdash short of probably the Director of Central Intelligence and the president emdash and this is a major problem. The formal monitoring estimates are drawn up by individuals who do not have access to all the information to make the monitoring judgements. This paper reports that the intelligence community did not present a formal document on either Soviet incentives of disincentives to cheat or on the possibility of cheating scenarios, and that was a mistake. However, the intelligence community was very responsive in producing those types of estimates, and, ultimately, the evidence behind them in response to questions. Nevertheless, the author thinks the intelligence community would do well to address this issue up front before a treaty is submitted to the Senate for advice and consent

Recommendations for strengthening the infrared technology component of any condition monitoring program

Science.gov (United States)

Nicholas, Jack R., Jr.; Young, R. K.

1999-03-01

place the condition monitoring program in perspective); (11) Use of procedures for Predictive, Condition Monitoring and maintenance in general (To get consistent results); (12) Developing a scheme for predictive, condition monitoring personnel qualification and certification (To provide a career path and incentive to advance skill level and value to the company); (13) Analyst Assignment to Technologies and Related Duties (To make intelligent use of the skills of individuals assigned); (14) Condition Monitoring Analyst Selection Criteria (Key attributes for success are mentioned.); (15) Design and Modification to Support Monitoring (For old and new machinery to facilitate data acquisition); (16) Establishment of a Museum of Components and Samples Pulled from Service for Cause (For orientation and awareness training of operators and managers and exchange of information between analysts); (17) Goals (To promote a proactive program approach for machinery condition improvement).

Health monitoring and rehabilitation of a concrete structure using intelligent materials

Science.gov (United States)

Song, G.; Mo, Y. L.; Otero, K.; Gu, H.

2006-04-01

This paper presents the concept of an intelligent reinforced concrete structure (IRCS) and its application in structural health monitoring and rehabilitation. The IRCS has multiple functions which include self-rehabilitation, self-vibration damping, and self-structural health monitoring. These functions are enabled by two types of intelligent (smart) materials: shape memory alloys (SMAs) and piezoceramics. In this research, Nitinol type SMA and PZT (lead zirconate titanate) type piezoceramics are used. The proposed concrete structure is reinforced by martensite Nitinol cables using the method of post-tensioning. The martensite SMA significantly increases the concrete's damping property and its ability to handle large impact. In the presence of cracks due to explosions or earthquakes, by electrically heating the SMA cables, the SMA cables contract and close up the cracks. In this research, PZT patches are embedded in the concrete structure to detect possible cracks inside the concrete structure. The wavelet packet analysis method is then applied as a signal-processing tool to analyze the sensor signals. A damage index is defined to describe the damage severity for health monitoring purposes. In addition, by monitoring the electric resistance change of the SMA cables, the crack width can be estimated. To demonstrate this concept, a concrete beam specimen with reinforced SMA cables and with embedded PZT patches is fabricated. Experiments demonstrate that the IRC has the ability of self-sensing and self-rehabilitation. Three-point bending tests were conducted. During the loading process, a crack opens up to 0.47 inches. Upon removal of the load and heating the SMA cables, the crack closes up. The damage index formed by wavelet packet analysis of the PZT sensor data predicts and confirms the onset and severity of the crack during the loading. Also during the loading, the electrical resistance value of the SMA cable changes by up to 27% and this phenomenon is used to

A digital filter-based approach to the remote condition monitoring of railway turnouts

International Nuclear Information System (INIS)

Garcia Marquez, Fausto Pedro; Schmid, Felix

2007-01-01

Railway operations in Europe have changed dramatically since the early 1990s, partly as a result of new European Union Directives. Performance targets have become more and more exacting, due to reductions in state support for railways and the need to increasing traffic. More intensive operations also place greater demands on the hardware of the railway. This is true for both rolling stock and infrastructure subsystems and components, particularly so in the case of the latter where the time available for maintenance is being reduced. The authors of this paper focus on the railway infrastructure, and more specifically on points. These are critical elements whose reliability is key to the operation of the whole system. Using intelligent monitoring systems, it is possible to predict problems and enable quick recovery before component failures disrupt operations. The authors have studied the application of remote condition monitoring to point mechanisms and their operation, and have identified algorithms which may be used to identify incipient failures. In this paper, the authors propose a Kalman filter for the linear discrete data filtering problem encountered when using current sensor data in a point condition monitoring system. The reason for applying Kalman filtering in this study was to increase the reliability of the model presented to the rule-based decision mechanism

A simple condition monitoring model for a direct monitoring process

NARCIS (Netherlands)

Christer, A.H.; Wang, Wenbin

1995-01-01

This paper addresses the problem of condition monitoring of a component which has available a measure of condition called wear. Wear accumulates over time and monitoring inspections are performed at chosen times to monitor and measure the cumulative wear. If past measurements of wear are available

SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

Science.gov (United States)

Lawson, Denise L.; James, Mark L.

1989-01-01

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

Science.gov (United States)

Saeed, M.; Lieu, C.; Raber, G.; Mark, R. G.

2002-01-01

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism.

Science.gov (United States)

Li, Fengmei; Wei, Yaoguang; Chen, Yingyi; Li, Daoliang; Zhang, Xu

2015-12-09

Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism

Directory of Open Access Journals (Sweden)

Fengmei Li

2015-12-01

Full Text Available Dissolved oxygen (DO is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

Intelligence and Nuclear Proliferation: Lessons Learned

International Nuclear Information System (INIS)

Hansen, Keith A.

2011-09-01

Intelligence agencies play a fundamental role in the prevention of nuclear proliferation, as they help to understand other countries' intentions and assess their technical capabilities and the nature of their nuclear activities. The challenges in this area remain, however, formidable. Past experiences and the discoveries of Iraq's WMD programs, of North Korean nuclear weapon program, and of Iranian activities, have put into question the ability of intelligence to monitor small, clandestine proliferation activities from either states or non-state entities. This Proliferation Paper analyzes the complex challenges intelligence faces and the various roles it plays in supporting national and international nuclear non-proliferation efforts, and reviews its track record. In an effort to shed light on the role and contribution of intelligence in national and international efforts to halt, if not prevent, further nuclear weapon proliferation, this paper first analyzes the challenges intelligence faces in monitoring small, clandestine proliferation activities and the role it plays in supporting non-proliferation efforts. It then reviews the intelligence track record in monitoring proliferation including the lessons learned from Iraq. Finally, it addresses whether it is possible for intelligence to accurately monitor future clandestine proliferation efforts. (author)

Condition Monitoring of Cables Task 3 Report: Condition Monitoring Techniques for Electric Cables

Energy Technology Data Exchange (ETDEWEB)

Villaran, M.; Lofaro, R.; na

2009-11-30

For more than 20 years the NRC has sponsored research studying electric cable aging degradation, condition monitoring, and environmental qualification testing practices for electric cables used in nuclear power plants. This report summarizes several of the most effective and commonly used condition monitoring techniques available to detect damage and measure the extent of degradation in electric cable insulation. The technical basis for each technique is summarized, along with its application, trendability of test data, ease of performing the technique, advantages and limitations, and the usefulness of the test results to characterize and assess the condition of electric cables.

Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

Directory of Open Access Journals (Sweden)

Karel Octavianus Bachri

2017-07-01

Full Text Available A3S(Arwin-Adang-Aciek-Sembiring is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN. First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

Intelligence and Neurophysiological Markers of Error Monitoring Relate to Children's Intellectual Humility.

Science.gov (United States)

Danovitch, Judith H; Fisher, Megan; Schroder, Hans; Hambrick, David Z; Moser, Jason

2017-09-18

This study explored developmental and individual differences in intellectual humility (IH) among 127 children ages 6-8. IH was operationalized as children's assessment of their knowledge and willingness to delegate scientific questions to experts. Children completed measures of IH, theory of mind, motivational framework, and intelligence, and neurophysiological measures indexing early (error-related negativity [ERN]) and later (error positivity [Pe]) error-monitoring processes related to cognitive control. Children's knowledge self-assessment correlated with question delegation, and older children showed greater IH than younger children. Greater IH was associated with higher intelligence but not with social cognition or motivational framework. ERN related to self-assessment, whereas Pe related to question delegation. Thus, children show separable epistemic and social components of IH that may differentially contribute to metacognition and learning. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Maintenance cost avoidance through comprehensive condition monitoring

International Nuclear Information System (INIS)

Miller, G.P.; McClymonds, S.L.

1990-01-01

Condition monitoring, the measurement and trending of a critical parameter for predictive maintenance, has reached new levels of acceptance and application within the utility and manufacturing industry. Commercially available systems extend well beyond traditional vibration-monitoring systems to include such areas as online wear, crack and leak detection, and stress monitoring. The challenge facing industry is to integrate the information generated from condition monitoring. Current studies indicate that the effectiveness of predictive maintenance depends much more on the program that is established to apply the monitoring techniques than on the monitoring equipment itself. This paper presents a five-phase approach to developing a condition monitoring program

Design of a real-time tax-data monitoring intelligent card system

Science.gov (United States)

Gu, Yajun; Bi, Guotang; Chen, Liwei; Wang, Zhiyuan

2009-07-01

To solve the current problem of low efficiency of domestic Oil Station's information management, Oil Station's realtime tax data monitoring system has been developed to automatically access tax data of Oil pumping machines, realizing Oil-pumping machines' real-time automatic data collection, displaying and saving. The monitoring system uses the noncontact intelligent card or network to directly collect data which can not be artificially modified and so seals the loopholes and improves the tax collection's automatic level. It can perform real-time collection and management of the Oil Station information, and find the problem promptly, achieves the automatic management for the entire process covering Oil sales accounting and reporting. It can also perform remote query to the Oil Station's operation data. This system has broad application future and economic value.

Active and intelligent packaging systems for a modern society.

Science.gov (United States)

Realini, Carolina E; Marcos, Begonya

2014-11-01

Active and intelligent packaging systems are continuously evolving in response to growing challenges from a modern society. This article reviews: (1) the different categories of active and intelligent packaging concepts and currently available commercial applications, (2) latest packaging research trends and innovations, and (3) the growth perspectives of the active and intelligent packaging market. Active packaging aiming at extending shelf life or improving safety while maintaining quality is progressing towards the incorporation of natural active agents into more sustainable packaging materials. Intelligent packaging systems which monitor the condition of the packed food or its environment are progressing towards more cost-effective, convenient and integrated systems to provide innovative packaging solutions. Market growth is expected for active packaging with leading shares for moisture absorbers, oxygen scavengers, microwave susceptors and antimicrobial packaging. The market for intelligent packaging is also promising with strong gains for time-temperature indicator labels and advancements in the integration of intelligent concepts into packaging materials. Copyright © 2014 Elsevier Ltd. All rights reserved.

Condition Indicators for Gearbox Condition Monitoring Systems

Directory of Open Access Journals (Sweden)

P. Večeř

2005-01-01

Full Text Available Condition monitoring systems for manual transmissions based on vibration diagnostics are widely applied in industry. The systems deal with various condition indicators, most of which are focused on a specific type of gearbox fault. Frequently used condition indicators (CIs are described in this paper. The ability of a selected condition indicator to describe the degree of gearing wear was tested using vibration signals acquired during durability testing of manual transmission with helical gears. 

Wireless Intelligent Monitoring and Control System of Greenhouse Temperature Based on Fuzzy-PID

Directory of Open Access Journals (Sweden)

Mei ZHAN

2014-03-01

Full Text Available Control effect is not ideal for traditional control method and wired control system, since greenhouse temperature has such characteristics as nonlinear and longtime lag. Therefore, Fuzzy- PID control method was introduced and radio frequency chip CC1110 was applied to design greenhouse wireless intelligent monitoring and control system. The design of the system, the component of nodes and the developed intelligent management software system were explained in this paper. Then describe the design of the control algorithm Fuzzy-PID. By simulating the new method in Matlab software, the results showed that Fuzzy-PID method small overshoot and better dynamic performance compared with general PID control. It has shorter settling time and no steady-state error compared with fuzzy control. It can meet requirements in greenhouse production.

Artificial Intelligence in Autonomous Telescopes

Science.gov (United States)

Mahoney, William; Thanjavur, Karun

2011-03-01

Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

Development of intelligent monitoring purifier for indoor PM 2.5

Science.gov (United States)

Lou, Guanting; Zhu, Rong; Guo, Jiangwei; Wei, Yongqing

2018-03-01

The particulate matter 2.5 (PM2.5) refers to tiny particles or droplets in the air that are two and one half microns or less in width. PM2.5 is an air pollutant that is a concern for people’s health when levels in air are high. The intelligent monitoring purifier was developed to detect indoor PM2.5 concentration before and after purification and the monitoring data could be displayed on the LCD screen, displaying different color patterns according to the concentrations. Through the Bluetooth transport module, real-time values could also display on the mobile phone and voice broadcast PM2.5 concentration level in the air. When PM2.5 concentration is higher than the setting threshold, the convection fan rotation and the speed can be remote controlled with mobile phone through the Bluetooth transport. Therefore, the efficiency and scope of the purification could be enhanced and further better air quality could be achieved.

The application of artificial intelligence on the optimal solution of the operating conditions of continuous casting; Aplicacao da inteligencia artificial na solucao otima das condicoes operacionais do lingotamento continuo

Energy Technology Data Exchange (ETDEWEB)

Spim Junior, J.A.; Ierardi, M.C.F.; Garcia, A. [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica

1995-12-31

This work presents the development of a software that incorporates artificial intelligence techniques, directly applied to the metallurgical industry, particularly to those using the continuous casting process for ingot production. The essential parts of the continuous casting equipment which must be subjected to monitoring are presented, and a methodology of physical settlements in each cooling region as well. The modification performed by the intelligent program taking into account the critical rules conducting to an efficient solidification, are compared with real time simulation of ingot surface temperatures. The efficiency of the intelligent system is assured by final product quality parameters. This approach is applied to the real dimension of a slab continuous caster under real operation conditions, demonstrating that very good results can be attained by using an heuristic search 11 refs., 4 figs., 4 tabs.

Artificial Intelligence Application in Power Generation Industry: Initial considerations

Science.gov (United States)

Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

2016-03-01

With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

Simulation of Artificial Intelligence for Automotive Air-conditioning System

Institute of Scientific and Technical Information of China (English)

YUAN Xiao-mei; CHEN You-hua; CHEN Zhi-jiu

2002-01-01

The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

Intelligent Control and Health Monitoring. Chapter 3

Science.gov (United States)

Garg, Sanjay; Kumar, Aditya; Mathews, H. Kirk; Rosenfeld, Taylor; Rybarik, Pavol; Viassolo, Daniel E.

2009-01-01

Advanced model-based control architecture overcomes the limitations state-of-the-art engine control and provides the potential of virtual sensors, for example for thrust and stall margin. "Tracking filters" are used to adapt the control parameters to actual conditions and to individual engines. For health monitoring standalone monitoring units will be used for on-board analysis to determine the general engine health and detect and isolate sudden faults. Adaptive models open up the possibility of adapting the control logic to maintain desired performance in the presence of engine degradation or to accommodate any faults. Improved and new sensors are required to allow sensing at stations within the engine gas path that are currently not instrumented due in part to the harsh conditions including high operating temperatures and to allow additional monitoring of vibration, mass flows and energy properties, exhaust gas composition, and gas path debris. The environmental and performance requirements for these sensors are summarized.

A Wireless and Batteryless Intelligent Carbon Monoxide Sensor.

Science.gov (United States)

Chen, Chen-Chia; Sung, Gang-Neng; Chen, Wen-Ching; Kuo, Chih-Ting; Chue, Jin-Ju; Wu, Chieh-Ming; Huang, Chun-Ming

2016-09-23

Carbon monoxide (CO) poisoning from natural gas water heaters is a common household accident in Taiwan. We propose a wireless and batteryless intelligent CO sensor for improving the safety of operating natural gas water heaters. A micro-hydropower generator supplies power to a CO sensor without battery (COSWOB) (2.5 W at a flow rate of 4.2 L/min), and the power consumption of the COSWOB is only ~13 mW. The COSWOB monitors the CO concentration in ambient conditions around natural gas water heaters and transmits it to an intelligent gateway. When the CO level reaches a dangerous level, the COSWOB alarm sounds loudly. Meanwhile, the intelligent gateway also sends a trigger to activate Wi-Fi alarms and sends notifications to the mobile device through the Internet. Our strategy can warn people indoors and outdoors, thereby reducing CO poisoning accidents. We also believe that our technique not only can be used for home security but also can be used in industrial applications (for example, to monitor leak occurrence in a pipeline).

An intelligent system for monitoring and diagnosis of the CO{sub 2} capture process

Energy Technology Data Exchange (ETDEWEB)

Zhou, Q.; Chan, C.W.; Tontiwachwuthikul, P. [University of Regina, Regina, SK (Canada). Faculty of Engineering

2011-07-15

Amine-based carbon dioxide capture has been widely considered as a feasible ideal technology for reducing large-scale CO{sub 2} emissions and mitigating global warming. The operation of amine-based CO{sub 2} capture is a complicated task, which involves monitoring over 100 process parameters and careful manipulation of numerous valves and pumps. The current research in the field of CO{sub 2} capture has emphasized the need for improving CO{sub 2} capture efficiency and enhancing plant performance. In the present study, artificial intelligence techniques were applied for developing a knowledge-based expert system that aims at effectively monitoring and controlling the CO{sub 2} capture process and thereby enhancing CO{sub 2} capture efficiency. In developing the system, the inferential modeling technique (IMT) was applied to analyze the domain knowledge and problem-solving techniques, and a knowledge base was developed on DeltaV Simulate. The expert system helps to enhance CO{sub 2} capture system performance and efficiency by reducing the time required for diagnosis and problem solving if abnormal conditions occur. The expert system can be used as a decision-support tool that helps inexperienced operators control the plant: it can be used also for training novice operators.

Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring

Directory of Open Access Journals (Sweden)

Zhaozhuo Xu

2016-01-01

Full Text Available Wireless sensor networks are proved to be effective in long-time localized torrential rain monitoring. However, the existing widely used architecture of wireless sensor networks for rain monitoring relies on network transportation and back-end calculation, which causes delay in response to heavy rain in localized areas. Our work improves the architecture by applying logistic regression and support vector machine classification to an intelligent wireless sensor node which is created by Raspberry Pi. The sensor nodes in front-end not only obtain data from sensors, but also can analyze the probabilities of upcoming heavy rain independently and give early warnings to local clients in time. When the sensor nodes send the probability to back-end server, the burdens of network transport are released. We demonstrate by simulation results that our sensor system architecture has potentiality to increase the local response to heavy rain. The monitoring capacity is also raised.

Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

Science.gov (United States)

Nalamwar, H. S.; Ivanov, M. A.; Baidali, S. A.

2017-01-01

The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the system especially for renewable energy source application such as solar photovoltaic (PV), data-acquisition systems had been used to collect all the data regarding the installed system. In this paper the development of a smart automated monitoring & controlling system for the solar panel is described, the core idea is based on IoT (the Internet of Things). The measurements of data are made using sensors, block management data acquisition modules, and a software system. Then, all the real-time data collection of the electrical output parameters of the PV plant such as voltage, current and generated electricity is displayed and stored in the block management. The proposed system is smart enough to make suggestions if the panel is not working properly, to display errors, to remind about maintenance of the system through email or SMS, and to rotate panels according to a sun position using the Ephemeral table that stored in the system. The advantages of the system are the performance of the solar panel system which can be monitored and analyzed.

Acoustic multivariate condition monitoring - AMCM

Energy Technology Data Exchange (ETDEWEB)

Rosenhave, P E [Vestfold College, Maritime Dept., Toensberg (Norway)

1998-12-31

In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

Acoustic multivariate condition monitoring - AMCM

Energy Technology Data Exchange (ETDEWEB)

Rosenhave, P.E. [Vestfold College, Maritime Dept., Toensberg (Norway)

1997-12-31

In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design

Science.gov (United States)

Hall, Travis; Nguyen, Tam Q.; Mayeda, Jill C.; Lie, Paul E.; Lopez, Jerry; Banister, Ron E.

2017-01-01

It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients’ long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is

Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design.

Science.gov (United States)

Hall, Travis; Lie, Donald Y C; Nguyen, Tam Q; Mayeda, Jill C; Lie, Paul E; Lopez, Jerry; Banister, Ron E

2017-11-15

It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients' long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient's vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is sleeping

Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design

Directory of Open Access Journals (Sweden)

Travis Hall

2017-11-01

Full Text Available It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients’ long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF non-contact vital signs (NCVS monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the

Non-stationary condition monitoring through event alignment

DEFF Research Database (Denmark)

Pontoppidan, Niels Henrik; Larsen, Jan

2004-01-01

We present an event alignment framework which enables change detection in non-stationary signals. change detection. Classical condition monitoring frameworks have been restrained to laboratory settings with stationary operating conditions, which are not resembling real world operation....... In this paper we apply the technique for non-stationary condition monitoring of large diesel engines based on acoustical emission sensor signals. The performance of the event alignment is analyzed in an unsupervised probabilistic detection framework based on outlier detection with either Principal Component...... Analysis or Gaussian Processes modeling. We are especially interested in the true performance of the condition monitoring performance with mixed aligned and unaligned data, e.g. detection of fault condition of unaligned examples versus false alarms of aligned normal condition data. Further, we expect...

Proactive condition monitoring of low-speed machines

CERN Document Server

Stamboliska, Zhaklina; Moczko, Przemyslaw

2015-01-01

This book broadens readers’ understanding of proactive condition monitoring of low-speed machines in heavy industries. It focuses on why low-speed machines are different than others and how maintenance of these machines should be implemented with particular attention. The authors explain the best available monitoring techniques for various equipment and the principle of how to get proactive information from each technique. They further put forward possible strategies for application of FEM for detection of faults and technical assessment of machinery. Implementation phases are described and industrial case-studies of proactive condition monitoring are included. Proactive Condition Monitoring of Low-Speed Machines is an essential resource for engineers and technical managers across a range of industries as well as design engineers working in industrial product development. This book also: ·         Explains the practice of proactive condition monitoring and illustrates implementation phases ·   ...

The Use of Hidden Markov Models for Anomaly Detection in Nuclear Core Condition Monitoring

Science.gov (United States)

Stephen, Bruce; West, Graeme M.; Galloway, Stuart; McArthur, Stephen D. J.; McDonald, James R.; Towle, Dave

2009-04-01

Unplanned outages can be especially costly for generation companies operating nuclear facilities. Early detection of deviations from expected performance through condition monitoring can allow a more proactive and managed approach to dealing with ageing plant. This paper proposes an anomaly detection framework incorporating the use of the Hidden Markov Model (HMM) to support the analysis of nuclear reactor core condition monitoring data. Fuel Grab Load Trace (FGLT) data gathered within the UK during routine refueling operations has been seen to provide information relating to the condition of the graphite bricks that comprise the core. Although manual analysis of this data is time consuming and requires considerable expertise, this paper demonstrates how techniques such as the HMM can provide analysis support by providing a benchmark model of expected behavior against which future refueling events may be compared. The presence of anomalous behavior in candidate traces is inferred through the underlying statistical foundation of the HMM which gives an observation likelihood averaged along the length of the input sequence. Using this likelihood measure, the engineer can be alerted to anomalous behaviour, indicating data which might require further detailed examination. It is proposed that this data analysis technique is used in conjunction with other intelligent analysis techniques currently employed to analyse FGLT to provide a greater confidence measure in detecting anomalous behaviour from FGLT data.

Monitoring and diagnosis of vegetable growth based on internet of things

Science.gov (United States)

Zhang, Qian; Yu, Feng; Fu, Rong; Li, Gang

2017-10-01

A new condition monitoring method of vegetable growth was proposed, which was based on internet of things. It was combined remote environmental monitoring, video surveillance, intelligently decision-making and two-way video consultation together organically.

Intelligent monitoring and fault diagnosis for ATLAS TDAQ: a complex event processing solution

CERN Document Server

Magnoni, Luca; Luppi, Eleonora

Effective monitoring and analysis tools are fundamental in modern IT infrastructures to get insights on the overall system behavior and to deal promptly and effectively with failures. In recent years, Complex Event Processing (CEP) technologies have emerged as effective solutions for information processing from the most disparate fields: from wireless sensor networks to financial analysis. This thesis proposes an innovative approach to monitor and operate complex and distributed computing systems, in particular referring to the ATLAS Trigger and Data Acquisition (TDAQ) system currently in use at the European Organization for Nuclear Research (CERN). The result of this research, the AAL project, is currently used to provide ATLAS data acquisition operators with automated error detection and intelligent system analysis. The thesis begins by describing the TDAQ system and the controlling architecture, with a focus on the monitoring infrastructure and the expert system used for error detection and automated reco...

Machinery condition monitoring principles and practices

CERN Document Server

Mohanty, Amiya Ranjan

2015-01-01

Find the Fault in the MachinesDrawing on the author's more than two decades of experience with machinery condition monitoring and consulting for industries in India and abroad, Machinery Condition Monitoring: Principles and Practices introduces the practicing engineer to the techniques used to effectively detect and diagnose faults in machines. Providing the working principle behind the instruments, the important elements of machines as well as the technique to understand their conditions, this text presents every available method of machine fault detection occurring in machines in general, an

Nuclear propulsion control and health monitoring

Science.gov (United States)

Walter, P. B.; Edwards, R. M.

1993-11-01

An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.

Hybrid intelligent monironing systems for thermal power plant trips

Science.gov (United States)

Barsoum, Nader; Ismail, Firas Basim

2012-11-01

Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

Towards an Intelligent Monitoring System for Patients with Obstrusive Sleep Apnea

Directory of Open Access Journals (Sweden)

Xavier Rafael-Palou

2017-12-01

Full Text Available Due to the growing incidence of chronic diseases and aging populations, the pressure to control costs and the expectations of continuous improvements in the quality of service have increased the need to understand how healthcare is provided and to determine whether cost-effective improvements to care practices can be made. In the case of people suffering Obstructive Sleep Apnea, patients using self-administer nasal Continuous Positive Airway Pressure (CPAP may receive information on the treatment only once they go to a visit with the lung specialist. In this paper, we propose an IoT-based Intelligent Monitoring System that relies on machine learning to achieve a threefold goal: (1 it is aimed at early detecting compliance in order to predict CPAP usage; (2 it monitors the actual adherence degree to the treatment to keep informed both the patient and the lung specialists; and (3 it sends recommendations to the patient to empower her/him and to better follow up.

Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

Science.gov (United States)

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Construction and application of an intelligent air quality monitoring system for healthcare environment.

Science.gov (United States)

Yang, Chao-Tung; Liao, Chi-Jui; Liu, Jung-Chun; Den, Walter; Chou, Ying-Chyi; Tsai, Jaw-Ji

2014-02-01

Indoor air quality monitoring in healthcare environment has become a critical part of hospital management and policy. Manual air sampling and analysis are cost-inhibitive and do not provide real-time air quality data and response measures. In this month-long study over 14 sampling locations in a public hospital in Taiwan, we observed a positive correlation between CO(2) concentration and population, total bacteria, and particulate matter concentrations, thus monitoring CO(2) concentration as a general indicator for air quality could be a viable option. Consequently, an intelligent environmental monitoring system consisting of a CO(2)/temperature/humidity sensor, a digital plug, and a ZigBee Router and Coordinator was developed and tested. The system also included a backend server that received and analyzed data, as well as activating ventilation and air purifiers when CO(2) concentration exceeded a pre-set value. Alert messages can also be delivered to offsite users through mobile devices.

Technology review: prototyping platforms for monitoring ambient conditions.

Science.gov (United States)

Afolaranmi, Samuel Olaiya; Ramis Ferrer, Borja; Martinez Lastra, Jose Luis

2018-05-08

The monitoring of ambient conditions in indoor spaces is very essential owing to the amount of time spent indoors. Specifically, the monitoring of air quality is significant because contaminated air affects the health, comfort and productivity of occupants. This research work presents a technology review of prototyping platforms for monitoring ambient conditions in indoor spaces. It involves the research on sensors (for CO 2 , air quality and ambient conditions), IoT platforms, and novel and commercial prototyping platforms. The ultimate objective of this review is to enable the easy identification, selection and utilisation of the technologies best suited for monitoring ambient conditions in indoor spaces. Following the review, it is recommended to use metal oxide sensors, optical sensors and electrochemical sensors for IAQ monitoring (including NDIR sensors for CO 2 monitoring), Raspberry Pi for data processing, ZigBee and Wi-Fi for data communication, and ThingSpeak IoT platform for data storage, analysis and visualisation.

Software for Intelligent System Health Management

Science.gov (United States)

Trevino, Luis C.

2004-01-01

This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

OpenAIRE

Bo Sun; Qiang Feng; Songjie Li

2012-01-01

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

Directory of Open Access Journals (Sweden)

Gang Ma

2015-01-01

Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

Development of an Intelligent Monitoring System for Geological Carbon Sequestration (GCS) Systems

Science.gov (United States)

Sun, A. Y.; Jeong, H.; Xu, W.; Hovorka, S. D.; Zhu, T.; Templeton, T.; Arctur, D. K.

2016-12-01

To provide stakeholders timely evidence that GCS repositories are operating safely and efficiently requires integrated monitoring to assess the performance of the storage reservoir as the CO2 plume moves within it. As a result, GCS projects can be data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, and accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. How to correlate anomaly detected by a certain sensor to events observed by other devices to verify leakage incidents? How to optimally allocate resources for task-oriented monitoring if reservoir integrity is in question? These are issues that warrant further investigation before real integration can take place. In this work, we are building a web-based, data integration, assimilation, and learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS will be an intelligent monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in high-throughput database, complex event processing, data assimilation, and machine learning technologies. Results will be demonstrated using realistic data and model derived from a GCS site.

ANN Based Tool Condition Monitoring System for CNC Milling Machines

Directory of Open Access Journals (Sweden)

Mota-Valtierra G.C.

2011-10-01

Full Text Available Most of the companies have as objective to manufacture high-quality products, then by optimizing costs, reducing and controlling the variations in its production processes it is possible. Within manufacturing industries a very important issue is the tool condition monitoring, since the tool state will determine the quality of products. Besides, a good monitoring system will protect the machinery from severe damages. For determining the state of the cutting tools in a milling machine, there is a great variety of models in the industrial market, however these systems are not available to all companies because of their high costs and the requirements of modifying the machining tool in order to attach the system sensors. This paper presents an intelligent classification system which determines the status of cutt ers in a Computer Numerical Control (CNC milling machine. This tool state is mainly detected through the analysis of the cutting forces drawn from the spindle motors currents. This monitoring system does not need sensors so it is no necessary to modify the machine. The correct classification is made by advanced digital signal processing techniques. Just after acquiring a signal, a FIR digital filter is applied to the data to eliminate the undesired noisy components and to extract the embedded force components. A Wavelet Transformation is applied to the filtered signal in order to compress the data amount and to optimize the classifier structure. Then a multilayer perceptron- type neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.

Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

Directory of Open Access Journals (Sweden)

Bin Chen

2014-01-01

Full Text Available It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province. The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Intelligent low-level RF system by non-destructive beam monitoring device for cyclotrons

Science.gov (United States)

Sharifi Asadi Malafeh, M. S.; Ghergherehchi, M.; Afarideh, H.; Chai, J. S.; Yoon, Sang Kim

2016-04-01

The project of a 10 MeV PET cyclotron accelerator for medical diagnosis and treatment was started at Amirkabir University of Technology in 2012. The low-level RF system of the cyclotron accelerator is designed to stabilize acceleration voltage and control the resonance frequency of the cavity. In this work an Intelligent Low Level Radio Frequency Circuit or ILLRF, suitable for most AVF cyclotron accelerators, is designed using a beam monitoring device and narrow band tunable band-pass filter. In this design, the RF phase detection does not need signal processing by a microcontroller.

Intelligibility of clear speech: effect of instruction.

Science.gov (United States)

Lam, Jennifer; Tjaden, Kris

2013-10-01

The authors investigated how clear speech instructions influence sentence intelligibility. Twelve speakers produced sentences in habitual, clear, hearing impaired, and overenunciate conditions. Stimuli were amplitude normalized and mixed with multitalker babble for orthographic transcription by 40 listeners. The main analysis investigated percentage-correct intelligibility scores as a function of the 4 conditions and speaker sex. Additional analyses included listener response variability, individual speaker trends, and an alternate intelligibility measure: proportion of content words correct. Relative to the habitual condition, the overenunciate condition was associated with the greatest intelligibility benefit, followed by the hearing impaired and clear conditions. Ten speakers followed this trend. The results indicated different patterns of clear speech benefit for male and female speakers. Greater listener variability was observed for speakers with inherently low habitual intelligibility compared to speakers with inherently high habitual intelligibility. Stable proportions of content words were observed across conditions. Clear speech instructions affected the magnitude of the intelligibility benefit. The instruction to overenunciate may be most effective in clear speech training programs. The findings may help explain the range of clear speech intelligibility benefit previously reported. Listener variability analyses suggested the importance of obtaining multiple listener judgments of intelligibility, especially for speakers with inherently low habitual intelligibility.

Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies

CERN Document Server

Watanabe, Toyohide; Phillips-Wren, Gloria; Howlett, Robert; Jain, Lakhmi

2012-01-01

The Intelligent Decision Technologies (IDT) International Conference encourages an interchange of research on intelligent systems and intelligent technologies that enhance or improve decision making. The focus of IDT is interdisciplinary and includes research on all aspects of intelligent decision technologies, from fundamental development to real applications. IDT has the potential to expand their support of decision making in such areas as finance, accounting, marketing, healthcare, medical and diagnostic systems, military decisions, production and operation, networks, traffic management, crisis response, human-machine interfaces, financial and stock market monitoring and prediction, and robotics. Intelligent decision systems implement advances in intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, and genetic algorithms, among others.  Emerging areas of active research include virtual decision environments, social networking, 3D human-machine interfaces, cognitive interfaces,...

Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).

Science.gov (United States)

Nadiri, Ata Allah; Gharekhani, Maryam; Khatibi, Rahman; Sadeghfam, Sina; Moghaddam, Asghar Asghari

2017-01-01

This research presents a Supervised Intelligent Committee Machine (SICM) model to assess groundwater vulnerability indices of an aquifer. SICM uses Artificial Neural Networks (ANN) to overarch three Artificial Intelligence (AI) models: Support Vector Machine (SVM), Neuro-Fuzzy (NF) and Gene Expression Programming (GEP). Each model uses the DRASTIC index, the acronym of 7 geological, hydrological and hydrogeological parameters, which collectively represents intrinsic (or natural) vulnerability and gives a sense of contaminants, such as nitrate-N, penetrating aquifers from the surface. These models are trained to modify or condition their DRASTIC index values by measured nitrate-N concentration. The three AI-techniques often perform similarly but have differences as well and therefore SICM exploits the situation to improve the modeled values by producing a hybrid modeling results through selecting better performing SVM, NF and GEP components. The models of the study area at Ardabil aquifer show that the vulnerability indices by the DRASTIC framework produces sharp fronts but AI models smoothen the fronts and reflect a better correlation with observed nitrate values; SICM improves on the performances of three AI models and cope well with heterogeneity and uncertain parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

Measuring Emotional Intelligence: Where We Are Today.

Science.gov (United States)

Finegan, Jane E.

Emotional intelligence has been defined as "the ability to monitor one's own and others' feelings and emotions, to discriminate among them, and to use this information to guide one's thinking and actions" (P. Salovey and J. Mayer, 1990). As a subset of social intelligence and of personal intelligences (H. Gardner, 1983), emotional…

Research on intelligent monitor for 3D power distribution of reactor core

International Nuclear Information System (INIS)

Xia, Hong; Li, Bin; Liu, Jianxin

2014-01-01

Highlights: • Core power distribution of ex-core measurement system has been reconstructed. • Building up an artificial intelligence model for 3-D core power distribution. • Error of the experiments has been reduced to 0.76%. • Methods for improving the accuracy of the model have been obtained. - Abstract: A real-time monitor for 3D reactor power distribution is critical for nuclear safety and high efficiency of NPP’s operation as well as for optimizing the control system, especially when the nuclear power plant (NPP) works at a certain power level or it works in load following operation. This paper was based on analyzing the monitor for 3D reactor power distribution technologies used in modern NPPs. Furthermore, considering the latest research outcomes, the paper proposed a method based on using an ex-core neutron detector system and a neural network to set up a real time monitor system for reactor’s 3D power distribution supervision. The results of the experiments performed on a reactor simulation machine illustrated that the new monitor system worked very well for a certain burn-up range during the fuel cycle. In addition, this new model could reduce the errors associated with the fitting of the distribution effectively, and several optimization methods were also obtained to improve the accuracy of the simulation model

The Impact of Emotional Intelligence on Conditions of Trust Among Leaders at the Kentucky Department for Public Health

Directory of Open Access Journals (Sweden)

Jennifer Redmond Knight

2015-03-01

Full Text Available There has been limited leadership research on emotional intelligence and trust in governmental public health settings. The purpose of this study was to identify and seek to understand the relationship between trust and elements of emotional intelligence, including stress management, at the Kentucky Department for Public Health. The Kentucky Department for Public Health (KDPH serves as Kentucky’s state governmental health department. KDPH is led by a Commissioner and composed of seven primary divisions and 25 branches within those divisions. The study was a non-randomized cross-sectional study utilizing electronic surveys that evaluated conditions of trust among staff members and emotional intelligence among supervisors. Pearson correlation coefficients and corresponding p-values are presented to provide the association between emotional intelligence scales and the conditions of trust. Significant positive correlations were observed between supervisors' stress management and the staff members' trust or perception of supervisors' loyalty(r=0.6, p=0.01, integrity(r=0.5, p=0.03, receptivity(r=0.6, p=0.02, promise fulfillment(r=0.6, p=0.02 and availability (r=0.5, p=0.07. This research lays the foundation for emotional intelligence and trust research and leadership training in other governmental public health settings, such as local, other state, national or international organizations. This original research provides metrics to assess the public health workforce with attention to organizational management and leadership constructs. The survey tools could be used in other governmental public health settings in order to develop tailored training opportunities related to emotional intelligence and trust organizations.

Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

International Nuclear Information System (INIS)

Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

1996-01-01

The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

Intelligent Monitoring System with High Temperature Distributed Fiberoptic Sensor for Power Plant Combustion Processes

Energy Technology Data Exchange (ETDEWEB)

Kwang Y. Lee; Stuart S. Yin; Andre Boehman

2006-09-26

The objective of the proposed work is to develop an intelligent distributed fiber optical sensor system for real-time monitoring of high temperature in a boiler furnace in power plants. Of particular interest is the estimation of spatial and temporal distributions of high temperatures within a boiler furnace, which will be essential in assessing and controlling the mechanisms that form and remove pollutants at the source, such as NOx. The basic approach in developing the proposed sensor system is three fold: (1) development of high temperature distributed fiber optical sensor capable of measuring temperatures greater than 2000 C degree with spatial resolution of less than 1 cm; (2) development of distributed parameter system (DPS) models to map the three-dimensional (3D) temperature distribution for the furnace; and (3) development of an intelligent monitoring system for real-time monitoring of the 3D boiler temperature distribution. Under Task 1, we have set up a dedicated high power, ultrafast laser system for fabricating in-fiber gratings in harsh environment optical fibers, successfully fabricated gratings in single crystal sapphire fibers by the high power laser system, and developed highly sensitive long period gratings (lpg) by electric arc. Under Task 2, relevant mathematical modeling studies of NOx formation in practical combustors have been completed. Studies show that in boiler systems with no swirl, the distributed temperature sensor may provide information sufficient to predict trends of NOx at the boiler exit. Under Task 3, we have investigated a mathematical approach to extrapolation of the temperature distribution within a power plant boiler facility, using a combination of a modified neural network architecture and semigroup theory. Given a set of empirical data with no analytic expression, we first developed an analytic description and then extended that model along a single axis.

Expert System for Diagnostics and Status Monitoring of NPP Water Chemistry Condition

International Nuclear Information System (INIS)

Shvedova, M.N.; Kritski, V.G.; Zakharova, S.V.; Nikolaev, F.V.; Benediktov, V.B.

2002-01-01

Water chemistry condition (WCC) has been the subject of constant study and improvement up to the present day. It is connected with the presence of a direct relationship between the violation of water chemistry regulation on the one hand and components reliability of the circuit's equipment and cost-effectiveness of their operation on the other. It dictates the necessity to apply different optimization methods in the field of monitoring and use of information - analytical and diagnostic systems to assess WCC quality, control and support. By now NPP experts have broad experience in revealing and removing the causes of WCC disturbances. However this knowledge is often of an intuitive, non-classified nature, scattered among various working documents, which makes their transfer difficult. Based on what has been mentioned above, special attention is currently being paid to the problem of creating expert diagnostic systems for supporting the optimum WCC. The existing developments in this field (DIWA, Smart chem Works, the water quality control system at the Onagava NPP etc. [1,3,4,5] are based on wide use of experts' knowledge. Such expert diagnostic systems for supporting WCC refer to the new generation of intellectual control methods, which allow the incorporation of the latest achievements both in the field of water chemistry simulation and in the field of artificial intelligence and computer technologies. LI 'VNIPIET' employees have, for several years, been developing an expert diagnostic system for supporting WCC and status monitoring of RBMK - reactor NPPs [2]. This system has not only conveniently organized the traditional functions of information acquisition and storage, a complete presentation of information in the form of tables, graphs of a dynamical changes of parameters and formation regular reports, diagnostic functions and issuing recommendations on WCC correction, but it also allows the assessment of confidence in the diagnosis made, relying on a wide

Modern techniques for condition monitoring of railway vehicle dynamics

International Nuclear Information System (INIS)

Ngigi, R W; Pislaru, C; Ball, A; Gu, F

2012-01-01

A modern railway system relies on sophisticated monitoring systems for maintenance and renewal activities. Some of the existing conditions monitoring techniques perform fault detection using advanced filtering, system identification and signal analysis methods. These theoretical approaches do not require complex mathematical models of the system and can overcome potential difficulties associated with nonlinearities and parameter variations in the system. Practical applications of condition monitoring tools use sensors which are mounted either on the track or rolling stock. For instance, monitoring wheelset dynamics could be done through the use of track-mounted sensors, while vehicle-based sensors are preferred for monitoring the train infrastructure. This paper attempts to collate and critically appraise the modern techniques used for condition monitoring of railway vehicle dynamics by analysing the advantages and shortcomings of these methods.

Intelligence system for reactor operator informational support

International Nuclear Information System (INIS)

Prangishvili, I.V.; Pashchenko, F.F.; Saprykin, E.M.

1989-01-01

Problems related to creation and introduction at NPP of highly efficient and reliable systems for monitoring and control of working processes and intelligence-endowed systems of operator informational support (ISOIS) are considered. The main units included in ISOIS are considered. The main units included in ISOIS are described. The unit of current state monitoring provides information for the operator, which is necessary under concrete conditions for the process monitoring and control, so as to avoid emergencies and affers a program of actions in a dialogue mode for the operator. The identification unit is designed for the obtaining of assessed values of process parameters (neutron fields, temperatures, pressures) and basic equipment (reactivity coefficients, fuel rod weights, time of delay). The prediction unit evaluates the behaviour of process parameters and process state in various situations. 9 refs

Putting intelligent structured intermittent auscultation (ISIA) into practice.

Science.gov (United States)

Maude, Robyn M; Skinner, Joan P; Foureur, Maralyn J

2016-06-01

Fetal monitoring guidelines recommend intermittent auscultation for the monitoring of fetal wellbeing during labour for low-risk women. However, these guidelines are not being translated into practice and low-risk women birthing in institutional maternity units are increasingly exposed to continuous cardiotocographic monitoring, both on admission to hospital and during labour. When continuous fetal monitoring becomes routinised, midwives and obstetricians lose practical skills around intermittent auscultation. To support clinical practice and decision-making around auscultation modality, the intelligent structured intermittent auscultation (ISIA) framework was developed. The purpose of this discussion paper is to describe the application of intelligent structured intermittent auscultation in practice. The intelligent structured intermittent auscultation decision-making framework is a knowledge translation tool that supports the implementation of evidence into practice around the use of intermittent auscultation for fetal heart monitoring for low-risk women during labour. An understanding of the physiology of the materno-utero-placental unit and control of the fetal heart underpin the development of the framework. Intelligent structured intermittent auscultation provides midwives with a robust means of demonstrating their critical thinking and clinical reasoning and supports their understanding of normal physiological birth. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Business Intelligence

OpenAIRE

Petersen, Anders

2001-01-01

Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

Development of condition monitoring and diagnosis system for standby diesel generator

Energy Technology Data Exchange (ETDEWEB)

Choi, Kwang Hee; Park, Jong Hyuck; Park, Jong Eun [Korea Electric Power Research Institute, Daejeon (Korea, Republic of)

2009-05-15

The emergency diesel generator (EDG) of the nuclear power plant is designed to supply the power to the nuclear on Station Black Out (SBO) condition. The operation reliability of onsite emergency diesel generator should be ensured by a condition monitoring system designed to monitor and analysis the condition of diesel generator. For this purpose, we have developed the online condition monitoring and diagnosis system for the wolsong unit 3 and 4 standby diesel generator including diesel engine performance. In this paper, technologies of condition monitoring and diagnosis system (SDG MDS) for the wolsong standby diesel generator are described. By using the condition monitoring module of the SDG MDS, performance monitoring function for major operating parameters of EDG reliability program required by Reg. guide 1.155 can be operated as on line monitoring system.

Development of condition monitoring and diagnosis system for standby diesel generator

International Nuclear Information System (INIS)

Choi, Kwang Hee; Park, Jong Hyuck; Park, Jong Eun

2009-01-01

The emergency diesel generator (EDG) of the nuclear power plant is designed to supply the power to the nuclear on Station Black Out (SBO) condition. The operation reliability of onsite emergency diesel generator should be ensured by a condition monitoring system designed to monitor and analysis the condition of diesel generator. For this purpose, we have developed the online condition monitoring and diagnosis system for the wolsong unit 3 and 4 standby diesel generator including diesel engine performance. In this paper, technologies of condition monitoring and diagnosis system (SDG MDS) for the wolsong standby diesel generator are described. By using the condition monitoring module of the SDG MDS, performance monitoring function for major operating parameters of EDG reliability program required by Reg. guide 1.155 can be operated as on line monitoring system

Nuclear Energy Research Initiative (NERI): On-Line Intelligent Self-Diagnostic Monitoring for Next Generation Nuclear Plants - Phase I Annual Report

International Nuclear Information System (INIS)

Bond, L.G.; Doctor, S.R.; Gilbert, R.W.; Jarrell, D.B.; Greitzer, F.L.; Meador, R.J.

2000-01-01

OAK-B135 This OSTI ID belongs to an IWO and is being released out of the system. The Program Manager Rebecca Richardson has confirmed that all reports have been received. The objective of this project is to design and demonstrate the operation of the real-time intelligent self-diagnostic and prognostic system for next generation nuclear power plant systems. This new self-diagnostic technology is titled, ''On-Line Intelligent Self-Diagnostic Monitoring System'' (SDMS). This project provides a proof-of-principle technology demonstration for SDMS on a pilot plant scale service water system, where a distributed array of sensors is integrated with active components and passive structures typical of next generation nuclear power reactor and plant systems. This project employs state-of-the-art sensors, instrumentation, and computer processing to improve the monitoring and assessment of the power reactor system and to provide diagnostic and automated prognostics capabilities

Quaternion Based Thermal Condition Monitoring System

Science.gov (United States)

Wong, Wai Kit; Loo, Chu Kiong; Lim, Way Soong; Tan, Poi Ngee

In this paper, we will propose a new and effective machine condition monitoring system using log-polar mapper, quaternion based thermal image correlator and max-product fuzzy neural network classifier. Two classification characteristics namely: peak to sidelobe ratio (PSR) and real to complex ratio of the discrete quaternion correlation output (p-value) are applied in the proposed machine condition monitoring system. Large PSR and p-value observe in a good match among correlation of the input thermal image with a particular reference image, while small PSR and p-value observe in a bad/not match among correlation of the input thermal image with a particular reference image. In simulation, we also discover that log-polar mapping actually help solving rotation and scaling invariant problems in quaternion based thermal image correlation. Beside that, log-polar mapping can have a two fold of data compression capability. Log-polar mapping can help smoother up the output correlation plane too, hence makes a better measurement way for PSR and p-values. Simulation results also show that the proposed system is an efficient machine condition monitoring system with accuracy more than 98%.

Hybrid Modeling Improves Health and Performance Monitoring

Science.gov (United States)

2007-01-01

Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

Condition monitoring a key component in the preventive maintenance

International Nuclear Information System (INIS)

Isar, C.

2006-01-01

The preventive maintenance programs are necessary to ensure that nuclear safety significant equipment will function when it is supposed to. Diesel generator, pumps, motor operated valves and air operated control valves are typically operated every three months. When you drive a car, you depend on lot of sounds, the feel of the steering wheel and gauges to determine if the car is running correctly. Similarly with operating equipment for a power plant - sounds or vibration of the equipment or the gauges and test equipment indicate a problem or degradation, actions are taken to correct the deficiency. Due to safety and economical reason diagnostic and monitoring systems are of growing interest in all complex industrial production. Diagnostic systems are requested to detect, diagnose and localize faulty operating conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. In this context it is a need for using various on-line and off-line condition monitoring and diagnostics, non-destructive inspection techniques and surveillance. The condition monitoring technique used in nuclear power plant Cernavoda are presented in this paper. The selection of components and parameters to be monitored, monitoring and diagnostics techniques used are incorporated into a preventive maintenance program. Modern measurement technique in combination with advanced computerized data processing and acquisition show new ways in the field of machine surveillance. The diagnostic capabilities of predictive maintenance technologies have increased recently year with advances made in sensor technologies. The paper will focus on the following condition monitoring technique: - oil analysis - acoustic leakage monitoring - thermography - valve diagnostics: motor operated valve, air operated valve and check valve - motor current signature - vibration monitoring and rotating machine monitoring and diagnostics For each condition monitoring

Monitoring and operational support on nuclear power plants using an artificial intelligence system

International Nuclear Information System (INIS)

Bianchi, P.H.; Baptista Filho, B.D.

2009-01-01

The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

Monitoring and operational support on nuclear power plants using an artificial intelligence system

Energy Technology Data Exchange (ETDEWEB)

Bianchi, Paulo H.; Baptista Filho, Benedito D., E-mail: phbianchi@gmail.co, E-mail: bdbfilho@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2009-07-01

The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

Westinghouse use of artificial intelligence in signal interpretation

International Nuclear Information System (INIS)

Mark, R.H.

1984-01-01

This paper discusses Westinghouse's use of artificial intelligence to assist inspectors who routinely monitor the thousands of tubes in nuclear steam generators. Using the AI technology has made the inspection process easier to learn and to apply. The system uses pattern recognition to identify off-normal conditions. As part of the in-service inspection program for nuclear power reactors, utilities make a practice of inspecting the condition of the large heat exchangers that produce the steam that turns the electric turbine generator. The same data are presented for inspection using form, motion, and color to call attention to off-normal signal patterns

Muscular condition monitoring system using fiber bragg grating sensors

International Nuclear Information System (INIS)

Kim, Heon Young; Lee, Jin Hyuk; Kim, Dae Hyun

2014-01-01

Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the muscle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

Muscular condition monitoring system using fiber bragg grating sensors

Energy Technology Data Exchange (ETDEWEB)

Kim, Heon Young; Lee, Jin Hyuk; Kim, Dae Hyun [Seoul National University of Technology, Seoul (Korea, Republic of)

2014-10-15

Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the muscle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

Nuclear Energy Research Initiative (NERI): On-Line Intelligent Self-Diagnostic Monitoring for Next Generation Nuclear Plants - Phase I Annual Report

Energy Technology Data Exchange (ETDEWEB)

L. J. Bond; S. R. Doctor; R. W. Gilbert; D. B. Jarrell; F. L. Greitzer; R. J. Meador

2000-09-01

OAK-B135 This OSTI ID belongs to an IWO and is being released out of the system. The Program Manager Rebecca Richardson has confirmed that all reports have been received. The objective of this project is to design and demonstrate the operation of the real-time intelligent self-diagnostic and prognostic system for next generation nuclear power plant systems. This new self-diagnostic technology is titled, ''On-Line Intelligent Self-Diagnostic Monitoring System'' (SDMS). This project provides a proof-of-principle technology demonstration for SDMS on a pilot plant scale service water system, where a distributed array of sensors is integrated with active components and passive structures typical of next generation nuclear power reactor and plant systems. This project employs state-of-the-art sensors, instrumentation, and computer processing to improve the monitoring and assessment of the power reactor system and to provide diagnostic and automated prognostics capabilities.

Vibration-based condition monitoring industrial, aerospace and automotive applications

CERN Document Server

Randall, Robert Bond

2010-01-01

""Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring"" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material

Operational performance of generator condition monitors

International Nuclear Information System (INIS)

Braun, J.M.; Brown, G.

1990-01-01

This paper reports on the generator condition monitor (GCM) developed in an attempt to detect overheating inside large turbine generators. As part of a broader study on rotating machinery diagnostics, generator condition monitors were evaluated under field conditions in a 550 MW turbogenerator. Small 100 W resistors coated with insulating paints and varnishes were mounted inside the generator to simulate insulation overheating. The GCM responded very rapidly to an overheating event, typically within two minutes, even for hot spots as small s 10 cm 2 . Similarly the aerosols produced on overheating were found extremely short lived, decaying within two to three minutes after overheating was discontinued. Use of heated ion chambers was found to desensitize the GCM regardless of the nature of the overheated insulation and in some cases would altogether prevent the GCM from reaching the 50% pre-set alarm level commonly used on GCMs

Condition Monitoring of the SSE Generation Fleet

Science.gov (United States)

Twiddle, J.; Muthuraman, S.; Connolly, N.

2012-05-01

SSE (previously known as Scottish and Southern Energy) operates a diverse portfolio of generation plant, including coal, gas and renewable plant with a total generation capacity of 11,375MW (Sept 2011). In recent years a group of specialists dedicated to providing condition monitoring services has been established at the Equipment Performance Centre (EPC) based at Knottingley, West Yorkshire. We aim to illustrate the role of the EPC and the methods used for monitoring the generation fleet with the objective of maintaining asset integrity, reducing risk of plant failure and unplanned outages and describe the challenges which have been overcome in establishing the EPC. This paper describes methods including vibration and process data analysis, model-based techniques and on-site testing used for monitoring of generation plant, including gas turbines, steam turbines, generators and steam raising plant. These condition monitoring processes utilise available data, adding value to the business, by bringing services in-house and capturing knowledge of plant operation for the benefit of the whole fleet.

Wind Turbine Gearbox Oil Filtration and Condition Monitoring

Energy Technology Data Exchange (ETDEWEB)

Sheng, Shuangwen

2015-10-25

This is an invited presentation for a pre-conference workshop, titled advances and opportunities in lubrication: wind turbine, at the 2015 Society of Tribologists and Lubrication Engineers (STLE) Tribology Frontiers Conference held in Denver, CO. It gives a brief overview of wind turbine gearbox oil filtration and condition monitoring by highlighting typical industry practices and challenges. The presentation starts with an introduction by covering recent growth of global wind industry, reliability challenges, benefits of oil filtration and condition monitoring, and financial incentives to conduct wind operation and maintenance research, which includes gearbox oil filtration and condition monitoring work presented herein. Then, the presentation moves on to oil filtration by stressing the benefits of filtration, discussing typical main- and offline-loop practices, highlighting important factors considered when specifying a filtration system, and illustrating real-world application challenges through a cold-start example. In the next section on oil condition monitoring, a discussion on oil sample analysis, oil debris monitoring, oil cleanliness measurements and filter analysis is given based on testing results mostly obtained by and at NREL, and by pointing out a few challenges with oil sample analysis. The presentation concludes with a brief touch on future research and development (R and D) opportunities. It is hoping that the information presented can inform the STLE community to start or redirect their R and D work to help the wind industry advance.

ATLAS diamond Beam Condition Monitor

CERN Document Server

Gorišek, A; Dolenc, I; Frais-Kölbl, H; Griesmayer, E; Kagan, H; Korpar, S; Kramberger, G; Mandic, I; Meyer, M; Mikuz, M; Pernegger, H; Smith, S; Trischuk, W; Weilhammer, P; Zavrtanik, M

2007-01-01

The ATLAS experiment has chosen to use diamond for its Beam Condition Monitor (BCM) given its radiation hardness, low capacitance and short charge collection time. In addition, due to low leakage current diamonds do not require cooling. The ATLAS Beam Condition Monitoring system is based on single beam bunch crossing measurements rather than integrating the accumulated particle flux. Its fast electronics will allow separation of LHC collisions from background events such as beam gas interactions or beam accidents. There will be two stations placed symmetrically about the interaction point along the beam axis at . Timing of signals from the two stations will provide almost ideal separation of beam–beam interactions and background events. The ATLAS BCM module consists of diamond pad detectors of area and thickness coupled to a two-stage RF current amplifier. The production of the final detector modules is almost done. A S/N ratio of 10:1 has been achieved with minimum ionizing particles (MIPs) in the test bea...

Advance in study of intelligent diagnostic method for nuclear power plant

International Nuclear Information System (INIS)

Zhou Gang; Yang Li

2008-01-01

The advance of research on the application of three types of intelligent diagnostic approach based on neural network (ANN), fuzzy logic and expert system to the operation status monitoring and fault diagnosis of nuclear power plant (NPP) was reviewed. The research status and characters on status monitoring and fault diagnosis approaches based on neural network, fuzzy logic and expert system for nuclear power plant were analyzed. The development trend of applied research on intelligent diagnostic approaches for nuclear power plant was explored. The analysis results show that the research achievements on intelligent diagnostic approaches based on fuzzy logic and expert system for nuclear power plant are not much relatively. The research of intelligent diagnostic approaches for nuclear power plant concentrate on the aspect of operation status monitoring and fault diagnosis based on neural networks for nuclear power plant. The advancing tendency of intelligent diagnostic approaches for nuclear power plant is the combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple neural network diagnostic approaches. (authors)

Augmented reality enabling intelligence exploitation at the edge

Science.gov (United States)

Kase, Sue E.; Roy, Heather; Bowman, Elizabeth K.; Patton, Debra

2015-05-01

Today's Warfighters need to make quick decisions while interacting in densely populated environments comprised of friendly, hostile, and neutral host nation locals. However, there is a gap in the real-time processing of big data streams for edge intelligence. We introduce a big data processing pipeline called ARTEA that ingests, monitors, and performs a variety of analytics including noise reduction, pattern identification, and trend and event detection in the context of an area of operations (AOR). Results of the analytics are presented to the Soldier via an augmented reality (AR) device Google Glass (Glass). Non-intrusive AR devices such as Glass can visually communicate contextually relevant alerts to the Soldier based on the current mission objectives, time, location, and observed or sensed activities. This real-time processing and AR presentation approach to knowledge discovery flattens the intelligence hierarchy enabling the edge Soldier to act as a vital and active participant in the analysis process. We report preliminary observations testing ARTEA and Glass in a document exploitation and person of interest scenario simulating edge Soldier participation in the intelligence process in disconnected deployment conditions.

Recent progress in competitive intelligence, competitive technical intelligence and knowledge management

Directory of Open Access Journals (Sweden)

Dou Henri

2011-04-01

Full Text Available This paper discusses the role of competitive intelligence and knowledge management to create, maintain and sustain competitive advantages. The triple helix model, based on the integration of the public sector (government, business models (private corporations and universities to promote innovation is examined. Research trends in competitive intelligence are presented. It concludes that the systematic use of the technology monitoring should support the comparison between various business models of companies that hold the market best practices and form a basis to knowledge for the decision making process and strategies development.

Decision Support System for Condition Monitoring Technologies

NARCIS (Netherlands)

Mouatamir, Abderrahim

2018-01-01

The technological feasibility of a condition-based maintenance (CBM) policy is intrinsically related to the suitable selection of condition monitoring (CM) technologies such as vibration- and oil analysis or other non-destructive testing (NDT) techniques such as radiographic- and magnetic particle

A study on the condition monitoring for safety-related electric cables

Energy Technology Data Exchange (ETDEWEB)

Kim, Chul Hwan; Ahn, S. P.; Yeo, S. M.; Kang, Y. S.; Ahn, S. M.; Kim, I. S.; Kim, D. S.; Kang, J. S. [Sungkyunkwan Univ., Suwon (Korea, Republic of)

2002-03-15

In this report, we have studied compositions and characteristics of various types of insulation material for cables in Nuclear Power Plant. We arrange relationship with condition monitoring methods. Also, we propose new condition monitoring method using third harmonic frequency. We test the proposed method with CV cables. We also describe about feature of condition monitoring such as application, theory, characteristic, thereby other engineer can confirm to advantage and disadvantage for each method, and possibly choice adequate condition monitoring method for various types of cables.

Integrated reliability condition monitoring and maintenance of equipment

CERN Document Server

Osarenren, John

2015-01-01

Consider a Viable and Cost-Effective Platform for the Industries of the Future (IOF) Benefit from improved safety, performance, and product deliveries to your customers. Achieve a higher rate of equipment availability, performance, product quality, and reliability. Integrated Reliability: Condition Monitoring and Maintenance of Equipment incorporates reliable engineering and mathematical modeling to help you move toward sustainable development in reliability condition monitoring and maintenance. This text introduces a cost-effective integrated reliability growth monitor, integrated reliability degradation monitor, technological inheritance coefficient sensors, and a maintenance tool that supplies real-time information for predicting and preventing potential failures of manufacturing processes and equipment. The author highlights five key elements that are essential to any improvement program: improving overall equipment and part effectiveness, quality, and reliability; improving process performance with maint...

Workshop on power plant cable condition monitoring: Proceedings

International Nuclear Information System (INIS)

Del Valle, L.

1988-07-01

A three-day workshop on cable condition monitoring was held in San Francisco on Fegruary 16--18, 1988. The workshop was cosponsored by the Nuclear Power, Electrical Systems, and Coal Combustion Systems Divisions of the Electric Power Research Institute. The primary objective of the workshop was to identify the state-of-the-art for cable condition monitoring. Twenty-five technical papers as well as EPRI research programs were presented at the technical sessions. Four working group sessions and one general session were held on each of two days. Each group session provided a forum for participants to exchange ideas and to discuss in more depth research for cable condition monitoring, existing and innovative testing technology, and utility and NRC needs for testing. Recommendations from the working groups were summarized and presented at the end of the workshop

Intelligent monitoring, control, and security of critical infrastructure systems

CERN Document Server

Polycarpou, Marios

2015-01-01

This book describes the challenges that critical infrastructure systems face, and presents state of the art solutions to address them. How can we design intelligent systems or intelligent agents that can make appropriate real-time decisions in the management of such large-scale, complex systems? What are the primary challenges for critical infrastructure systems? The book also provides readers with the relevant information to recognize how important infrastructures are, and their role in connection with a society’s economy, security and prosperity. It goes on to describe state-of-the-art solutions to address these points, including new methodologies and instrumentation tools (e.g. embedded software and intelligent algorithms) for transforming and optimizing target infrastructures. The book is the most comprehensive resource to date for professionals in both the private and public sectors, while also offering an essential guide for students and researchers in the areas of modeling and analysis of critical in...

Guiding rules for development of intelligent monitoring system of nuclear power plants

International Nuclear Information System (INIS)

Kitamura, M.; Furukawa, H.; Kozma, R.; Washio, T.

1996-01-01

General frameworks and major component techniques for intelligent monitoring of nuclear power plants are presented. The key concept, diversity-based design, is to provide advisory information through consensus of multiple agents, each performing operational decision-making by focusing on mutually different information obtained from the plant. The multi-agent design scheme allows to attain high credibility and tolerance against sensor failure in fault detection and causal reasoning. The advantage of the proposed scheme realized by multiple neural networks was clearly demonstrated through numerical experiments with anomalies in a pressurized water reactor. Relevant techniques are also introduced for diagnostic information evaluation in specified symptoms, and for remedial procedure synthesis. A new architecture for future implementation of the proposed scheme, worm-type multi-agent system, is also proposed as a promising candidate. (author)

Digital intelligence sources transporter

International Nuclear Information System (INIS)

Zhang Zhen; Wang Renbo

2011-01-01

It presents from the collection of particle-ray counting, infrared data communication, real-time monitoring and alarming, GPRS and other issues start to realize the digital management of radioactive sources, complete the real-time monitoring of all aspects, include the storing of radioactive sources, transporting and using, framing intelligent radioactive sources transporter, as a result, achieving reliable security supervision of radioactive sources. (authors)

Intelligent model-based diagnostics for vehicle health management

Science.gov (United States)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Intelligent robotic tracker

Science.gov (United States)

Otaguro, W. S.; Kesler, L. O.; Land, K. C.; Rhoades, D. E.

1987-01-01

An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

Plant-wide integrated equipment monitoring and analysis system

International Nuclear Information System (INIS)

Morimoto, C.N.; Hunter, T.A.; Chiang, S.C.

2004-01-01

A nuclear power plant equipment monitoring system monitors plant equipment and reports deteriorating equipment conditions. The more advanced equipment monitoring systems can also provide information for understanding the symptoms and diagnosing the root cause of a problem. Maximizing the equipment availability and minimizing or eliminating consequential damages are the ultimate goals of equipment monitoring systems. GE Integrated Equipment Monitoring System (GEIEMS) is designed as an integrated intelligent monitoring and analysis system for plant-wide application for BWR plants. This approach reduces system maintenance efforts and equipment monitoring costs and provides information for integrated planning. This paper describes GEIEMS and how the current system is being upgraded to meet General Electric's vision for plant-wide decision support. (author)

Computational intelligence techniques in health care

CERN Document Server

Zhou, Wengang; Satheesh, P

2016-01-01

This book presents research on emerging computational intelligence techniques and tools, with a particular focus on new trends and applications in health care. Healthcare is a multi-faceted domain, which incorporates advanced decision-making, remote monitoring, healthcare logistics, operational excellence and modern information systems. In recent years, the use of computational intelligence methods to address the scale and the complexity of the problems in healthcare has been investigated. This book discusses various computational intelligence methods that are implemented in applications in different areas of healthcare. It includes contributions by practitioners, technology developers and solution providers.

An intelligent approach for cooling radiator fault diagnosis based on infrared thermal image processing technique

International Nuclear Information System (INIS)

Taheri-Garavand, Amin; Ahmadi, Hojjat; Omid, Mahmoud; Mohtasebi, Seyed Saeid; Mollazade, Kaveh; Russell Smith, Alan John; Carlomagno, Giovanni Maria

2015-01-01

This research presents a new intelligent fault diagnosis and condition monitoring system for classification of different conditions of cooling radiator using infrared thermal images. The system was adopted to classify six types of cooling radiator faults; radiator tubes blockage, radiator fins blockage, loose connection between fins and tubes, radiator door failure, coolant leakage, and normal conditions. The proposed system consists of several distinct procedures including thermal image acquisition, image pre-processing, image processing, two-dimensional discrete wavelet transform (2D-DWT), feature extraction, feature selection using a genetic algorithm (GA), and finally classification by artificial neural networks (ANNs). The 2D-DWT is implemented to decompose the thermal images. Subsequently, statistical texture features are extracted from the original images and are decomposed into thermal images. The significant selected features are used to enhance the performance of the designed ANN classifier for the 6 types of cooling radiator conditions (output layer) in the next stage. For the tested system, the input layer consisted of 16 neurons based on the feature selection operation. The best performance of ANN was obtained with a 16-6-6 topology. The classification results demonstrated that this system can be employed satisfactorily as an intelligent condition monitoring and fault diagnosis for a class of cooling radiator. - Highlights: • Intelligent fault diagnosis of cooling radiator using thermal image processing. • Thermal image processing in a multiscale representation structure by 2D-DWT. • Selection features based on a hybrid system that uses both GA and ANN. • Application of ANN as classifier. • Classification accuracy of fault detection up to 93.83%

Hybrid Intelligent Warning System for Boiler tube Leak Trips

Directory of Open Access Journals (Sweden)

Singh Deshvin

2017-01-01

Full Text Available Repeated boiler tube leak trips in coal fired power plants can increase operating cost significantly. An early detection and diagnosis of boiler trips is essential for continuous safe operations in the plant. In this study two artificial intelligent monitoring systems specialized in boiler tube leak trips have been proposed. The first intelligent warning system (IWS-1 represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2 represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. The Extreme Learning Machine (ELM methodology was also adopted in IWS-1 and compared with traditional training algorithms. Genetic algorithm (GA was adopted in IWS-2 to optimize the ANN topology and the boiler parameters. An integrated data preparation framework was established for 3 real cases of boiler tube leak trip based on a thermal power plant in Malaysia. Both the IWSs were developed using MATLAB coding for training and validation. The hybrid IWS-2 performed better than IWS-1.The developed system was validated to be able to predict trips before the plant monitoring system. The proposed artificial intelligent system could be adopted as a reliable monitoring system of the thermal power plant boilers.

Instantaneous angular speed monitoring of gearboxes under non-cyclic stationary load conditions

Science.gov (United States)

Stander, C. J.; Heyns, P. S.

2005-07-01

Recent developments in the condition monitoring and asset management market have led to the commercialisation of online vibration-monitoring systems. These systems are primarily utilised to monitor large mineral mining equipment such as draglines, continuous miners and hydraulic shovels. Online monitoring systems make diagnostic information continuously available for asset management, production outsourcing and maintenance alliances with equipment manufacturers. However, most online vibration-monitoring systems are based on conventional vibration-monitoring technologies, which are prone to giving false equipment deterioration warnings on gears that operate under fluctuating load conditions. A simplified mathematical model of a gear system was developed to illustrate the feasibility of monitoring the instantaneous angular speed (IAS) as a means of monitoring the condition of gears that are subjected to fluctuating load conditions. A distinction is made between cyclic stationary load modulation and non-cyclic stationary load modulation. It is shown that rotation domain averaging will suppress the modulation caused by non-cyclic stationary load conditions but will not suppress the modulation caused by cyclic stationary load conditions. An experimental investigation on a test rig indicated that the IAS of a gear shaft could be monitored with a conventional shaft encoder to indicate a deteriorating gear fault condition.

Intelligent fractions learning system: implementation

CSIR Research Space (South Africa)

Smith, Andrew C

2011-05-01

Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...

Design of intelligent house system based on Yeelink

Directory of Open Access Journals (Sweden)

Lin Zhi-Huang

2016-01-01

Full Text Available In order to monitor the security situation of house in real time, an intelligent house remote monitoring system is designed based on Yeelink cloud services and ZigBee wireless communication technology. This system includes three parts, ZigBee wireless sensor networks, intelligent house gateway and Yeelink Cloud Services. Users can access Yeelink website or APP to get real time information in the house, receiving information including gas concentration, temperature. Also, remote commands can be sent from mobile devices to control the household appliances. The user who can monitor and control the house effectively through a simple and convenient user interface, will feel much more safe and comfortable.

Intelligent Integrated Health Management for a System of Systems

Science.gov (United States)

Smith, Harvey; Schmalzel, John; Figueroa, Fernando

2008-01-01

implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3

A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

Directory of Open Access Journals (Sweden)

Grover Zurita

2016-09-01

Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

ATLAS diamond Beam Condition Monitor

Energy Technology Data Exchange (ETDEWEB)

Gorisek, A. [CERN (Switzerland)]. E-mail: andrej.gorisek@cern.ch; Cindro, V. [J. Stefan Institute (Slovenia); Dolenc, I. [J. Stefan Institute (Slovenia); Frais-Koelbl, H. [Fotec (Austria); Griesmayer, E. [Fotec (Austria); Kagan, H. [Ohio State University, OH (United States); Korpar, S. [J. Stefan Institute (Slovenia); Kramberger, G. [J. Stefan Institute (Slovenia); Mandic, I. [J. Stefan Institute (Slovenia); Meyer, M. [CERN (Switzerland); Mikuz, M. [J. Stefan Institute (Slovenia); Pernegger, H. [CERN (Switzerland); Smith, S. [Ohio State University, OH (United States); Trischuk, W. [University of Toronto (Canada); Weilhammer, P. [CERN (Switzerland); Zavrtanik, M. [J. Stefan Institute (Slovenia)

2007-03-01

The ATLAS experiment has chosen to use diamond for its Beam Condition Monitor (BCM) given its radiation hardness, low capacitance and short charge collection time. In addition, due to low leakage current diamonds do not require cooling. The ATLAS Beam Condition Monitoring system is based on single beam bunch crossing measurements rather than integrating the accumulated particle flux. Its fast electronics will allow separation of LHC collisions from background events such as beam gas interactions or beam accidents. There will be two stations placed symmetrically about the interaction point along the beam axis at z=+/-183.8cm. Timing of signals from the two stations will provide almost ideal separation of beam-beam interactions and background events. The ATLAS BCM module consists of diamond pad detectors of 1cm{sup 2} area and 500{mu}m thickness coupled to a two-stage RF current amplifier. The production of the final detector modules is almost done. A S/N ratio of 10:1 has been achieved with minimum ionizing particles (MIPs) in the test beam setup at KEK. Results from the test beams and bench measurements are presented.

ATLAS diamond Beam Condition Monitor

International Nuclear Information System (INIS)

Gorisek, A.; Cindro, V.; Dolenc, I.; Frais-Koelbl, H.; Griesmayer, E.; Kagan, H.; Korpar, S.; Kramberger, G.; Mandic, I.; Meyer, M.; Mikuz, M.; Pernegger, H.; Smith, S.; Trischuk, W.; Weilhammer, P.; Zavrtanik, M.

2007-01-01

The ATLAS experiment has chosen to use diamond for its Beam Condition Monitor (BCM) given its radiation hardness, low capacitance and short charge collection time. In addition, due to low leakage current diamonds do not require cooling. The ATLAS Beam Condition Monitoring system is based on single beam bunch crossing measurements rather than integrating the accumulated particle flux. Its fast electronics will allow separation of LHC collisions from background events such as beam gas interactions or beam accidents. There will be two stations placed symmetrically about the interaction point along the beam axis at z=+/-183.8cm. Timing of signals from the two stations will provide almost ideal separation of beam-beam interactions and background events. The ATLAS BCM module consists of diamond pad detectors of 1cm 2 area and 500μm thickness coupled to a two-stage RF current amplifier. The production of the final detector modules is almost done. A S/N ratio of 10:1 has been achieved with minimum ionizing particles (MIPs) in the test beam setup at KEK. Results from the test beams and bench measurements are presented

Construction of health monitoring system for traveler based on the mobile Internet

Directory of Open Access Journals (Sweden)

Wei Haoqian

2017-04-01

Full Text Available With the development of communication technology and computer technology,intelligent terminals represented by smartphone and mobile Internet have become indispensable tools in people's life and work.As the intelligent terminal platform is widely used and the wearable medical equipment is gradually mature,this paper based on the Internet designs and develops a health monitoring system for travelers who suffered from chronic diseases or worried about their physical conditions,to provide a whole process of health monitoring and assistant service.The system,combing smartphone and wearable medical devices,uploads the health and physical signs data to the health monitoring platform through the mobile Internet.Then the professionals statistically analyze the data and provide appropriate advice and guidance,so as to achieve the remote medical treatment for travelers.

Condition Monitoring for DC-link Capacitors Based on Artificial Neural Network Algorithm

DEFF Research Database (Denmark)

Soliman, Hammam Abdelaal Hammam; Wang, Huai; Gadalla, Brwene Salah Abdelkarim

2015-01-01

hardware will reduce the cost, and therefore could be more promising for industry applications. A condition monitoring method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implementation of the ANN to the DC-link capacitor condition monitoring in a back......In power electronic systems, capacitor is one of the reliability critical components . Recently, the condition monitoring of capacitors to estimate their health status have been attracted by the academic research. Industry applications require more reliable power electronics products...... with preventive maintenance. However, the existing capacitor condition monitoring methods suffer from either increased hardware cost or low estimation accuracy, being the challenges to be adopted in industry applications. New development in condition monitoring technology with software solutions without extra...

Electric machines modeling, condition monitoring, and fault diagnosis

CERN Document Server

Toliyat, Hamid A; Choi, Seungdeog; Meshgin-Kelk, Homayoun

2012-01-01

With countless electric motors being used in daily life, in everything from transportation and medical treatment to military operation and communication, unexpected failures can lead to the loss of valuable human life or a costly standstill in industry. To prevent this, it is important to precisely detect or continuously monitor the working condition of a motor. Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis reviews diagnosis technologies and provides an application guide for readers who want to research, develop, and implement a more effective fault diagnosis and condi

Pump failure leads to alternative vertical pump condition monitoring technique

International Nuclear Information System (INIS)

DeVilliers, Adriaan; Glandon, Kevin

2011-01-01

Condition monitoring and detecting early signs of potential failure mechanisms present particular problems in vertical pumps. Most often, the majority of the pump assembly is not readily accessible for visual or audible inspection or conventional vibration monitoring techniques using accelerometers and/or proximity sensors. The root cause failure analysis of a 2-stage vertical centrifugal service-water pump at a nuclear power generating facility in the USA is presented, highlighting this long standing challenge in condition monitoring of vertical pumps. This paper will summarize the major findings of the root cause analysis (RCA), highlight the limitations of traditional monitoring techniques, and present an expanded application of motor current monitoring as a means to gain insight into the mechanical performance and condition of a pump. The 'real-world' example of failure, monitoring and correlation of the monitoring technique to a detailed pump disassembly inspection is also presented. This paper will explain some of the reasons behind well known design principles requiring natural frequency separation from known forcing frequencies, as well as explore an unexpected submerged brittle fracture failure mechanism, and how such issues may be avoided. (author)

Intelligent poly (vinyl alcohol)-chitosan nanoparticles-mulberry extracts films capable of monitoring pH variations.

Science.gov (United States)

Ma, Qianyun; Liang, Tieqiang; Cao, Lele; Wang, Lijuan

2018-03-01

The aim of this study was to prepare a visually responsive intelligent film based on poly (vinyl alcohol) (PVA), chitosan nanoparticles (CHNPs) and mulberry extracts (MBE). CHNPs were first prepared by using ionotropic gelation method to enhance the mechanical properties of PVA based films. The morphology, particle size, zeta potential and crystallinity of CHNPs were measured. The resultant CHNPs were spherical with a diameter of 381.2nm, with high stability and a zeta potential of 49.1±1.33mV. The film with 6% CHNPs (P-C6) had the highest tensile strength (∼73.43MPa). MBE was incorporated into the P-C6 film. The film containing 20% MBE had the highest tensile strength and showed visible color responses to variations across pH 1-13. The film was tested by monitoring the spoilage of fish. The color of the film changed from red to green as the fish spoiled. Therefore, the pH responsive intelligent film developed here can be used as a package label to detect food spoilage. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating structural health and condition monitoring

DEFF Research Database (Denmark)

May, Allan; Thöns, Sebastian; McMillan, David

2015-01-01

window’ allowing for the possible detection of faults up to 6 months in advance. The SHM system model uses a reduction in the probability of failure factor to account for lower modelling uncertainties. A case study is produced that shows a reduction in operating costs and also a reduction in risk......There is a large financial incentive to minimise operations and maintenance (O&M) costs for offshore wind power by optimising the maintenance plan. The integration of condition monitoring (CM) and structural health monitoring (SHM) may help realise this. There is limited work on the integration...

Electrical condition monitoring method for polymers

Science.gov (United States)

Watkins, Jr. Kenneth S.; Morris, Shelby J.; Masakowski, Daniel D.; Wong, Ching Ping; Luo, Shijian

2010-02-16

An electrical condition monitoring method utilizes measurement of electrical resistivity of a conductive composite degradation sensor to monitor environmentally induced degradation of a polymeric product such as insulated wire and cable. The degradation sensor comprises a polymeric matrix and conductive filler. The polymeric matrix may be a polymer used in the product, or it may be a polymer with degradation properties similar to that of a polymer used in the product. The method comprises a means for communicating the resistivity to a measuring instrument and a means to correlate resistivity of the degradation sensor with environmentally induced degradation of the product.

Intelligent control of dynamic LED lighting; Intelligent styring af dynamisk LED belysning. Slutrapport

Energy Technology Data Exchange (ETDEWEB)

Thorseth, A.; Corell, D.; Hansen, Soeren S.; Dam-Hansen, C.; Petersen, Paul Michael

2013-01-15

The project has resulted in a prototype of a new intelligent lighting control system. The control system enables the end user to control his or her own local lighting environment (lighting zone) according to individual preferences and needs. The report provides a description of how the developed intelligent lighting system is composed and functions. The system is designed as a work lamp that enables dynamic change of the light color scheme according to a number of light control algorithms. It is specifically designed in relation to user tests of the intelligent lighting system, which is carried out in the final part of the project. An intelligent and advanced control of LED lighting was developed, which enables optimization of the user's light conditions in a given situation. Based on a number of known parameters, the system can control lighting so that at any time optimal light conditions are created, using a minimum of electric power. (LN)

Distributed intelligence at CELLO

International Nuclear Information System (INIS)

Boer, W. de

1981-01-01

This paper describes the use of distributed intelligence at CELLO, a large 4π detector at PETRA. Besides special purpose hardware processors for online calibration and reformatting of data, several microcomputers are used for monitoring and testing the various detector components. (orig.)

Monitoring Thermal Conditions in Footwear

Science.gov (United States)

Silva-Moreno, Alejandra. A.; Lopez Vela, Martín; Alcalá Ochoa, Noe

2006-09-01

Thermal conditions inside the foot were evaluated on a volunteer subject. We have designed and constructed an electronic system which can monitors temperature and humidity of the foot inside the shoe. The data is stored in a battery-powered device for later uploading to a host computer for data analysis. The apparatus potentially can be used to provide feedback to patients who are prone to having skin breakdowns.

The Application Research of Modern Intelligent Cold Chain Distribution System Based on Internet of Things Technology

Science.gov (United States)

Fan, Dehui; Gao, Shan

This paper implemented an intelligent cold chain distribution system based on the technology of Internet of things, and took the protoplasmic beer logistics transport system as example. It realized the remote real-time monitoring material status, recorded the distribution information, dynamically adjusted the distribution tasks and other functions. At the same time, the system combined the Internet of things technology with weighted filtering algorithm, realized the real-time query of condition curve, emergency alarming, distribution data retrieval, intelligent distribution task arrangement, etc. According to the actual test, it can realize the optimization of inventory structure, and improve the efficiency of cold chain distribution.

Transformer ageing modern condition monitoring techniques and their interpretations

CERN Document Server

Purkait, Prithwiraj

2017-01-01

This book is a one-stop guide to state-of-the-art research in transformer ageing, condition monitoring and diagnosis. It is backed by rigorous research projects supported by the Australian Research Council in collaboration with several transmission and distribution companies. Many of the diagnostic techniques and tools developed in these projects have been applied by electricity utilities and would appeal to both researchers and practicing engineers. Important topics covered in this book include transformer insulation materials and their ageing behaviour, transformer condition monitoring techniques and detailed diagnostic techniques and their interpretation schemes. It also features a monitoring framework for smart transformers as well as a chapter on biodegradable oil.

Beam conditions monitors at CMS and LHC using diamond sensors

Energy Technology Data Exchange (ETDEWEB)

Hempel, Maria; Lohmann, Wolfgang [Desy-Zeuthen, Platanenallee 6, 15738 Zeuthen (Germany); Brandenburgische Technische Universitaet Cottbus, Konrad-Wachsmann-Allee 1, 03046 Cottbus (Germany); Castro-Carballo, Maria-Elena; Lange, Wolfgang; Novgorodova, Olga [Desy-Zeuthen, Platanenallee 6, 15738 Zeuthen (Germany); Walsh, Roberval [Desy-Hamburg, Notkestrasse 85, 22607 Hamburg (Germany)

2012-07-01

The Fast Beam Conditions Monitor (BCM1F) is a particle detector based on diamonds. Eight modules comprising a single crystal diamond, front-end electronics and an optical link are installed on both sides of the interaction point inside the tracker of the CMS detector. The back-end uses ADCs, TDCs and scalers to measure the amplitudes, arrival time and rates of beam-halo particles and collision products. These data are used to protect the inner tracker from adverse beam conditions, perform a fast monitoring of the luminosity and e.g. beam-gas interactions. Recently two additional BCM1F modules have been installed at other positions of the LHC to supplement the beam-loss monitors by a flux measurement with nanosecond time resolution. In the talk essential parameters of the system are presented and examples of beam conditions monitoring are reported.

Condition Monitoring of Machinery in Non-Stationary Operations : Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations"

CERN Document Server

Bartelmus, Walter; Chaari, Fakher; Zimroz, Radoslaw; Haddar, Mohamed

2012-01-01

Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers...

The use of condition monitoring information for maintenance planning and decision-making

Energy Technology Data Exchange (ETDEWEB)

Laakso, K.; Rosqvist, T. [VTT Industrial Systems (Finland); Paulsen, J.L. [Risoe National Lab., Roskilde (Denmark)

2002-12-01

A survey is presented outlining the use of condition monitoring information in three Nordic nuclear power plants. The questions of the survey relate to the role of condition monitoring in strategic, as well as operative, maintenance planning and decision-making. The survey indicates that condition monitoring is increasingly implemented at nuclear power plants, but very selectively and in a rather slow pace for predictive maintenance. A combined strategy of condition based maintenance and predetermined preventive maintenance is applied for important equipment such as main circulation pumps and steam turbines. A realistic aim is to reduce the number of costly or error prone maintenance and disassembling inspection activities by condition monitoring given that the approach enables a good diagnosis and prediction. Systematic follow-up and analysis of such condition monitoring information followed by a case-specific planning and decision making of timely and rightly directed maintenance actions can justify an extension of the intervals of a number of predetermined inspection, maintenance or periodic testing tasks. (au)

Current topics in active and intelligent food packaging for preservation of fresh foods.

Science.gov (United States)

Lee, Seung Yuan; Lee, Seung Jae; Choi, Dong Soo; Hur, Sun Jin

2015-11-01

The purpose of this review is to provide an overview of current packaging systems, e.g. active packaging and intelligent packaging, for various foods. Active packaging, such as modified atmosphere packaging (MAP), extends the shelf life of fresh produce, provides a high-quality product, reduces economic losses, including those caused by delay of ripening, and improves appearance. However, in active packaging, several variables must be considered, such as temperature control and different gas formulations with different product types and microorganisms. Active packaging refers to the incorporation of additive agents into packaging materials with the purpose of maintaining or extending food product quality and shelf life. Intelligent packaging is emerging as a potential advantage in food processing and is an especially useful tool for tracking product information and monitoring product conditions. Moreover, intelligent packaging facilitates data access and information exchange by altering conditions inside or outside the packaging and product. In spite of these advantages, few of these packaging systems are commercialized because of high cost, strict safety and hygiene regulations or limited consumer acceptance. Therefore more research is needed to develop cheaper, more easily applicable and effective packaging systems for various foods. © 2015 Society of Chemical Industry.

Significance of Operating Environment in Condition Monitoring of Large Civil Structures

Directory of Open Access Journals (Sweden)

Sreenivas Alampalli

1999-01-01

Full Text Available Success of remote long-term condition monitoring of large civil structures and developing calibrated analytical models for damage detection, depend significantly on establishing accurate baseline signatures and their sensitivity. Most studies reported in the literature concentrated on the effect of structural damage on modal parameters without emphasis on reliability of modal parameters. Thus, a field bridge structure was studied for the significance of operating conditions in relation to baseline signatures. Results indicate that in practice, civil structures should be monitored for at least one full cycle of in-service environmental changes before establishing baselines for condition monitoring or calibrating finite-element models. Boundary conditions deserve special attention.

GEOGLAM Crop Monitor Assessment Tool: Developing Monthly Crop Condition Assessments

Science.gov (United States)

McGaughey, K.; Becker Reshef, I.; Barker, B.; Humber, M. L.; Nordling, J.; Justice, C. O.; Deshayes, M.

2014-12-01

The Group on Earth Observations (GEO) developed the Global Agricultural Monitoring initiative (GEOGLAM) to improve existing agricultural information through a network of international partnerships, data sharing, and operational research. This presentation will discuss the Crop Monitor component of GEOGLAM, which provides the Agricultural Market Information System (AMIS) with an international, multi-source, and transparent consensus assessment of crop growing conditions, status, and agro-climatic conditions likely to impact global production. This activity covers the four primary crop types (wheat, maize, rice, and soybean) within the main agricultural producing regions of the AMIS countries. These assessments have been produced operationally since September 2013 and are published in the AMIS Market Monitor Bulletin. The Crop Monitor reports provide cartographic and textual summaries of crop conditions as of the 28th of each month, according to crop type. This presentation will focus on the building of international networks, data collection, and data dissemination.

Wireless pilot monitoring system for extreme race conditions.

Science.gov (United States)

Pino, Esteban J; Arias, Diego E; Aqueveque, Pablo; Melin, Pedro; Curtis, Dorothy W

2012-01-01

This paper presents the design and implementation of an assistive device to monitor car drivers under extreme conditions. In particular, this system is designed in preparation for the 2012 Atacama Solar Challenge to be held in the Chilean desert. Actual preliminary results show the feasibility of such a project including physiological and ambient sensors, real-time processing algorithms, wireless data transmission and a remote monitoring station. Implementation details and field results are shown along with a discussion of the main problems found in real-life telemetry monitoring.

Infant Long-Term Memory for a Conditioned Response and Intelligence Test Performance at 2 Years of Age.

Science.gov (United States)

Fagen, Jeffrey W.; And Others

To find predictive relations between measures taken in infancy and later scores on intelligence tests, a study was made that measured in the infant those cognitive processes examined later in life. Operant conditioning tasks were employed which required 3-, 7-, and 11-month-old infants to execute some response to produce an environmental…

Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features

Science.gov (United States)

Ahmed, H. O. A.; Wong, M. L. D.; Nandi, A. K.

2018-01-01

Condition classification of rolling element bearings in rotating machines is important to prevent the breakdown of industrial machinery. A considerable amount of literature has been published on bearing faults classification. These studies aim to determine automatically the current status of a roller element bearing. Of these studies, methods based on compressed sensing (CS) have received some attention recently due to their ability to allow one to sample below the Nyquist sampling rate. This technology has many possible uses in machine condition monitoring and has been investigated as a possible approach for fault detection and classification in the compressed domain, i.e., without reconstructing the original signal. However, previous CS based methods have been found to be too weak for highly compressed data. The present paper explores computationally, for the first time, the effects of sparse autoencoder based over-complete sparse representations on the classification performance of highly compressed measurements of bearing vibration signals. For this study, the CS method was used to produce highly compressed measurements of the original bearing dataset. Then, an effective deep neural network (DNN) with unsupervised feature learning algorithm based on sparse autoencoder is used for learning over-complete sparse representations of these compressed datasets. Finally, the fault classification is achieved using two stages, namely, pre-training classification based on stacked autoencoder and softmax regression layer form the deep net stage (the first stage), and re-training classification based on backpropagation (BP) algorithm forms the fine-tuning stage (the second stage). The experimental results show that the proposed method is able to achieve high levels of accuracy even with extremely compressed measurements compared with the existing techniques.

Intelligent control of liquid transfer for the automated synthesis of positron emitting radiopharmaceuticals

International Nuclear Information System (INIS)

Iwata, Ren; Ido, Tatsuo; Yamazaki, Shigeki

1990-01-01

A method for the intelligent control of liquid transfer, developed for automated synthesis of 2-deoxy-2-[ 18 F]fluoro-D-glucose from [ 18 F]fluoride, is described. A thermal mass flow controller coupled to a personal computer is used to monitor conditions for transferring or passing liquid through a tube or a column. Using this sensor a computer can detect completion of liquid transfer, dispense a stock solution and check the setup conditions of the system. The present feedback control can be readily adapted to other automated syntheses of positron emitting radiopharmaceuticals. (author)

Implementation strategies and tools for condition based monitoring at nuclear power plants

International Nuclear Information System (INIS)

2007-05-01

There is now an acute need to optimize maintenance to improve both reliability and competitiveness of nuclear power plant operation. There is an increasing tendency to move from the preventive (time based) maintenance concept to one dependent on plant and component conditions. In this context, various on-line and off-line condition monitoring and diagnostics, nondestructive inspection techniques and surveillance are used. Component selection for condition based maintenance, parameter selection for monitoring condition, evaluation of condition monitoring results are issues influencing the effectiveness of condition based maintenance. All these selections of components and parameters to be monitored, monitoring and diagnostics techniques to be used, acceptance criteria and trending for condition evaluation, and the economic aspect of predictive maintenance and condition monitoring should be incorporated into an integrated, effective condition based maintenance programme, which is part of the plant's overall maintenance optimization programme. This publication collects and analyses proven condition based maintenance strategies and techniques (engineering and organizational) in Member States. It includes selected papers on maintenance optimization presented during its preparation. This report was prepared under IAEA project on integrated NPP life cycle management including decommissioning. The main objective of an integrated life cycle management programme is to enable NPP's to compete, without compromising safety, successfully in the changing energy markets throughout their service life and to facilitate life extension and eventual decommissioning through improved engineering, technological, economic and managerial actions. The technical working group on NPP life management and other advisory groups nominated by the Member States provide recommendations on high priority needs of Member States in this area

Basic study on intelligent materialization of glass; Glass no intelligent ko zairyoka ni kansuru kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-10-31

This is the report No. 98 issued by the Inorganic Material Research Institute. An intelligent material is a substance and/or material which responds intelligently to environmental conditions and exhibits functions. One of the features of amorphous materials including amorphous glass is a large freedom in chemical composition. These materials maintain order in short distance, but have as a whole the turbulent and specific atom orientation. Therefore, high tolerability in selecting the composition, and diverse synthesizing methods are available. A wide range of utilization may be conceived, such as introduction of the state of electrons having different valences in a structure, and the diverse chemical combinations. Patterns of existence of polyhedrons having different orientations, and how they are connected correlate closely with an external environment. Intelligent materials have high freedom against change in the external environment and are suitable to exhibit intelligent functions. Setting heat and light as the external conditions, attempts have been made on search and creation of intelligent materials based on state change induced by interactions between the two factors. Fundamental studies have been made on synthesis of different environment responding glasses and films, and on factors and phenomena for exhibition of the intelligence. 62 refs., 91 figs., 8 tabs.

Artificial intelligence system for the monitoring of natural gas production systems; Intelligente Ueberwachung von Erdgasfoerderanlagen

Energy Technology Data Exchange (ETDEWEB)

Tschaetsch, H.U.

2001-02-01

The article explains a novel, artificial intelligence-based system called HISS (Human Interface Supervision System) which has been installed as a prototype for the monitoring of a natural gas production site at Thoense near Hannover/Germany. The system is capable to perform audio-visual and smelling functions, analogous to the human sensory perception. (orig./CB) [German] Die Aufrechterhaltung eines einwandfreien Betriebszustandes von technischen Anlagen durch staendige Kontrollen und regelmaessige Wartungsarbeiten ist haeufig eine aufwendige und kostspielige Angelegenheit. Gleichwohl ist sie - sowohl was die Frage der Sicherheit als auch des Umweltschutzes anbelangt - unentbehrlich. Die Erdgasfoerderanlage Thoense bei Hannover wird von einem intelligenten Ueberwachungssystem, HISS - Human Interface Supervision System, kontrolliert, das die menschlichen Eigenschaften sehen, hoeren und riechen beherrscht. (orig.)

Intelligent Chemical Sensor Systems for In-space Safety Applications

Science.gov (United States)

Hunter, G. W.; Xu, J. C.; Neudeck, P. G.; Makel, D. B.; Ward, B.; Liu, C. C.

2006-01-01

Future in-space and lunar operations will require significantly improved monitoring and Integrated System Health Management (ISHM) throughout the mission. In particular, the monitoring of chemical species is an important component of an overall monitoring system for space vehicles and operations. For example, in leak monitoring of propulsion systems during launch, inspace, and on lunar surfaces, detection of low concentrations of hydrogen and other fuels is important to avoid explosive conditions that could harm personnel and damage the vehicle. Dependable vehicle operation also depends on the timely and accurate measurement of these leaks. Thus, the development of a sensor array to determine the concentration of fuels such as hydrogen, hydrocarbons, or hydrazine as well as oxygen is necessary. Work has been on-going to develop an integrated smart leak detection system based on miniaturized sensors to detect hydrogen, hydrocarbons, or hydrazine, and oxygen. The approach is to implement Microelectromechanical Systems (MEMS) based sensors incorporated with signal conditioning electronics, power, data storage, and telemetry enabling intelligent systems. The final sensor system will be self-contained with a surface area comparable to a postage stamp. This paper discusses the development of this "Lick and Stick" leak detection system and it s application to In-Space Transportation and other Exploration applications.

Intelligent system for pilot and astronaut Psychophysiological status monitoring and recuperating.

Science.gov (United States)

Janicki, Andrzej; -Bogumila Pecyna, S. Maria

called intelligent computations, and their methodology is called “computational intelligence”. The absence of gravity which causes significant physiological stress with broad biomedical changes generated key problems for researchers and practitioners of aviations and space flight. Following previous experiences we had on the matter, some current results achieved on the bases of FlexComp Infinity/Biograph Infiniti, V6.1™ of Thought Technology ltd. [Janicki, Pecyna, 2014] are underlined. A particular emphasis has been placed on the ability of the distributed parallel computations connected with the sophisticated application of the NASA Autogenic Feedback Training AFTE [PS Cowings, 2011] method combined biofeedback and Autogenic Therapy exercises [WIML-NASA, 2011]. The present paper reports on the results of a serious preliminary experiments addressed especially to space disorientation and/or awareness of reality problem. Keywords: pilot’s decision making process; intelligent a agent; coherency; psychophysiological pilot status; remote monitoring; remote training; synthetic indicators; scientific information system; three-factor utility function; space disorientation;Near-Infrared Hemoencephalography; References: A.Janicki “three-factor utility function” in LabTSI™ Modeling and Simulation Platform, KUL Univ. publication 2011 - in polish, page 95-103 M.B. Pecyna and M. Pokorski "Near-Infrared Hemoencephalography for Monitoring Blood Oxygenation in Prefrontal Cortical Areas in diagnosis and Therapy of Developmental Dyslexia" in "Neurobiology of Respiration" Springer Science+Business Media Dordrecht 2013 page 175 - 180. NASA-WIML Workshop on 2011, Psychophysiological Aspects of Flight Safety In Aerospace Operations, WIML 2011

Monitoring and analysis of an absorption air-conditioning system

Energy Technology Data Exchange (ETDEWEB)

Perez de Vinaspre, M.; Bourouis, M.; Coronas, A. [Centro de Innovacion Tecnologica en Revalorizacion Energetica y Refrigeracion, Tarragona (Spain); Garcia, A.; Soto, V.; Pinazo, J.M. [E.T.S. Ingenieros Industriales, Valencia (Spain)

2004-09-01

In the last few years, high-energy consumption due to air-conditioning has led to a growing interest in the efficient use of energy in buildings. Although simulation programs have always been the main tools for analyzing energy in buildings, the reliability of their results is often compromised by a lack of certainty to reflect real conditions. The aim of this work is to monitorize and analyze the thermal behavior of an absorption-based air-conditioning installation of a university building in Tarragona, Spain. The existing monitoring system of the installation has been improved by implementing additional sensors and flow meters. The data has been stored during summer 2002 and used to assess the energy balance of the air-conditioning installation and the operational regime of the absorption chiller. [Author].

Artificial Consciousness or Artificial Intelligence

Directory of Open Access Journals (Sweden)

Spanache Florin

2017-05-01

Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

AN EVALUATION OF CONDITION MONITORING TECHNIQUES FOR LOW-VOLTAGE ELECTRIC CABLES

International Nuclear Information System (INIS)

LOFARO, R.J.; GROVE, E.; SOO, P.

2000-01-01

Aging of systems and components in nuclear power plants is a well known occurrence that must be managed to ensure the continued safe operation of these plants. Much of the degradation due to aging is controlled through periodic maintenance and/or component replacement. However, there are components that do not receive periodic maintenance or monitoring once they are installed; electric cables are such a component. To provide a means of monitoring the condition of electric cables, research is ongoing to evaluate promising condition monitoring (CM) techniques that can be used in situ to monitor cable condition and predict remaining life. While several techniques are promising, each has limitations that must be considered in its application. This paper discusses the theory behind several of the promising cable CM techniques being studied, along with their effectiveness for monitoring aging degradation in typical cable insulation materials, such as cross-linked polyethylene and ethylene propylene rubber. Successes and limitations of each technique are also presented

Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

Energy Technology Data Exchange (ETDEWEB)

Lukas, M; Anderson, D P [Spectro Incorporated, Littleton, Massachusetts (United States)

1998-12-31

Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

Energy Technology Data Exchange (ETDEWEB)

Lukas, M.; Anderson, D.P. [Spectro Incorporated, Littleton, Massachusetts (United States)

1997-12-31

Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

Condition monitoring of rotormachinery in nuclear power plants

International Nuclear Information System (INIS)

Suedmersen, U.; Runkel, J.; Vortriede, A.; Reimche, W.; Stegemann, D.

1996-01-01

Due to safety and economical reasons diagnostic and monitoring systems are of growing interest in nuclear power plants and other complex industrial productions. Key components of NPP's are rotating machineries of the primary and secondary loops like PWR main coolant pumps, BWR recirculation pumps, turbines, fresh water pumps and feed water pumps. Diagnostic systems are requested which detect, diagnose and localize faulty operation conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. The knowledge of characteristical machine signatures and their time dependent behaviour are the basis of efficient condition monitoring of rotating machines. The performance of reference measurements are of importance for fault detection during operation by trend settings. The comparison with thresholds given by norms and standards is only a small section of available possibilities. Therefore, for each machinery own thresholds should be determined using statistical time values, spectra comparison, cepstrum analysis and correlation analysis for source localization corresponding to certain machine operation conditions. (author). 14 refs, 15 figs

Condition monitoring of rotormachinery in nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Suedmersen, U; Runkel, J; Vortriede, A; Reimche, W; Stegemann, D [University of Hannover, Hannover (Germany). Inst. of Nuclear Engineering and Nondestructive Testing

1997-12-31

Due to safety and economical reasons diagnostic and monitoring systems are of growing interest in nuclear power plants and other complex industrial productions. Key components of NPP`s are rotating machineries of the primary and secondary loops like PWR main coolant pumps, BWR recirculation pumps, turbines, fresh water pumps and feed water pumps. Diagnostic systems are requested which detect, diagnose and localize faulty operation conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. The knowledge of characteristical machine signatures and their time dependent behaviour are the basis of efficient condition monitoring of rotating machines. The performance of reference measurements are of importance for fault detection during operation by trend settings. The comparison with thresholds given by norms and standards is only a small section of available possibilities. Therefore, for each machinery own thresholds should be determined using statistical time values, spectra comparison, cepstrum analysis and correlation analysis for source localization corresponding to certain machine operation conditions. (author). 14 refs, 15 figs.

USDA Foreign Agricultural Service overview for operational monitoring of current crop conditions and production forecasts.

Science.gov (United States)

Crutchfield, J.

2016-12-01

The presentation will discuss the current status of the International Production Assessment Division of the USDA ForeignAgricultural Service for operational monitoring and forecasting of current crop conditions, and anticipated productionchanges to produce monthly, multi-source consensus reports on global crop conditions including the use of Earthobservations (EO) from satellite and in situ sources.United States Department of Agriculture (USDA) Foreign Agricultural Service (FAS) International Production AssessmentDivision (IPAD) deals exclusively with global crop production forecasting and agricultural analysis in support of the USDAWorld Agricultural Outlook Board (WAOB) lockup process and contributions to the World Agricultural Supply DemandEstimates (WASE) report. Analysts are responsible for discrete regions or countries and conduct in-depth long-termresearch into national agricultural statistics, farming systems, climatic, environmental, and economic factors affectingcrop production. IPAD analysts become highly valued cross-commodity specialists over time, and are routinely soughtout for specialized analyses to support governmental studies. IPAD is responsible for grain, oilseed, and cotton analysison a global basis. IPAD is unique in the tools it uses to analyze crop conditions around the world, including customweather analysis software and databases, satellite imagery and value-added image interpretation products. It alsoincorporates all traditional agricultural intelligence resources into its forecasting program, to make the fullest use ofavailable information in its operational commodity forecasts and analysis. International travel and training play animportant role in learning about foreign agricultural production systems and in developing analyst knowledge andcapabilities.

The 1990 Goddard Conference on Space Applications of Artificial Intelligence

Science.gov (United States)

Rash, James L. (Editor)

1990-01-01

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Cultures, Conditions, and Cognitive Closure: Breaking Intelligence Studies’ Dependence on Security Studies

Directory of Open Access Journals (Sweden)

Matthew Crosston

2015-09-01

Full Text Available This paper is about how the conceptualization of ‘culture’ in intelligence studies has taken on too powerful a role, one that has become too restrictive in its impact on thinking about other intelligence communities, especially non-Western ones. This restriction brings about unintentional cognitive closure that damages intelligence analysis. The argument leans heavily in many ways on the fine work of Desch and Johnston in the discipline of Security Studies, who cogently brought to light over fifteen years ago how ultra-popular cultural theories were best utilized as supplements to traditional realist approaches, but were not in fact capable of supplanting or replacing realist explanations entirely. The discipline of Intelligence Studies today needs a similar ‘intellectual intervention’ as it has almost unknowingly advanced in the post-Cold War era on the coattails of Security Studies but has largely failed to apply the same corrective measures. This effort may be best accomplished by going back to Snyder in the 1970s who warned that culture should be used as the explanation of last resort for Security Studies.

Fusing Open Source Intelligence and Handheld Situational Awareness - Benghazi Case Study

Science.gov (United States)

2014-10-01

1 DM-0001694 Fusing Open Source Intelligence and Handheld Situational Awareness Benghazi Case Study Jeff Boleng, PhD Marc Novakouski Gene...command and control element at the CIA compound that would have been monitoring OSINT and other sources of intelligence before the attack and... Source Intelligence and Handheld Situational Awareness - Benghazi Case Study 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

Comparative Analysis of the Main Business Intelligence Solutions

OpenAIRE

Alexandra RUSANEANU

2013-01-01

Nowadays, Business Intelligence solutions are the main tools for analyzing and monitoring the company’s performance at any organizational level. This paper presents a comparative analysis of the most powerful Business Intelligence solutions using a set of technical features such as infrastructure of the platform, development facilities, complex analysis tools, interactive dashboards and scorecards, mobile integration and complex implementation of performance management methodologies.

Strong Genetic Overlap Between Executive Functions and Intelligence

OpenAIRE

Engelhardt, Laura E.; Mann, Frank D.; Briley, Daniel A.; Church, Jessica A.; Harden, K. Paige; Tucker-Drob, Elliot M.

2016-01-01

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision-making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic infl...

Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

Science.gov (United States)

Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

2018-08-01

An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

USING CONDITION MONITORING TO PREDICT REMAINING LIFE OF ELECTRIC CABLES

International Nuclear Information System (INIS)

LOFARO, R.; SOO, P.; VILLARAN, M.; GROVE, E.

2001-01-01

Electric cables are passive components used extensively throughout nuclear power stations to perform numerous safety and non-safety functions. It is known that the polymers commonly used to insulate the conductors on these cables can degrade with time; the rate of degradation being dependent on the severity of the conditions in which the cables operate. Cables do not receive routine maintenance and, since it can be very costly, they are not replaced on a regular basis. Therefore, to ensure their continued functional performance, it would be beneficial if condition monitoring techniques could be used to estimate the remaining useful life of these components. A great deal of research has been performed on various condition monitoring techniques for use on electric cables. In a research program sponsored by the U.S. Nuclear Regulatory Commission, several promising techniques were evaluated and found to provide trendable information on the condition of low-voltage electric cables. These techniques may be useful for predicting remaining life if well defined limiting values for the aging properties being measured can be determined. However, each technique has advantages and limitations that must be addressed in order to use it effectively, and the necessary limiting values are not always easy to obtain. This paper discusses how condition monitoring measurements can be used to predict the remaining useful life of electric cables. The attributes of an appropriate condition monitoring technique are presented, and the process to be used in estimating the remaining useful life of a cable is discussed along with the difficulties that must be addressed

Artificial intelligence applications in fixed area monitor for TRIGA reactor building and service building

International Nuclear Information System (INIS)

Talpalariu, C.; Talpalariu, J.; Vaja, N.; Matei, C.

2008-01-01

This system is intended for the protection of personnel working in those areas of the Reactor Building and Service Building where high gamma radiation fields are expected. A detector, sensitive to gamma radiation, is installed in each of the areas to be monitored. The detector will send a signal, proportional to the radiation level in the area, to a corresponding electronic module (Alarm Unit), where the signal will be amplified and checked against alarm set points for possible alarming conditions. In case the field exceeds the alarm set values, the Alarm Unit will produce a signal that will trigger the field alarms (Horn and Beacon) located in the area where the condition occurred. Each Alarm Unit will send a numerical input to central computer command. he system is required to accomplish the following tasks: - Monitors the level of gamma radiation in those areas of the Station where high radiation fields are expected; - Provides a continuous and centralized display of the radiation level in each of the monitored areas. The display shall be in exposure rate units (R/h); - Provides a visual and audible alarm in each monitored areas; Allows the control room operator to check at any time the radiation levels and alarm conditions in each of the monitored areas; - Control room operator shall be alerted of any alarm conditions that occurs in the Station. A typical monitoring loop is composed of the following components: Detector Assembly type: CI-MA - 522 two channels, two ranges; Horn and Beacon Assembly; Remote Indicating Meter with Warning Lights; Central computer; common equipment for all 40 loops. (authors)

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

Science.gov (United States)

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

Bridge condition assessment based on long-term strain monitoring

Science.gov (United States)

Sun, LiMin; Sun, Shouwang

2011-04-01

In consideration of the important role that bridges play as transportation infrastructures, their safety, durability and serviceability have always been deeply concerned. Structural Health Monitoring Systems (SHMS) have been installed to many long-span bridges to provide bridge engineers with the information needed in making rational decisions for maintenance. However, SHMS also confronted bridge engineers with the challenge of efficient use of monitoring data. Thus, methodologies which are robust to random disturbance and sensitive to damage become a subject on which many researches in structural condition assessment concentrate. In this study, an innovative probabilistic approach for condition assessment of bridge structures was proposed on the basis of long-term strain monitoring on steel girder of a cable-stayed bridge. First, the methodology of damage detection in the vicinity of monitoring point using strain-based indices was investigated. Then, the composition of strain response of bridge under operational loads was analyzed. Thirdly, the influence of temperature and wind on strains was eliminated and thus strain fluctuation under vehicle loads is obtained. Finally, damage evolution assessment was carried out based on the statistical characteristics of rain-flow cycles derived from the strain fluctuation under vehicle loads. The research conducted indicates that the methodology proposed is qualified for structural condition assessment so far as the following respects are concerned: (a) capability of revealing structural deterioration; (b) immunity to the influence of environmental variation; (c) adaptability to the random characteristic exhibited by long-term monitoring data. Further examination of the applicability of the proposed methodology in aging bridge may provide a more convincing validation.

Integrated online condition monitoring system for nuclear power plants

International Nuclear Information System (INIS)

Hashemian, Hashem M.

2010-01-01

Online condition monitoring or online monitoring (OLM) uses data acquired while a nuclear power is operating to continuously assess the health of the plant's sensors, processes, and equipment; to measure the dynamic performance of the plant's process instrumentation; to verify in-situ the calibration of the process instrumentation; to detect blockages, voids, and leaks in the pressure sensing lines; to identify core flow anomalies; to extend the life of neutron detectors and other sensors; and to measure the vibration of reactor internals. Both the steady-state or DC output of plant sensors and their AC signal or noise output can be used to assess sensor health, depending on whether the application is monitoring a rapidly changing (e.g., core barrel motion) or a slowly changing (e.g., sensor calibration) process. The author has designed, developed, installed, and tested OLM systems (comprised of software/hardware-based data acquisition and data processing modules) that integrate low-frequency (1 mHz to 1 Hz) techniques such as RTD cross-calibration, pressure transmitter calibration monitoring, and equipment condition monitoring and high-frequency (1 Hz to 1 kHz) techniques such as the noise analysis technique. The author has demonstrated the noise analysis technique's effectiveness for measuring the dynamic response-time of pressure transmitters and their sensing lines; for performing predictive maintenance on reactor internals; for detecting core flow anomalies; and for extending neutron detector life. Integrated online condition monitoring systems can combine AC and DC data acquisition and signal processing techniques, can use data from existing process sensors during all modes of plant operation, including startup, normal operation, and shutdown; can be retrofitted into existing PWRs, BWRs, and other reactor types and will be integrated into next-generation plants. (orig.)

Integrated online condition monitoring system for nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Hashemian, Hashem M. [Analysis and Measurement Services Corporation, Knoxville, TN (United States). AMS Technology Center

2010-09-15

Online condition monitoring or online monitoring (OLM) uses data acquired while a nuclear power is operating to continuously assess the health of the plant's sensors, processes, and equipment; to measure the dynamic performance of the plant's process instrumentation; to verify in-situ the calibration of the process instrumentation; to detect blockages, voids, and leaks in the pressure sensing lines; to identify core flow anomalies; to extend the life of neutron detectors and other sensors; and to measure the vibration of reactor internals. Both the steady-state or DC output of plant sensors and their AC signal or noise output can be used to assess sensor health, depending on whether the application is monitoring a rapidly changing (e.g., core barrel motion) or a slowly changing (e.g., sensor calibration) process. The author has designed, developed, installed, and tested OLM systems (comprised of software/hardware-based data acquisition and data processing modules) that integrate low-frequency (1 mHz to 1 Hz) techniques such as RTD cross-calibration, pressure transmitter calibration monitoring, and equipment condition monitoring and high-frequency (1 Hz to 1 kHz) techniques such as the noise analysis technique. The author has demonstrated the noise analysis technique's effectiveness for measuring the dynamic response-time of pressure transmitters and their sensing lines; for performing predictive maintenance on reactor internals; for detecting core flow anomalies; and for extending neutron detector life. Integrated online condition monitoring systems can combine AC and DC data acquisition and signal processing techniques, can use data from existing process sensors during all modes of plant operation, including startup, normal operation, and shutdown; can be retrofitted into existing PWRs, BWRs, and other reactor types and will be integrated into next-generation plants. (orig.)

Nonlinear Cointegration Approach for Condition Monitoring of Wind Turbines

Directory of Open Access Journals (Sweden)

Konrad Zolna

2015-01-01

Full Text Available Monitoring of trends and removal of undesired trends from operational/process parameters in wind turbines is important for their condition monitoring. This paper presents the homoscedastic nonlinear cointegration for the solution to this problem. The cointegration approach used leads to stable variances in cointegration residuals. The adapted Breusch-Pagan test procedure is developed to test for the presence of heteroscedasticity in cointegration residuals obtained from the nonlinear cointegration analysis. Examples using three different time series data sets—that is, one with a nonlinear quadratic deterministic trend, another with a nonlinear exponential deterministic trend, and experimental data from a wind turbine drivetrain—are used to illustrate the method and demonstrate possible practical applications. The results show that the proposed approach can be used for effective removal of nonlinear trends form various types of data, allowing for possible condition monitoring applications.

Intelligence in Artificial Intelligence

OpenAIRE

Datta, Shoumen Palit Austin

2016-01-01

The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

Condition Monitoring Of Operating Pipelines With Operational Modal Analysis Application

Directory of Open Access Journals (Sweden)

Mironov Aleksey

2015-12-01

Full Text Available In the petroleum, natural gas and petrochemical industries, great attention is being paid to safety, reliability and maintainability of equipment. There are a number of technologies to monitor, control, and maintain gas, oil, water, and sewer pipelines. The paper focuses on operational modal analysis (OMA application for condition monitoring of operating pipelines. Special focus is on the topicality of OMA for definition of the dynamic features of the pipeline (frequencies and mode shapes in operation. The research was conducted using two operating laboratory models imitated a part of the operating pipeline. The results of finite-element modeling, identification of pipe natural modes and its modification under the influence of virtual failure are discussed. The work considers the results of experimental research of dynamic behavior of the operating pipe models using one of OMA techniques and comparing dynamic properties with the modeled data. The study results demonstrate sensitivity of modal shape parameters to modification of operating pipeline technical state. Two strategies of pipeline repair – with continuously condition-based monitoring with proposed technology and without such monitoring, was discussed. Markov chain reliability models for each strategy were analyzed and reliability improvement factor for proposed technology of monitoring in compare with traditional one was evaluated. It is resumed about ability of operating pipeline condition monitoring by measuring dynamic deformations of the operating pipe and OMA techniques application for dynamic properties extraction.

Dynamic vulnerability assessment and intelligent control for sustainable power systems

CERN Document Server

Gonzalez-Longatt, Francisco

2018-01-01

Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

Operations Monitoring Assistant System Design

Science.gov (United States)

1986-07-01

Logic. Artificial Inteligence 25(1)::75-94. January.18. 41 -Nils J. Nilsson. Problem-Solving Methods In Artificli Intelligence. .klcG raw-Hill B3ook...operations monitoring assistant (OMA) system is designed that combines operations research, artificial intelligence, and human reasoning techniques and...KnowledgeCraft (from Carnegie Group), and 5.1 (from Teknowledze). These tools incorporate the best methods of applied artificial intelligence, and

Advanced condition monitoring program for turbine system

International Nuclear Information System (INIS)

Ono, Shigetoshi

2015-01-01

It is important for utilities to achieve a stable operation in nuclear power plants. To achieve it, plant anomalies that affect a stable operation must be found out and eliminated. Therefore, the advanced condition monitoring program was developed. In this program, a sophisticated heat balance model based on the actual plant data is adopted to identify plant anomalies at an incipient stage and the symptoms of plant anomalies are found by heat balance changes from the model calculation. The model calculation results have shown precise prediction for actual plant parameters. Moreover, this program has the diagnostic engine that helps operators derive the cause of plant anomalies. By using this monitoring program, the component reliability in the turbine system can be periodically monitored and assessed, and as a result the stable operation of nuclear power plants can be achieved. (author)

Tolkku - a toolbox for decision support from condition monitoring data

International Nuclear Information System (INIS)

Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, Kimmo

2012-01-01

This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.

BSN Program Admittance Criteria: Should Emotional Intelligence Be Included?

Science.gov (United States)

Smith, Tanya

2017-01-01

Emotional intelligence refers to the ability to identify and monitor emotions and remain aware of how emotions affect thoughts and actions. Emotional intelligence has been discussed as a better predictor of personal and occupational success than performance on intellectual intelligence tests. Despite the importance of one's emotional intelligence, BSN (Bachelor of Science in Nursing) nursing schools routinely admit candidates based on the student's cumulative college course grade point average (GPA). Nursing is a profession that requires one's ability to empathize, care, and react in emotionally sound manners. Is the GPA enough to determine if a student will evolve into a professional nurse? This article will explore the routine admittance criteria for BSN nursing programs and propose the concept of using the emotional intelligence tool as an adjunct to the cumulative college course GPA. The emotional intelligence theory will be identified and applied to the nursing profession. © 2016 Wiley Periodicals, Inc.

[Microinjection Monitoring System Design Applied to MRI Scanning].

Science.gov (United States)

Xu, Yongfeng

2017-09-30

A microinjection monitoring system applied to the MRI scanning was introduced. The micro camera probe was used to stretch into the main magnet for real-time video injection monitoring of injection tube terminal. The programming based on LabVIEW was created to analysis and process the real-time video information. The feedback signal was used for intelligent controlling of the modified injection pump. The real-time monitoring system can make the best use of injection under the condition that the injection device was away from the sample which inside the magnetic room and unvisible. 9.4 T MRI scanning experiment showed that the system in ultra-high field can work stability and doesn't affect the MRI scans.

Development of intelligent supervisory control system

International Nuclear Information System (INIS)

Takizawa, Y.; Fukumoto, A.; Makino, M.; Takiguchi, S.

1994-01-01

The objective of the development of an intelligent supervisory control system for next generation plants is enhancement of the operational reliability by applying the recent outcome of artificial intelligence and computer technologies. This system consists of the supervisory control and monitoring for automatic operation, the equipment operation support for historical data management and for test scheduling, the operators' decision making support for accidental plant situations and the human-friendly interface of these support functions. The verification test results showed the validity of the functions realized by this system for the next generation control room. (author)

Binary Masking & Speech Intelligibility

DEFF Research Database (Denmark)

Boldt, Jesper

The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either experime......The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either...... experiments under ideal conditions or as experiments under more realistic conditions useful for real-life applications such as hearing aids. In the experiments under ideal conditions, the previously defined ideal binary mask is evaluated using hearing impaired listeners, and a novel binary mask -- the target...... binary mask -- is introduced. The target binary mask shows the same substantial increase in intelligibility as the ideal binary mask and is proposed as a new reference for binary masking. In the category of real-life applications, two new methods are proposed: a method for estimation of the ideal binary...

Unmanned Aerial Vehicles (UAVs and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

Directory of Open Access Journals (Sweden)

Luis F. Gonzalez

2016-01-01

Full Text Available Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV, artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

Science.gov (United States)

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Wire system aging assessment and condition monitoring (WASCO)

International Nuclear Information System (INIS)

Fantoni, P.F.

2007-04-01

Nuclear facilities rely on electrical wire systems to perform a variety of functions for successful operation. Many of these functions directly support the safe operation of the facility; therefore, the continued reliability of wire systems, even as they age, is critical. Condition Monitoring (CM) of installed wire systems is an important part of any aging program, both during the first 40 years of the qualified life and even more in anticipation of the license renewal for a nuclear power plant. This report contains some test results of a method for wire system condition monitoring, developed at the Halden Reactor Project, called LIRA (LIne Resonance Analysis), which can be used on-line to detect any local or global changes in the cable electrical parameters as a consequence of insulation faults or degradation. (au)

Monitoring of operation with artificial intelligence methods; Betriebsueberwachung mit Verfahren der Kuenstlichen Intelligenz

Energy Technology Data Exchange (ETDEWEB)

Bruenninghaus, H. [DMT-Gesellschaft fuer Forschung und Pruefung mbH, Essen (Germany). Geschaeftsbereich Systemtechnik

1999-03-11

Taking the applications `early detection of fires` and `reduction of burst of messages` as an example, the usability of artificial intelligence (AI) methods in the monitoring of operation was checked in a R and D project. The contribution describes the concept, development and evaluation of solutions to the specified problems. A platform, which made it possible to investigate different AI methods (in particular artificial neuronal networks), had to be creaated as a basis for the project. At the same time ventilation data had to be acquired and processed by the networks for the classification. (orig.) [Deutsch] Am Beispiel der Anwendungsfaelle `Brandfrueherkennung` und `Meldungsschauerreduzierung` wurde im Rahmen eines F+E-Vorhabens die Einsetzbarkeit von Kuenstliche-Intelligenz-Methoden (KI) in der Betriebsueberwachung geprueft. Der Beitrag stellt Konzeption, Entwicklung und Bewertung von Loesungsansaetzen fuer die genannten Aufgabenstellungen vor. Als Grundlage fuer das Vorhaben wurden anhand KI-Methoden (speziell: Kuenstliche Neuronale Netze -KNN) auf der Grundlage gewonnener und aufbereiteter Wetterdaten die Beziehungen zwischen den Wettermessstellen im Laufe des Wetterwegs klassifiziert. (orig.)

Research on human physiological parameters intelligent clothing based on distributed Fiber Bragg Grating

Science.gov (United States)

Miao, Changyun; Shi, Boya; Li, Hongqiang

2008-12-01

A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.

Prediction and Optimization of Speech Intelligibility in Adverse Conditions

NARCIS (Netherlands)

Taal, C.H.

2013-01-01

In digital speech-communication systems like mobile phones, public address systems and hearing aids, conveying the message is one of the most important goals. This can be challenging since the intelligibility of the speech may be harmed at various stages before, during and after the transmission

Online Sources of Competitive Intelligence.

Science.gov (United States)

Wagers, Robert

1986-01-01

Presents an approach to using online sources of information for competitor intelligence (i.e., monitoring industry and tracking activities of competitors); identifies principal sources; and suggests some ways of making use of online databases. Types and sources of information and sources and database charts are appended. Eight references are…

Effects of Personal Intelligence Reading Instruction on personal intelligence profiles of Thai university students

Directory of Open Access Journals (Sweden)

Salila Vongkrahchang

2016-01-01

Full Text Available The study investigated the impact of reading instruction using personal intelligence (PI on Thai university students' PI profiles. Thirty-nine undergraduates majoring in English involved in the study for ten weeks. Their PI profiles were measured twice at the pre-and post-interventions. The mixed methods research design was employed. The results showed that the students developed more personal intelligence in the post-intervention profiles (x¯ = 2.72, SD = 0.80 than in their pre-intervention ones (x¯ = 2.54, SD = 0.82. The students showed a preference for intrapersonal intelligence, in goal setting (x¯ = 2.85, SD = 0.78, monitoring (x¯ = 2.85, SD = 0.74, and evaluation strategy (x¯ = 3.21, SD = 0.77. Their interaction assessed by classroom observation and student worksheets also highlighted the PI profile findings. Personal Intelligence Reading Instruction facilitated the students setting specific and achievable goals, making overt and doable plans for their reading tasks, adjusting strategies helping them understand the text better, and identifying sources of difficulties while reading.

On the use of temperature for online condition monitoring of geared systems - A review

Science.gov (United States)

Touret, T.; Changenet, C.; Ville, F.; Lalmi, M.; Becquerelle, S.

2018-02-01

Gear unit condition monitoring is a key factor for mechanical system reliability management. When they are subjected to failure, gears and bearings may generate excessive vibration, debris and heat. Vibratory, acoustic or debris analyses are proven approaches to perform condition monitoring. An alternative to those methods is to use temperature as a condition indicator to detect gearbox failure. The review focuses on condition monitoring studies which use this thermal approach. According to the failure type and the measurement method, it exists a distinction whether it is contact (e.g. thermocouple) or non-contact temperature sensor (e.g. thermography). Capabilities and limitations of this approach are discussed. It is shown that the use of temperature for condition monitoring has a clear potential as an alternative to vibratory or acoustic health monitoring.

Online condition monitoring to enable extended operation of nuclear power plants

International Nuclear Information System (INIS)

Meyer, Ryan Michael; Bond, Leonard John; Ramuhalli, Pradeep

2012-01-01

Safe, secure, and economic operation of nuclear power plants will remain of strategic significance. New and improved monitoring will likely have increased significance in the post-Fukushima world. Prior to Fukushima, many activities were already underway globally to facilitate operation of nuclear power plants beyond their initial licensing periods. Decisions to shut down a nuclear power plant are mostly driven by economic considerations. Online condition monitoring is a means to improve both the safety and economics of extending the operating lifetimes of nuclear power plants, enabling adoption of proactive aging management. With regard to active components (e.g., pumps, valves, motors, etc.), significant experience in other industries has been leveraged to build the science base to support adoption of online condition-based maintenance and proactive aging management in the nuclear industry. Many of the research needs are associated with enabling proactive management of aging in passive components (e.g., pipes, vessels, cables, containment structures, etc.). This paper provides an overview of online condition monitoring for the nuclear power industry with an emphasis on passive components. Following the overview, several technology/knowledge gaps are identified, which require addressing to facilitate widespread online condition monitoring of passive components. (author)

Automated Machinery Health Monitoring Using Stress Wave Analysis & Artificial Intelligence

National Research Council Canada - National Science Library

Board, David

1998-01-01

.... Army, for application to helicopter drive train components. The system will detect structure borne, high frequency acoustic data, and process it with feature extraction and polynomial network artificial intelligence software...

Recent trends in the condition monitoring of transformers theory, implementation and analysis

CERN Document Server

Chakravorti, Sivaji; Chatterjee, Biswendu

2013-01-01

Recent Trends in the Condition Monitoring of Transformers reflects the current interest in replacing traditional techniques used in power transformer condition monitoring with non-invasive measures such as polarization/depolarization current measurement, recovery voltage measurement, frequency domain spectroscopy and frequency response analysis. The book stresses the importance of scrutinizing the condition of transformer insulation which may fail under present day conditions of intensive use with the resulting degradation of dielectric properties causing functional failure of the transformer.

The influence of gender on personality variables conditioning learning: Emotional intelligence and academic procrastination

Directory of Open Access Journals (Sweden)

Mercè Clariana,

2011-10-01

Full Text Available This research analyses the relationship between academic procrastination and emotional intelligence taking also into account the gender and age influence. Psychology undergraduates from the UAB (Universitat Autónoma de Barcelona, Spain and the UIB (Universitat de les Illes Balears, Spain, 45 males and 147 females constituted the sample of the study. Academic procrastination was assessed by means of the D scale (CLARIANA & MARTÍN, 2008 and emotional intelligence by means of the EQ–i (BAR–ON, 1997. The results show that academic procrastination has a significant negative relationship with intrapersonal intelligence, emotional quotient and mood. Moreover, female students scored significantly higher than males both in intrapersonal and interpersonal Intelligence while males obtained higher scores in both stress management and adaptability.

Operator support system using computational intelligence techniques

International Nuclear Information System (INIS)

Bueno, Elaine Inacio; Pereira, Iraci Martinez

2015-01-01

Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

Operator support system using computational intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Bueno, Elaine Inacio, E-mail: ebueno@ifsp.edu.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2015-07-01

Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

Directory of Open Access Journals (Sweden)

Bo Sun

2012-01-01

Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

Self Configurable Intelligent Distributed Antenna System

DEFF Research Database (Denmark)

Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee

2016-01-01

with their respective base stations, spectrum pooling and management at antenna end is not efficient. The situation worsens in Heterogeneous and Dense-net conditions in an Area of Interest (AoI). In this paper, we propose a DAS based intelligent architecture referred to as Self Configurable Intelligent Distributed...

Luminosity measurement and beam condition monitoring at CMS

Energy Technology Data Exchange (ETDEWEB)

Leonard, Jessica Lynn [DESY, Zeuthen (Germany)

2015-07-01

The BRIL system of CMS consists of instrumentation to measure the luminosity online and offline, and to monitor the LHC beam conditions inside CMS. An accurate luminosity measurement is essential to the CMS physics program, and measurement of the beam background is necessary to ensure safe operation of CMS. In expectation of higher luminosity and denser proton bunch spacing during LHC Run II, many of the BRIL subsystems are being upgraded and others are being added to complement the existing measurements. The beam condition monitor (BCM) consists of several sets of diamond sensors used to measure online luminosity and beam background with a single-bunch-crossing resolution. The BCM also detects when beam conditions become unfavorable for CMS running and may trigger a beam abort to protect the detector. The beam halo monitor (BHM) uses quartz bars to measure the background of the incoming beams at larger radii. The pixel luminosity telescope (PLT) consists of telescopes of silicon sensors designed to provide a CMS online and offline luminosity measurement. In addition, the forward hadronic calorimeter (HF) will deliver an independent luminosity measurement, making the whole system robust and allowing for cross-checks of the systematics. Data from each of the subsystems will be collected and combined in the BRIL DAQ framework, which will publish it to CMS and LHC. The current status of installation and commissioning results for the BRIL subsystems are given.

Priority target conditions for algorithms for monitoring children's growth: Interdisciplinary consensus.

Directory of Open Access Journals (Sweden)

Pauline Scherdel

Full Text Available Growth monitoring of apparently healthy children aims at early detection of serious conditions through the use of both clinical expertise and algorithms that define abnormal growth. Optimization of growth monitoring requires standardization of the definition of abnormal growth, and the selection of the priority target conditions is a prerequisite of such standardization.To obtain a consensus about the priority target conditions for algorithms monitoring children's growth.We applied a formal consensus method with a modified version of the RAND/UCLA method, based on three phases (preparatory, literature review, and rating, with the participation of expert advisory groups from the relevant professional medical societies (ranging from primary care providers to hospital subspecialists as well as parent associations. We asked experts in the pilot (n = 11, reading (n = 8 and rating (n = 60 groups to complete the list of diagnostic classification of the European Society for Paediatric Endocrinology and then to select the conditions meeting the four predefined criteria of an ideal type of priority target condition.Strong agreement was obtained for the 8 conditions selected by the experts among the 133 possible: celiac disease, Crohn disease, craniopharyngioma, juvenile nephronophthisis, Turner syndrome, growth hormone deficiency with pituitary stalk interruption syndrome, infantile cystinosis, and hypothalamic-optochiasmatic astrocytoma (in decreasing order of agreement.This national consensus can be used to evaluate the algorithms currently suggested for growth monitoring. The method used for this national consensus could be re-used to obtain an international consensus.

Artificial Intelligence and Moral intelligence

OpenAIRE

Laura Pana

2008-01-01

We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

Swarm Intelligence systems

International Nuclear Information System (INIS)

Beni, G.

1994-01-01

We review the characteristics of Swarm Intelligence and discuss systems exhibiting it. The recently developed mathematical description of Swarm behavior is also reviewed and discussed. The self-organization of Swarms is described as the reconfiguring asynchronously and conservatively of a distribution. Swarm reconfigurations are based on producing distributions that are solutions to systems of linear equations. Conservation and asynchronicity are related, respectively, to the global and local nature of the Swarm problem. The conditions for the convergence of the Swarm algorithm are presented. The important point is that, under very general conditions, the Swarm reconfigures in a time which is independent of the size of the Swarm. This fact implies that a centralized controller can never reconfigure as fast as a Swarm provided the size of the Swarm is large enough. This result is related to the unpredictability of the Swarm, a basic property of Swarm Intelligence. Finally, the conditions under which Swarm algorithms become of practical importance are discussed and examples given. (author)

In-process monitoring and control of microassembly by utilising force sensor

OpenAIRE

S. Tangjitsitcharoen; P. Tangpornprasert; Ch. Virulsri; N. Rojanarowan

2008-01-01

Purpose: The aim of this research is to develop an in-process monitoring system to control the position of the shaftwithin a tolerance of ±2.5 μm regardless of any conditions of the geometries of the shaft and the thrust plate.Design/methodology/approach: To realize an automated and intelligent microassembly process, a method hasbeen developed to monitor and control the position of the shaft in the plate of the high-precision spindle motorfor hard disk drive in order to reduce the shaft high ...

Distributed intelligent urban environment monitoring system

Science.gov (United States)

Du, Jinsong; Wang, Wei; Gao, Jie; Cong, Rigang

2018-02-01

The current environmental pollution and destruction have developed into a world-wide major social problem that threatens human survival and development. Environmental monitoring is the prerequisite and basis of environmental governance, but overall, the current environmental monitoring system is facing a series of problems. Based on the electrochemical sensor, this paper designs a small, low-cost, easy to layout urban environmental quality monitoring terminal, and multi-terminal constitutes a distributed network. The system has been small-scale demonstration applications and has confirmed that the system is suitable for large-scale promotion

Application of artificial intelligence in process control

CERN Document Server

Krijgsman, A

1993-01-01

This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

Intelligent on-line fault tolerant control for unanticipated catastrophic failures.

Science.gov (United States)

Yen, Gary G; Ho, Liang-Wei

2004-10-01

As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.

Improvements in valve reliability due to implementation of effective condition monitoring programs

International Nuclear Information System (INIS)

Hale, Stan

2003-01-01

Modern diagnostic systems for motor-operated valves, pneumatic control valves and checkvalves have facilitated a shift in the maintenance philosophy for valves and actuators in nuclear power plants from schedule based to condition-based maintenance (CBM). This shift enables plant management to focus resources and schedule priority on the plant equipment that warrants attention thereby not wasting resources or increasing the human factors risk on equipment that has not degraded. The most recent initiatives combine condition monitoring with risk/safety insights to focus attention and resonances on the right equipment at the right time consistent with each component's safety-significance. The activities of the ASME working groups responsible for nuclear O and M codes have kept pace with the technology and process improvements necessary to maximize the technical and economic benefits of condition based and risk informed maintenance. This paper discusses adoption of valve condition monitoring in the nuclear power industry, changes to ASME codes and standards during the 90's to facilitate adoption of condition monitoring technology for in-service testing and recent efforts to combine risk insights with condition monitoring strategies to achieve the highest level of valve reliability and nuclear safety without over inflating maintenance cost. (author)

Economic analysis of condition monitoring systems for offshore wind turbine sub-systems

DEFF Research Database (Denmark)

May, Allan; MacMillan, David; Thöns, Sebastian

2015-01-01

The use of condition monitoring systems on offshore wind turbines has increased dramatically in recent times. However, their use is mostly restricted to vibration based monitoring systems for the gearbox, generator and drive train. A survey of commercially available condition monitoring systems...... year life cycle. The model uses Hidden Markov Models to represent both the actual system state and the observed condition monitoring state. The CM systems are modelled to include reduced failure types, false alarms, detection rates and 6 month failure warnings. The costs for system failures are derived...... and their associated costs has been completed for the blades, drive train, tower and foundation. This paper considers what value can be obtained from integrating these additional systems into the maintenance plan. This is achieved by running simulations on an operations and maintenance model for a wind farm over a 20...

Intelligent mobile sensor system for drum inspection and monitoring: Phase 1

International Nuclear Information System (INIS)

1993-06-01

The objective of this project was to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort is a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The device is capable of operating in narrow aisles and interpolating the free aisle space between rows of stacked drums. The system has an integrated sensor suite for leak detection, and is interfaced with a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which positions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 90% of all drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort is separated into three phases of which phase one is now complete. The first phase has demonstrated an integrated system for monitoring and inspection activities for waste storage facility operations. This demonstration system was quickly fielded and evaluated by leveraging technologies developed from previous NASA and DARPA contracts and internal research. The second phase will demonstrate a prototype system appropriate for operational use in an actual storage facility. The prototype provides an integrated design that considers operational requirements, hardware costs, maintenance, safety, and robustness. The final phase will demonstrate commercial viability using the prototype vehicle in a pilot waste operations and inspection project

E-learning environment as intelligent tutoring system

Science.gov (United States)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Intelligent Smoke Alarm System with Wireless Sensor Network Using ZigBee

Directory of Open Access Journals (Sweden)

Qin Wu

2018-01-01

Full Text Available The conflagration of fire is still a serious problem caused by humans, and houses are at a high risk of fire. Recently, people have used smoke alarms which only have one sensor to detect fire. Smoke is emitted in several forms in daily life. A single sensor is not a reliable way to detect fire. With the rapid advancement in Internet technology, people can monitor their houses remotely to determine the current condition of the house. This paper introduces an intelligent smoke alarm system that uses ZigBee transmission technology to build a wireless network, uses random forest to identify smoke, and uses E-charts for data visualization. By combining the real-time dynamic changes of various environmental factors, compared to the traditional smoke alarm, the accuracy and controllability of the fire warning are increased, and the visualization of the data enables users to monitor the room environment more intuitively. The proposed system consists of a smoke detection module, a wireless communication module, and intelligent identification and data visualization module. At present, the collected environmental data can be classified into four statuses, that is, normal air, water mist, kitchen cooking, and fire smoke. Reducing the frequency of miscalculations also means improving the safety of the person and property of the user.

The ATLAS Beam Conditions Monitor

International Nuclear Information System (INIS)

Cindro, V; Dolenc, I; Kramberger, G; Macek, B; Mandic, I; Mikuz', M; Zavrtanik, M; Dobos, D; Gorisek, A; Pernegger, H; Weilhammer, P; Frais-Koelbl, H; Griesmayer, E; Niegl, M; Kagan, H; Tardif, D; Trischuk, W

2008-01-01

Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to build their own beam monitoring devices. The ATLAS Beam Conditions Monitor (BCM) consists of two stations (forward and backward) of detectors each with four modules. The sensors are required to tolerate doses up to 500 kGy and in excess of 10 15 charged particles per cm 2 over the lifetime of the experiment. Each module includes two diamond sensors read out in parallel. The stations are located symmetrically around the interaction point, positioning the diamond sensors at z = ±184 cm and r = 55 mm (a pseudo- rapidity of about 4.2). Equipped with fast electronics (2 ns rise time) these stations measure time-of-flight and pulse height to distinguish events resulting from lost beam particles from those normally occurring in proton-proton interactions. The BCM also provides a measurement of bunch-by-bunch luminosities in ATLAS by counting in-time and out-of-time collisions. Eleven detector modules have been fully assembled and tested. Tests performed range from characterisation of diamond sensors to full module tests with electron sources and in proton testbeams. Testbeam results from the CERN SPS show a module median-signal to noise of 11:1 for minimum ionising particles incident at a 45-degree angle. The best eight modules were installed on the ATLAS pixel support frame that was inserted into ATLAS in the summer of 2007. This paper describes the full BCM detector system along with simulation studies being used to develop the logic in the back-end FPGA coincidence hardware

The ATLAS Beam Conditions Monitor

Energy Technology Data Exchange (ETDEWEB)

Cindro, V; Dolenc, I; Kramberger, G; Macek, B; Mandic, I; Mikuz' , M; Zavrtanik, M [Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana (Slovenia); Dobos, D; Gorisek, A; Pernegger, H; Weilhammer, P [CERN, Geneva (Switzerland); Frais-Koelbl, H; Griesmayer, E; Niegl, M [University of Applied Sciences Wiener Neustadt and Fotec, Wiener Neustadt (Austria); Kagan, H [Ohio State University, Columbus (United States); Tardif, D; Trischuk, W [University of Toronto, Toronto (Canada)], E-mail: william@physics.utoronto.ca

2008-02-15

Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to build their own beam monitoring devices. The ATLAS Beam Conditions Monitor (BCM) consists of two stations (forward and backward) of detectors each with four modules. The sensors are required to tolerate doses up to 500 kGy and in excess of 10{sup 15} charged particles per cm{sup 2} over the lifetime of the experiment. Each module includes two diamond sensors read out in parallel. The stations are located symmetrically around the interaction point, positioning the diamond sensors at z = {+-}184 cm and r = 55 mm (a pseudo- rapidity of about 4.2). Equipped with fast electronics (2 ns rise time) these stations measure time-of-flight and pulse height to distinguish events resulting from lost beam particles from those normally occurring in proton-proton interactions. The BCM also provides a measurement of bunch-by-bunch luminosities in ATLAS by counting in-time and out-of-time collisions. Eleven detector modules have been fully assembled and tested. Tests performed range from characterisation of diamond sensors to full module tests with electron sources and in proton testbeams. Testbeam results from the CERN SPS show a module median-signal to noise of 11:1 for minimum ionising particles incident at a 45-degree angle. The best eight modules were installed on the ATLAS pixel support frame that was inserted into ATLAS in the summer of 2007. This paper describes the full BCM detector system along with simulation studies being used to develop the logic in the back-end FPGA coincidence hardware.

Technical guide for monitoring selected conditions related to wilderness character

Science.gov (United States)

Peter Landres; Steve Boutcher; Liese Dean; Troy Hall; Tamara Blett; Terry Carlson; Ann Mebane; Carol Hardy; Susan Rinehart; Linda Merigliano; David N. Cole; Andy Leach; Pam Wright; Deb Bumpus

2009-01-01

The purpose of monitoring wilderness character is to improve wilderness stewardship by providing managers a tool to assess how selected actions and conditions related to wilderness character are changing over time. Wilderness character monitoring provides information to help answer two key questions about wilderness character and wilderness stewardship: 1. How is...

Priming Ability Emotional Intelligence

Science.gov (United States)

Schutte, Nicola S.; Malouff, John M.

2012-01-01

Two studies examined whether priming self-schemas relating to successful emotional competency results in better emotional intelligence performance. In the first study participants were randomly assigned to a successful emotional competency self-schema prime condition or a control condition and then completed an ability measure of emotional…

Intelligence Naturelle et Intelligence Artificielle

OpenAIRE

Dubois, Daniel

2011-01-01

Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

Intelligent Structured Intermittent Auscultation (ISIA): evaluation of a decision-making framework for fetal heart monitoring of low-risk women

Science.gov (United States)

2014-01-01

Background Research-informed fetal monitoring guidelines recommend intermittent auscultation (IA) for fetal heart monitoring for low-risk women. However, the use of cardiotocography (CTG) continues to dominate many institutional maternity settings. Methods A mixed methods intervention study with before and after measurement was undertaken in one secondary level health service to facilitate the implementation of an initiative to encourage the use of IA. The intervention initiative was a decision-making framework called Intelligent Structured Intermittent Auscultation (ISIA) introduced through an education session. Results Following the intervention, medical records review revealed an increase in the use of IA during labour represented by a relative change of 12%, with improved documentation of clinical findings from assessments, and a significant reduction in the risk of receiving an admission CTG (RR 0.75, 95% CI, 0.60 – 0.95, p = 0.016). Conclusion The ISIA informed decision-making framework transformed the practice of IA and provided a mechanism for knowledge translation that enabled midwives to implement evidence-based fetal heart monitoring for low risk women. PMID:24884597

A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

Directory of Open Access Journals (Sweden)

Jeremy Straub

2013-05-01

Full Text Available An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response, this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

Semi-supervised vibration-based classification and condition monitoring of compressors

Science.gov (United States)

Potočnik, Primož; Govekar, Edvard

2017-09-01

Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.

Evaluation of an intelligent open learning system for engineering education

Directory of Open Access Journals (Sweden)

Maria Samarakou

2016-09-01

Full Text Available In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE, an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed.

Intelligent instrumentation principles and applications

CERN Document Server

Bhuyan, Manabendra

2011-01-01

With the advent of microprocessors and digital-processing technologies as catalyst, classical sensors capable of simple signal conditioning operations have evolved rapidly to take on higher and more specialized functions including validation, compensation, and classification. This new category of sensor expands the scope of incorporating intelligence into instrumentation systems, yet with such rapid changes, there has developed no universal standard for design, definition, or requirement with which to unify intelligent instrumentation. Explaining the underlying design methodologies of intelligent instrumentation, Intelligent Instrumentation: Principles and Applications provides a comprehensive and authoritative resource on the scientific foundations from which to coordinate and advance the field. Employing a textbook-like language, this book translates methodologies to more than 80 numerical examples, and provides applications in 14 case studies for a complete and working understanding of the material. Beginn...

New Fast Beam Conditions Monitoring (BCM1F) system for CMS

Science.gov (United States)

Zagozdzinska, A. A.; Bell, A. J.; Dabrowski, A. E.; Hempel, M.; Henschel, H. M.; Karacheban, O.; Przyborowski, D.; Leonard, J. L.; Penno, M.; Pozniak, K. T.; Miraglia, M.; Lange, W.; Lohmann, W.; Ryjov, V.; Lokhovitskiy, A.; Stickland, D.; Walsh, R.

2016-01-01

The CMS Beam Radiation Instrumentation and Luminosity (BRIL) project is composed of several systems providing the experiment protection from adverse beam conditions while also measuring the online luminosity and beam background. Although the readout bandwidth of the Fast Beam Conditions Monitoring system (BCM1F—one of the faster monitoring systems of the CMS BRIL), was sufficient for the initial LHC conditions, the foreseen enhancement of the beams parameters after the LHC Long Shutdown-1 (LS1) imposed the upgrade of the system. This paper presents the new BCM1F, which is designed to provide real-time fast diagnosis of beam conditions and instantaneous luminosity with readout able to resolve the 25 ns bunch structure.

Radiation Monitoring System in Advanced Spent Fuel Conditioning Process Facility

Energy Technology Data Exchange (ETDEWEB)

You, Gil Sung; Kook, D. H.; Choung, W. M.; Ku, J. H.; Cho, I. J.; You, G. S.; Kwon, K. C.; Lee, W. K.; Lee, E. P

2006-09-15

The Advanced spent fuel Conditioning Process is under development for effective management of spent fuel by converting UO{sub 2} into U-metal. For demonstration of this process, {alpha}-{gamma} type new hot cell was built in the IMEF basement . To secure against radiation hazard, this facility needs radiation monitoring system which will observe the entire operating area before the hot cell and service area at back of it. This system consists of 7 parts; Area Monitor for {gamma}-ray, Room Air Monitor for particulate and iodine in both area, Hot cell Monitor for hot cell inside high radiation and rear door interlock, Duct Monitor for particulate of outlet ventilation, Iodine Monitor for iodine of outlet duct, CCTV for watching workers and material movement, Server for management of whole monitoring system. After installation and test of this, radiation monitoring system will be expected to assist the successful ACP demonstration.

Radiation Monitoring System in Advanced Spent Fuel Conditioning Process Facility

International Nuclear Information System (INIS)

You, Gil Sung; Kook, D. H.; Choung, W. M.; Ku, J. H.; Cho, I. J.; You, G. S.; Kwon, K. C.; Lee, W. K.; Lee, E. P.

2006-09-01

The Advanced spent fuel Conditioning Process is under development for effective management of spent fuel by converting UO 2 into U-metal. For demonstration of this process, α-γ type new hot cell was built in the IMEF basement . To secure against radiation hazard, this facility needs radiation monitoring system which will observe the entire operating area before the hot cell and service area at back of it. This system consists of 7 parts; Area Monitor for γ-ray, Room Air Monitor for particulate and iodine in both area, Hot cell Monitor for hot cell inside high radiation and rear door interlock, Duct Monitor for particulate of outlet ventilation, Iodine Monitor for iodine of outlet duct, CCTV for watching workers and material movement, Server for management of whole monitoring system. After installation and test of this, radiation monitoring system will be expected to assist the successful ACP demonstration

Optimization of Remediation Conditions using Vadose Zone Monitoring Technology

Science.gov (United States)

Dahan, O.; Mandelbaum, R.; Ronen, Z.

2010-12-01

Success of in-situ bio-remediation of the vadose zone depends mainly on the ability to change and control hydrological, physical and chemical conditions of subsurface. These manipulations enables the development of specific, indigenous, pollutants degrading bacteria or set the environmental conditions for seeded bacteria. As such, the remediation efficiency is dependent on the ability to implement optimal hydraulic and chemical conditions in deep sections of the vadose zone. Enhanced bioremediation of the vadose zone is achieved under field conditions through infiltration of water enriched with chemical additives. Yet, water percolation and solute transport in unsaturated conditions is a complex process and application of water with specific chemical conditions near land surface dose not necessarily result in promoting of desired chemical and hydraulic conditions in deeper sections of the vadose zone. A newly developed vadose-zone monitoring system (VMS) allows continuous monitoring of the hydrological and chemical properties of the percolating water along deep sections of the vadose zone. Implementation of the VMS at sites that undergoes active remediation provides real time information on the chemical and hydrological conditions in the vadose zone as the remediation process progresses. Manipulating subsurface conditions for optimal biodegradation of hydrocarbons is demonstrated through enhanced bio-remediation of the vadose zone at a site that has been contaminated with gasoline products in Tel Aviv. The vadose zone at the site is composed of 6 m clay layer overlying a sandy formation extending to the water table at depth of 20 m bls. The upper 5 m of contaminated soil were removed for ex-situ treatment, and the remaining 15 m vadose zone is treated in-situ through enhanced bioremedaition. Underground drip irrigation system was installed below the surface on the bottom of the excavation. Oxygen and nutrients releasing powder (EHCO, Adventus) was spread below the

Mobile Surveillance and Monitoring Robots

International Nuclear Information System (INIS)

Kimberly, Howard R.; Shipers, Larry R.

1999-01-01

Long-term nuclear material storage will require in-vault data verification, sensor testing, error and alarm response, inventory, and maintenance operations. System concept development efforts for a comprehensive nuclear material management system have identified the use of a small flexible mobile automation platform to perform these surveillance and maintenance operations. In order to have near-term wide-range application in the Complex, a mobile surveillance system must be small, flexible, and adaptable enough to allow retrofit into existing special nuclear material facilities. The objective of the Mobile Surveillance and Monitoring Robot project is to satisfy these needs by development of a human scale mobile robot to monitor the state of health, physical security and safety of items in storage and process; recognize and respond to alarms, threats, and off-normal operating conditions; and perform material handling and maintenance operations. The system will integrate a tool kit of onboard sensors and monitors, maintenance equipment and capability, and SNL developed non-lethal threat response technology with the intelligence to identify threats and develop and implement first response strategies for abnormal signals and alarm conditions. System versatility will be enhanced by incorporating a robot arm, vision and force sensing, robust obstacle avoidance, and appropriate monitoring and sensing equipment

Condition monitoring through advanced sensor and computational technology

International Nuclear Information System (INIS)

Kim, Jung Taek; Hur, S.; Seong, S. H.; Hwang, Il Soon; Lee, Joon Hyun; You, Jun; Lee, Sang Jung

2004-01-01

In order to successfully implement the extended-life operation plan of the nuclear power plant (NPP), predictive maintenance based on on-line monitoring of deteriorated components becomes highly important. In this work, we present progresses in the development of an advanced monitoring system to detect the health condition on check valve failures and pipe wall-thinning phenomena. The failures of check valves have resulted in significant maintenance efforts, on occasion, have resulted in water hammer, over-pressurization of low-pressure systems, and damage to flow system components. Pipe wall-thinning is usually caused by Flow-Accelerated Corrosion (FAC) under the undesirable combination of water chemistry, flow velocity and material composition. A piping elbow in the moisture separator/reheater drain line on the secondary waterside of a PWR is chosen as a monitoring target

USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN QUALITY IMPROVING PROCESS

OpenAIRE

KALİTE İYİLEŞTİRME SÜRECİNDE YAPAY ZEKÃ KAYA; Orhan ENGİN

2005-01-01

Today, changing of competition conditions and customer preferences caused to happen many differences in the viewpoint of firms' quality studies. At the same time, improvements in computer technologies accelerated use of artificial intelligence. Artificial intelligence technologies are being used to solve many industry problems. In this paper, we investigated the use of artificial intelligence techniques to solve quality problems. The artificial intelligence techniques, which are used in quali...

Strong genetic overlap between executive functions and intelligence.

Science.gov (United States)

Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M

2016-09-01

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems

Directory of Open Access Journals (Sweden)

Thomas J. Lampoltshammer

2014-03-01

Full Text Available The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL, which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors’ by use of local sensors’ intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units.

Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems

Science.gov (United States)

Lampoltshammer, Thomas J.; de Freitas, Edison Pignaton; Nowotny, Thomas; Plank, Stefan; da Costa, João Paulo Carvalho Lustosa; Larsson, Tony; Heistracher, Thomas

2014-01-01

The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors' by use of local sensors' intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units. PMID:24618777

Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

Science.gov (United States)

Mutter, Kussay Nugamesh

2018-01-01

This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

Fast beam conditions monitor BCM1F for the CMS experiment

Energy Technology Data Exchange (ETDEWEB)

Bell, A. [CERN, Geneva (Switzerland); Geneva Univ. (Switzerland); Castro, E. [DESY Zeuthen (Germany); Hall-Wilton, R. [CERN, Geneva (Switzerland); Wisconsin Univ., Madison, WI (US)] (and others)

2009-10-15

The CMS Beam Conditions and Radiation Monitoring System, BRM, will support beam tuning, protect the CMS detector from adverse beam conditions, and measure the accumulated dose close to or inside all sub-detectors. It is composed of different sub-systems measuring either the particle flux near the beam pipe with time resolution between nano- and microseconds or the integrated dose over longer time intervals. This paper presents the Fast Beam Conditions Monitor, BCM1F, which is designed for fast flux monitoring measuring both beam halo and collision products. BCM1F is located inside the CMS pixel detector volume close to the beam-pipe. It uses sCVD diamond sensors and radiation hard front-end electronics, along with an analog optical readout of the signals. The commissioning of the system and its successful operation during the first beams of the LHC are described. (orig.)

Fast beam conditions monitor BCM1F for the CMS experiment

International Nuclear Information System (INIS)

Bell, A.; Castro, E.; Hall-Wilton, R.

2009-10-01

The CMS Beam Conditions and Radiation Monitoring System, BRM, will support beam tuning, protect the CMS detector from adverse beam conditions, and measure the accumulated dose close to or inside all sub-detectors. It is composed of different sub-systems measuring either the particle flux near the beam pipe with time resolution between nano- and microseconds or the integrated dose over longer time intervals. This paper presents the Fast Beam Conditions Monitor, BCM1F, which is designed for fast flux monitoring measuring both beam halo and collision products. BCM1F is located inside the CMS pixel detector volume close to the beam-pipe. It uses sCVD diamond sensors and radiation hard front-end electronics, along with an analog optical readout of the signals. The commissioning of the system and its successful operation during the first beams of the LHC are described. (orig.)

4th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations

CERN Document Server

Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed

2016-01-01

The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining, or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book no...

Business Intelligence technology: The Croatian case

Directory of Open Access Journals (Sweden)

Katarina Ćurko

2002-01-01

Full Text Available Each company aims to improve its business performance. Business Intelligence (BI helps enterprises to optimize their decision-making capabilities and to attain unprecedented levels of competitive advantage. Its usage leads to conditions, procedures and mechanisms for creating quality information and business knowledge. By these the organization can successfully respond to numerous pressures in dynamical and complex environment. The main objective of the paper is to present what the business intelligence is, and show the results of the research about the level and use of business intelligence in Croatian large organizations.

Complexity Intelligence and Cultural Coaching:

Directory of Open Access Journals (Sweden)

Jan Inglis

2005-06-01

Full Text Available In this article, we present the term complexity intelligence as a useful moniker to describe the reasoning ability, emotional capacity and social cognition necessary to meet the challenges of our prevailing life conditions. We suggest that, as a society and as individuals, we develop complexity intelligence as we navigate the gap between our current capacities and the capacities needed to respond to the next stage of complex challenges in our lives. We further suggest that it is possible to stimulate and support the emergence of complexity intelligence in a society, but we need a new form of social change agent - a cultural coach, to midwife its emergence.

Monitoring Human Activity through Portable Devices

Directory of Open Access Journals (Sweden)

G. Sebestyen

2012-06-01

Full Text Available Monitoring human activity may be useful for medical supervision and for prophylactic purposes. Mobile devices like intelligent phones or watches have multiple sensors and wireless communication capabilities which can be used for this purpose. This paper presents some integrated solutions for determining and continuous monitoring of a person’s state. Aspects taken into consideration are: activity detection and recognition based on acceleration sensors, wireless communication protocols for data acquisition, web monitoring, alerts generation and statistical processing of multiple sensorial data. As practical implementations two case studies are presented, one using an intelligent phone and another using a mixed signal processor integrated in a watch.

A Wavelet Bicoherence-Based Quadratic Nonlinearity Feature for Translational Axis Condition Monitoring

Directory of Open Access Journals (Sweden)

Yong Li

2014-01-01

Full Text Available The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features.

Life system modeling and intelligent computing. Pt. I. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation. (orig.)

Non-stationary Condition Monitoring of large diesel engines with the AEWATT toolbox

DEFF Research Database (Denmark)

Pontoppidan, Niels Henrik; Larsen, Jan; Sigurdsson, Sigurdur

2005-01-01

We are developing a specialized toolbox for non-stationary condition monitoring of large 2-stroke diesel engines based on acoustic emission measurements. The main contribution of this toolbox has so far been the utilization of adaptive linear models such as Principal and Independent Component Ana......, the inversion of those angular timing changes called “event alignment”, has allowed for condition monitoring across operation load settings, successfully enabling a single model to be used with realistic data under varying operational conditions-...

Conditional standard errors of measurement for composite scores on the Wechsler Preschool and Primary Scale of Intelligence-Third Edition.

Science.gov (United States)

Price, Larry R; Raju, Nambury; Lurie, Anna; Wilkins, Charles; Zhu, Jianjun

2006-02-01

A specific recommendation of the 1999 Standards for Educational and Psychological Testing by the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education is that test publishers report estimates of the conditional standard error of measurement (SEM). Procedures for calculating the conditional (score-level) SEM based on raw scores are well documented; however, few procedures have been developed for estimating the conditional SEM of subtest or composite scale scores resulting from a nonlinear transformation. Item response theory provided the psychometric foundation to derive the conditional standard errors of measurement and confidence intervals for composite scores on the Wechsler Preschool and Primary Scale of Intelligence-Third Edition.

Mimic sensor to monitor condition of human health; Mimic sensor wo riyoshita taicho monitoring

Energy Technology Data Exchange (ETDEWEB)

Nagata, Y. [Mechanical Engineering Lab., Tokyo (Japan)

2000-04-01

In the aging society where the birth rate decreases and the number of nuclear families increases, it is very important to inquire after the aged or physically handicapped people, to monitor their physical conditions, and to take steps to keep them healthy. As for the in-home physical measurement for the aged or physically handicapped people and the work of health management for them based on such measurement, it is feared that under the present conditions the invalid themselves or their family members or nurses will inevitably have to bear the burden and that nobody can deny the difficulty of continuing such nursing care. If daily physical condition measurement and related data collection are automatically carried out, however, interested people' burden will lessen and in-home heath management will become actually feasible. In this paper, a mimic sensor for realizing such a situation is described, which will measure physical conditions without interfering with the daily life of interested people. Serving as the mimic sensor is a blood flow sensor embedded in a telephone receiver, and changes in the blood flow during telephone conversation and changes in the gaps between peeks will be monitored. The feasibility is shown of continual collection of information necessary for the measurement of physical conditions of the aged or physically handicapped persons. (NEDO)

Fast beam condition monitor for CMS. Performance and upgrade

International Nuclear Information System (INIS)

Leonard, Jessica L.; Bell, Alan; Burtowy, Piotr

2014-05-01

The CMS beam and radiation monitoring subsystem BCM1F (Fast Beam Condition Monitor) consists of 8 individual diamond sensors situated around the beam pipe within the pixel detector volume, for the purpose of fast bunch-by-bunch monitoring of beam background and collision products. In addition, effort is ongoing to use BCM1F as an online luminosity monitor. BCM1F will be running whenever there is beam in LHC, and its data acquisition is independent from the data acquisition of the CMS detector, hence it delivers luminosity even when CMS is not taking data. A report is given on the performance of BCM1F during LHC run I, including results of the van der Meer scan and on-line luminosity monitoring done in 2012. In order to match the requirements due to higher luminosity and 25 ns bunch spacing, several changes to the system must be implemented during the upcoming shutdown, including upgraded electronics and precise gain monitoring. First results from Run II preparation are shown.

Fast Beam Condition Monitor for CMS: performance and upgrade

CERN Document Server

INSPIRE-00009152; Bell, Alan; Burtowy, Piotr; Dabrowski, Anne; Hempel, Maria; Henschel, Hans; Lange, Wolfgang; Lohmann, Wolfgang; Odell, Nathaniel; Penno, Marek; Pollack, Brian; Przyborowski, Dominik; Ryjov, Vladimir; Stickland, David; Walsh, Roberval; Warzycha, Weronika; Zagozdzinska, Agnieszka

2014-11-21

The CMS beam and radiation monitoring subsystem BCM1F (Fast Beam Condition Monitor) consists of 8 individual diamond sensors situated around the beam pipe within the pixel detector volume, for the purpose of fast bunch-by-bunch monitoring of beam background and collision products. In addition, effort is ongoing to use BCM1F as an online luminosity monitor. BCM1F will be running whenever there is beam in LHC, and its data acquisition is independent from the data acquisition of the CMS detector, hence it delivers luminosity even when CMS is not taking data. A report is given on the performance of BCM1F during LHC run I, including results of the van der Meer scan and on-line luminosity monitoring done in 2012. In order to match the requirements due to higher luminosity and 25 ns bunch spacing, several changes to the system must be implemented during the upcoming shutdown, including upgraded electronics and precise gain monitoring. First results from Run II preparation are shown.

System for monitoring microclimate conditions in greenhouse

Directory of Open Access Journals (Sweden)

Marković Dušan B.

2014-01-01

Full Text Available Monitoring microclimate parameters in different kind of environments has significant contribution to many areas of human activity and production processes. One of them is vegetable production in greenhouses where measurement of its microclimate parameters may influence the decision on taking appropriate action and protect crops. It is also important to preserve optimal condition in greenhouses to facilitate the process of transpiration, plant mineral nutrition and prevent of a variety physiological damage caused by a deficit of some specific nutrients. Systems for monitoring have wide application in the last years thanks to development of modern computer technology. In this paper model of the monitoring system based on smart transducer concept was introduced. Within the system components are based on MSP430 ultra low power micro controllers. They are using wireless communication to exchange data within the system that was structured according to smart transducer concept. User applications from the network could access to system interface using HTTP protocol where web server could be running on the computer or it could be an embedded web server running on micro controller based device.

Towards artificial intelligence based diesel engine performance control under varying operating conditions using support vector regression

Directory of Open Access Journals (Sweden)

Naradasu Kumar Ravi

2013-01-01

Full Text Available Diesel engine designers are constantly on the look-out for performance enhancement through efficient control of operating parameters. In this paper, the concept of an intelligent engine control system is proposed that seeks to ensure optimized performance under varying operating conditions. The concept is based on arriving at the optimum engine operating parameters to ensure the desired output in terms of efficiency. In addition, a Support Vector Machines based prediction model has been developed to predict the engine performance under varying operating conditions. Experiments were carried out at varying loads, compression ratios and amounts of exhaust gas recirculation using a variable compression ratio diesel engine for data acquisition. It was observed that the SVM model was able to predict the engine performance accurately.

Condition Management of Marine Lube Oil and the Role of Intelligent Sensor Systems in Diagnostics

International Nuclear Information System (INIS)

Knowles, M; Baglee, D

2012-01-01

Failures in marine diesel engines can be costly and can cause extreme inconvenience when they result in ships becoming stranded. Lubricating oil is a crucial component in maintaining engine reliability and so monitoring its condition is essential. Furthermore the lubricating oil offers early indication of various other engine faults. Current approaches to oil-based condition monitoring involve samples being sent for land based testing which involves considerable delay during which the situation could deteriorate further. Furthermore there is a substantial risk of contamination. The POSSEIDON project aimed to address this by developing a system involving real-time condition monitoring sensors observing the properties of the lubricating oil. Novel sensors were developed which address the specific issues associated with the marine environment. Furthermore, to complement the sensor system outputs, specific monitoring and diagnosis software has been developed to support the operation of onboard personnel with specific advice. On-line management of engine and lubricant condition aboard the ship may thus be achieved. In this paper we will describe the progress achieved in this area by the recently completed POSSEIDON project, outline the opportunities for ongoing development in this area and describe the roadmap for future development. The Reliability Centered Maintenance (RCM) paradigm will be applied to identify critical aspects of oil condition and prioritize parameters for measurement. The critical issues for development of the prototype unit into a viable commercial unit will be discussed including hardware design constraints, sensor miniaturization and display optimization. Issues such onboard connectivity, ship to shore communications will also be addressed.

Image edge detection based tool condition monitoring with morphological component analysis.

Science.gov (United States)

Yu, Xiaolong; Lin, Xin; Dai, Yiquan; Zhu, Kunpeng

2017-07-01

The measurement and monitoring of tool condition are keys to the product precision in the automated manufacturing. To meet the need, this study proposes a novel tool wear monitoring approach based on the monitored image edge detection. Image edge detection has been a fundamental tool to obtain features of images. This approach extracts the tool edge with morphological component analysis. Through the decomposition of original tool wear image, the approach reduces the influence of texture and noise for edge measurement. Based on the target image sparse representation and edge detection, the approach could accurately extract the tool wear edge with continuous and complete contour, and is convenient in charactering tool conditions. Compared to the celebrated algorithms developed in the literature, this approach improves the integrity and connectivity of edges, and the results have shown that it achieves better geometry accuracy and lower error rate in the estimation of tool conditions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

On the use of multi-agent systems for the monitoring of industrial systems

Science.gov (United States)

Rezki, Nafissa; Kazar, Okba; Mouss, Leila Hayet; Kahloul, Laid; Rezki, Djamil

2016-03-01

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.

Evaluation of the RSG-GAS Alpha-Beta Aerosol Contaminant Monitor Performance Under Reactor Operation Condition

International Nuclear Information System (INIS)

Hartoyo, Unggul; Setiawanto, Anto; Sumarno, Yulius

2000-01-01

Analysis to evaluate the RSG-GAS alpha-beta aerosol contaminant monitor performance was done. The high potential radiation working area such as in RSG-GAS is important to monitored for personal safety. Further it is necessary to assure that the system monitor is reliable enough under normal conditions as well as emergency condition. The method uses in this analysis are monitoring and comparing with the standard source. The standard course indicator and panel in main control room indicate that the result is 1 x 110 exp 9 Ci/m exp 3. Based on data monitor observation, the RSG-GAS alpha-beta aerosol contaminant monitor system under reactor operation condition has a good enough performance

A real time study on condition monitoring of distribution transformer using thermal imager

Science.gov (United States)

Mariprasath, T.; Kirubakaran, V.

2018-05-01

The transformer is one of the critical apparatus in the power system. At any cost, a few minutes of outages harshly influence the power system. Hence, prevention-based maintenance technique is very essential. The continuous conditioning and monitoring technology significantly increases the life span of the transformer, as well as reduces the maintenance cost. Hence, conditioning and monitoring of transformer's temperature are very essential. In this paper, a critical review has been made on various conditioning and monitoring techniques. Furthermore, a new method, hot spot indication technique, is discussed. Also, transformer's operating condition is monitored by using thermal imager. From the thermal analysis, it is inferred that major hotspot locations are appearing at connection lead out; also, the bushing of the transformer is the very hottest spot in transformer, so monitoring the level of oil is essential. Alongside, real time power quality analysis has been carried out using the power analyzer. It shows that industrial drives are injecting current harmonics to the distribution network, which causes the power quality problem on the grid. Moreover, the current harmonic limit has exceeded the IEEE standard limit. Hence, the adequate harmonics suppression technique is need an hour.

Remote condition-based monitoring of turbines

International Nuclear Information System (INIS)

2005-01-01

specific point in time; Timewave: Amount of motion and symmetry of wave shape (i.e., a truncated wave can be an indication of a rub); Orbits: A cross-sectional view of shaft movement; DC Gap Voltage: A measurement of the distance (e.g., gap) between the shaft and the proximity probes. This value is useful in determining bearing wear of shaft centerline location. Daily monitoring of these metrics will not only warn of impending failure, but provide valuable information regarding the possible cause of the impending failure and an approximate indication of time to failure. In the event of a sudden problem and subsequent trip of a turbine, this data helps determine the root cause of the failure. This results in faster problem resolution and a quicker restart of the turbine. Additionally, daily monitoring of these metrics allows companies to watch a problematic turbine's health until the next scheduled outage. Azima's remote, condition-based monitoring system and diagnostics service is an effective way to collect and trend these metrics on a daily basis, as well as supply expert advice in the event of any anomalies. The Azima system aggregates the analog data from the proximity probes mounted on the turbine at a sensor hub. The sensor hub digitizes the analog data and then, either wirelessly or through a wired Ethernet connection, sends the data via the Internet to a hosted server. The hosted server maintains the software that trends the data (e.g., vibration, spectrum, timewave, DC gap voltage, and orbits) and provides automatic alerting. The data can be accessed anywhere, anytime through a standard Web browser. The advantages of daily, remote, condition-based monitoring include: Daily monitoring of vital turbine health metrics to detect impending problems before they become critical; Automatic alerting when a change in condition is detected; Anywhere, anytime access via a standard Web browser. This allows multiple groups at different locations to simultaneously review and

A Review of the Condition Monitoring of Capacitors in Power Electronic Converters

DEFF Research Database (Denmark)

Soliman, Hammam Abdelaal Hammam; Wang, Huai; Blaabjerg, Frede

2015-01-01

Capacitor is one of the reliability critical components in power electronic systems. In the last two decades, many efforts in the academic research have been devoted to the condition monitoring of capacitors to estimate their health status. Industry applications demand more reliable power...... electronics products with preventive maintenance. Nevertheless, most of the developed capacitor condition monitoring technologies are rarely adopted by industry due to the complexity, increased cost and other relevant issues. An overview of the prior-art research in this area is therefore needed to justify....... Therefore, this paper firstly classifies the capacitor condition monitoring methods into three categories, then the respective technology evolution from 1993 to 2015 is summarized. Remarks on the state-of-the-art research and the future opportunities targeting for practical industry applications are given....

A Review of the Condition Monitoring of Capacitors in Power Electronic Converters

DEFF Research Database (Denmark)

Soliman, Hammam Abdelaal Hammam; Wang, Huai; Blaabjerg, Frede

2016-01-01

Capacitors are one type of reliability-critical components in power electronic systems. In the last two decades, many efforts in academic research have been devoted to the condition monitoring of capacitors to estimate their health status. Industry applications are demanding more reliable power...... electronics products with preventive maintenance. Nevertheless, most of the developed capacitor condition monitoring technologies are rarely adopted by industry due to the complexity, increased cost, and other relevant issues. An overview of the prior-art research in this area is therefore needed to justify......, this paper first classifies the capacitor condition monitoring methods into three categories, then the respective technology evolution in the last two decades is summarized. Finally, the state-of-the-art research and the future opportunities targeting for industry applications are given....

Assessing Speech Intelligibility in Children with Hearing Loss: Toward Revitalizing a Valuable Clinical Tool

Science.gov (United States)

Ertmer, David J.

2011-01-01

Background: Newborn hearing screening, early intervention programs, and advancements in cochlear implant and hearing aid technology have greatly increased opportunities for children with hearing loss to become intelligible talkers. Optimizing speech intelligibility requires that progress be monitored closely. Although direct assessment of…

Condition monitoring of oil-impregnated paper bushings using extension neural network, Gaussian mixture and hidden Markov models

CSIR Research Space (South Africa)

Miya, WS

2008-10-01

Full Text Available was performed in MATLAB simulation environment with an IntelTM CoreTM2 Duo computer operating at a processor speed of 3 GHz. ENN simulation procedures entail the use of optimal learning rate, a minimum number of epochs (also used as a training.... Intelligent Transformer Monitoring System Utilizing Neuro-Fuzzy Technique Approach http://www.pserc.org/cgipserc/getbig/publicati/reports/2004report/shures hi_smart_sensor_final_report.pdf, Last accessed 27 September 2007. [3] Wang M H. Extension Neural...

Advanced intelligent computational technologies and decision support systems

CERN Document Server

Kountchev, Roumen

2014-01-01

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

Public Health Intelligence: Learning From the Ebola Crisis

Science.gov (United States)

Weber, David Jay

2015-01-01

Today’s public health crises, as exemplified by the Ebola outbreak, lead to dramatic calls to action that typically include improved electronic monitoring systems to better prepare for, and respond to, similar occurrences in the future. Even a preliminary public health informatics evaluation of the current Ebola crisis exposes the need for enhanced coordination and sharing of trustworthy public health intelligence. We call for a consumer-centric model of public health intelligence and the formation of a national center to guide public health intelligence gathering and synthesis. Sharing accurate and actionable information with government agencies, health care practitioners, policymakers, and, critically, the general public, will mark a shift from doing public health surveillance on people to doing public health surveillance for people. PMID:26180978

Laboratory versus industrial cutting force sensor in tool condition monitoring system

International Nuclear Information System (INIS)

Szwajka, K

2005-01-01

Research works concerning the utilisation of cutting force measures in tool condition monitoring usually present results and deliberations based on laboratory sensors. These sensors are too fragile to be used in industrial practice. Industrial sensors employed on the factory floor are less accurate, and this must be taken into account when creating a tool condition monitoring strategy. Another drawback of most of these works is that constant cutting parameters are used for the entire tool life. This does not reflect industrial practice where the same tool is used at different feeds and depths of cut in sequential passes. This paper presents a comparison of signals originating from laboratory and industrial cutting force sensors. The usability of the sensor output was studied during a laboratory simulation of industrial cutting conditions. Instead of building mathematical models for the correlation between tool wear and cutting force, an FFBP artificial neural network was used to find which combination of input data would provide an acceptable estimation of tool wear. The results obtained proved that cross talk between channels has an important influence on cutting force measurements, however this input configuration can be used for a tool condition monitoring system

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

Science.gov (United States)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

2011-01-01

invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Design of intelligent power consumption optimization and visualization management platform for large buildings based on internet of things

Directory of Open Access Journals (Sweden)

Gong Shulan

2017-01-01

Full Text Available The buildings provide a significant contribution to total energy consumption and CO2 emission. It has been estimated that the development of an intelligent power consumption monitor and control system will result in about 30% savings in energy consumption. This design innovatively integrates the advanced technologies such as the internet of things, the internet, intelligent buildings and intelligent electricity which can offer open, efficient, convenient energy consumption detection platform in demand side and visual management demonstration application platform in power enterprises side. The system was created to maximize the effective and efficient the use of energy resource. It was development around sensor networks and intelligent gateway and the monitoring center software. This will realize the highly integration and comprehensive application in energy and information to meet the needs with intelligent buildings

A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

OpenAIRE

Straub, Jeremy; Huber, Justin

2013-01-01

An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (p...

Design and Realization of a Condition Management System for the Gateway Electrical Energy Metering Device

Directory of Open Access Journals (Sweden)

Chao Tang

2013-12-01

Full Text Available With the construction of firm and intelligent power grid in China, it is difficult for the traditional management method of electrical energy metering device to meet the prospecting requirements. Using the computer and internet techniques to realize the information and intelligentization of the electrical energy metering management has become a necessary guarantee of improving power supply ability, marketing control, and customer service. This paper introduced a kind of large and intelligent condition management system of the gateway electrical energy metering device. The key technologies and realize process were analyzed. Moreover, a detailed description of the application modules such as the GIS smart display of metering point, the condition management of metering devices and the visual monitoring of metering point was presented. The trial operation in the selected transformer substations and the power stations of Chongqing Power Electrical Corp. indicated that, the condition management system is very open, safety and efficient. According to the data exchange with the production and scheduling platform, the system improved the efficient operation of the electrical energy metering devices. Meanwhile, combined with the real-time visual monitoring, the condition management system improved the prevention ability of electricity filching, realized the unified automatic large-scale management of electrical energy metering devices.

Northeast Artificial Intelligence Consortium Annual Report. Volume 2. 1988 Discussing, Using, and Recognizing Plans (NLP)

Science.gov (United States)

1989-10-01

Encontro Portugues de Inteligencia Artificial (EPIA), Oporto, Portugal, September 1985. [15] N. J. Nilsson. Principles Of Artificial Intelligence. Tioga...FI1 F COPY () RADC-TR-89-259, Vol II (of twelve) Interim Report October 1969 AD-A218 154 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL...7a. NAME OF MONITORING ORGANIZATION Northeast Artificial Of p0ilcabe) Intelligence Consortium (NAIC) Rome_____ Air___ Development____Center

Application of Video Recognition Technology in Landslide Monitoring System

Directory of Open Access Journals (Sweden)

Qingjia Meng

2018-01-01

Full Text Available The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology.

System Interface for an Integrated Intelligent Safety System (ISS for Vehicle Applications

Directory of Open Access Journals (Sweden)

Mahammad A. Hannan

2010-01-01

Full Text Available This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS that includes an airbag deployment decision system (ADDS and a tire pressure monitoring system (TPMS. A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.

Monitoring machining conditions by analyzing cutting force vibration

Energy Technology Data Exchange (ETDEWEB)

Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan [Soongsl University, Seoul (Korea, Republic of)

2015-09-15

This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration.

Monitoring machining conditions by analyzing cutting force vibration

International Nuclear Information System (INIS)

Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan

2015-01-01

This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration

Space Communications Artificial Intelligence for Link Evaluation Terminal (SCAILET)

Science.gov (United States)

Shahidi, Anoosh

1991-01-01

A software application to assis end-users of the Link Evaluation Terminal (LET) for satellite communication is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving, 220/110 Mbps capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET and ACTS are being developed at the NASA Lewis Research Center. The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. By comparing the transmitted bit pattern with the received bit pattern, HBR LET can determine the bit error rate BER) under various atmospheric conditions. An algorithm for power augmentation is applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions. Programming scripts, defined by the design engineer, set up the HBR LET terminal by programming subsystem devices through IEEE488 interfaces. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. The combination of the learning curve and the complexities involved with editing the script files may discourage end-users from utilizing the full capabilities of the HBR LET system. An intelligent assistant component of SCAILET that addresses critical end-user needs in the programming of the HBR LET system as anticipated by its developers is described. A close look is taken at the various steps involved in writing ECM software for a C&P, computer and at how the intelligent assistant improves the HBR LET system and enhances the end-user's ability to perform the experiments.

Smart x-ray beam position monitor system using artificial intelligence methods for the advanced photon source insertion-device beamlines

International Nuclear Information System (INIS)

Shu, D.; Ding, H.; Barraza, J.; Kuzay, T.M.; Haeffner, D.; Ramanathan, M.

1997-09-01

At the Advanced Photon Source (APS), each insertion device (ID) beamline front-end has two XBPMs to monitor the X-ray beam position for both that vertical and horizontal directions. Performance challenges for a conventional photoemission type X-ray beam position monitor (XBPM) during operations are contamination of the signal from the neighboring bending magnet sources and the sensitivity of the XBPM to the insertion device (ID) gap variations. Problems are exacerbated because users change the ID gap during their operations, and hence the percentage level of the contamination in the front end XBPM signals varies. A smart XBPM system with a high speed digital signal processor has been built at the Advanced Photon Source for the ID beamline front ends. The new version of the software, which uses an artificial intelligence method, provides a self learning and self-calibration capability to the smart XBPM system. The structure of and recent test results with the system are presented in this paper

Predicting speech intelligibility in adverse conditions: evaluation of the speech-based envelope power spectrum model

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2011-01-01

conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility......The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... observed for the different interferers. None of the standardized models successfully describe these data....

An Analysis of the Influence of Signals Intelligence Through Wargaming

National Research Council Canada - National Science Library

McCaffrey, Charles

2000-01-01

Signals intelligence (SIGINT), information derived from the monitoring, interception, decryption and evaluation of an adversary's electronic communications, has long been viewed as a significant factor in modem warfare...

Crowd-Sourced Intelligence Agency: Prototyping counterveillance

Directory of Open Access Journals (Sweden)

Jennifer Gradecki

2017-02-01

Full Text Available This paper discusses how an interactive artwork, the Crowd-Sourced Intelligence Agency (CSIA, can contribute to discussions of Big Data intelligence analytics. The CSIA is a publicly accessible Open Source Intelligence (OSINT system that was constructed using information gathered from technical manuals, research reports, academic papers, leaked documents, and Freedom of Information Act files. Using a visceral heuristic, the CSIA demonstrates how the statistical correlations made by automated classification systems are different from human judgment and can produce false-positives, as well as how the display of information through an interface can affect the judgment of an intelligence agent. The public has the right to ask questions about how a computer program determines if they are a threat to national security and to question the practicality of using statistical pattern recognition algorithms in place of human judgment. Currently, the public’s lack of access to both Big Data and the actual datasets intelligence agencies use to train their classification algorithms keeps the possibility of performing effective sous-dataveillance out of reach. Without this data, the results returned by the CSIA will not be identical to those of intelligence agencies. Because we have replicated how OSINT is processed, however, our results will resemble the type of results and mistakes made by OSINT systems. The CSIA takes some initial steps toward contributing to an informed public debate about large-scale monitoring of open source, social media data and provides a prototype for counterveillance and sousveillance tools for citizens.

Higher Social Intelligence Can Impair Source Memory

Science.gov (United States)

Barber, Sarah J.; Franklin, Nancy; Naka, Makiko; Yoshimura, Hiroki

2010-01-01

Source monitoring is made difficult when the similarity between candidate sources increases. The current work examines how individual differences in social intelligence and perspective-taking abilities serve to increase source similarity and thus negatively impact source memory. Strangers first engaged in a cooperative storytelling task. On each…

Condition monitoring and maintenance of nuclear power plant concrete structures

International Nuclear Information System (INIS)

Orr, R.; Prasad, N.

1988-01-01

Nuclear power plant concrete structures are potentially subject to deterioration due to several environmental conditions, including weather exposure, ground water exposure, and sustained high temperature and radiation levels. The nuclear power plant are generally licensed for a term of 40 years. In order to maximize the return from the existing plants, feasibility studies are in progress for continued operation of many of these plants beyond the original licensed life span. This paper describes a study that was performed with an objective to define appropriate condition monitoring and maintenance procedures. A timely implementation of a condition monitoring and maintenance program would provide a valuable database and would provide justification for extension of the plant's design life. The study included concrete structures such as the containment buildings, interior structures, basemats, intake structures and cooling towers. Age-related deterioration at several operating power plants was surveyed and the potential degradation mechanisms have been identified

Surface Acoustic Wave (SAW Resonators for Monitoring Conditioning Film Formation

Directory of Open Access Journals (Sweden)

Siegfried Hohmann

2015-05-01

Full Text Available We propose surface acoustic wave (SAW resonators as a complementary tool for conditioning film monitoring. Conditioning films are formed by adsorption of inorganic and organic substances on a substrate the moment this substrate comes into contact with a liquid phase. In the case of implant insertion, for instance, initial protein adsorption is required to start wound healing, but it will also trigger immune reactions leading to inflammatory responses. The control of the initial protein adsorption would allow to promote the healing process and to suppress adverse immune reactions. Methods to investigate these adsorption processes are available, but it remains difficult to translate measurement results into actual protein binding events. Biosensor transducers allow user-friendly investigation of protein adsorption on different surfaces. The combination of several transduction principles leads to complementary results, allowing a more comprehensive characterization of the adsorbing layer. We introduce SAW resonators as a novel complementary tool for time-resolved conditioning film monitoring. SAW resonators were coated with polymers. The adsorption of the plasma proteins human serum albumin (HSA and fibrinogen onto the polymer-coated surfaces were monitored. Frequency results were compared with quartz crystal microbalance (QCM sensor measurements, which confirmed the suitability of the SAW resonators for this application.

A case study of remaining storage life prediction using stochastic filtering with the influence of condition monitoring

International Nuclear Information System (INIS)

Wang, Zhaoqiang; Hu, Changhua; Wang, Wenbin; Zhou, Zhijie; Si, Xiaosheng

2014-01-01

Some systems may spend most of their time in storage, but once needed, must be fully functional. Slow degradation occurs when the system is in storage, so to ensure the functionality of these systems, condition monitoring is usually conducted periodically to check the condition of the system. However, taking the condition monitoring data may require putting the system under real testing situation which may accelerate the degradation, and therefore, shorten the storage life of the system. This paper presents a case study of condition-based remaining storage life prediction for gyros in the inertial navigation system on the basis of the condition monitoring data and the influence of the condition monitoring data taking process. A stochastic-filtering-based degradation model is developed to incorporate both into the prediction of the remaining storage life distribution. This makes the predicted remaining storage life depend on not only the condition monitoring data but also the testing process of taking the condition monitoring data, which the existing prognostic techniques and algorithms did not consider. The presented model is fitted to the real condition monitoring data of gyros testing using the maximum likelihood estimation method for parameter estimation. Comparisons are made with the model without considering the process of taking the condition monitoring data, and the results clearly demonstrate the superiority of the newly proposed model

Business intelligence and mobile technology research an information systems engineering perspective

CERN Document Server

Laouar, Mohamed Ridda

2014-01-01

All business organizations strive for increasing their growth by seizing new opportunities, reducing enterprise costs, attracting new customers and retaining old customers. In doing so, business intelligence and analytics allow business organizations to make better plans, informed decisions, and monitor their progress towards planned goals and objectives. The more disruptive power of IT technologies comes synergistically. Individual IT technologies do not work in isolation. Business intellige...

Condition Monitoring Through Advanced Sensor and Computational Technology

International Nuclear Information System (INIS)

Kim, Jung Taek; Park, Won Man; Kim, Jung Soo; Seong, Soeng Hwan; Hur, Sub; Cho, Jae Hwan; Jung, Hyung Gue

2005-05-01

The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties

''Intelligent'' radiation measurements

International Nuclear Information System (INIS)

Ward, A.

1980-01-01

A description is given of three applications of current microprocessor technology which are characterized by the use of the microprocessor to impart a degree of intelligence to conventional radiation detection techniques. In the first application the microcomputer computes the radiation dose from the observed counting rate in a Geiger counter. In the second application the microcomputer provides the pulse height distribution and the radioisotopes used, from the spectrum of pulses from a scintillation counter. The third application is an arrangement for radiation monitor calibration. (H.K.)

Wireless condition monitoring for the RA-6 research reactor

International Nuclear Information System (INIS)

Garcia Peyrano, O.; Calzeta, O.; Rico, N.; Damiani, H.; Coutsiers, E.

1999-01-01

The vibration laboratory at C.A.B. has a great experience with the analysis and diagnostic of symptoms of failures in the rotating equipment of the R-6 research reactor and in our longest NPP (CANDU 600 Mw), located in Embalse town, Cordoba City, Argentina. Objective: The standard condition monitoring instrumentation system were designed for large equipment operating under different environmental conditions and sensitivities. The signal processing is not flexible and the diagnostic is an expensive method for the small poll type research reactors. This papers describes the research and development which are related whit the new concept, cheaper and flexible condition monitoring instrumentation system. Implementing a vibration analysis measurements technique with a sensor inside (in the pool) of the nuclear reactor RA-6, and mainly based on fft signal processing, an extensive program for vibration source identification was done. Different nuclear power conditions were monitored as full power and in zero power, also. This zero power shows the best acoustical environmental, because the cooling pumps are stop, and the core is cooling by natural convection. Two sensors were mainly used as the detector's subsystem. One of these detectors was an accelerometer attached to the top of the fine control rod and the other one was a water resistant omnidirectional microphone which was located underwater at different distances from the nuclear core. All the signal measurement by this two sensors were recorded and then was processed. Both signal was acquired at the same time for correlation analysis purposes. The analysis was composed by a 'Spectral Dynamics SD380' connected to a P.C. with dedicated post processing software. On the other hand, some calibration and sensitivity comparison was done using an SKFCM40, dual channel data collector and analyzer. (author)

ASSESSMENT OF CABLE AGING USING CONDITION MONITORING TECHNIQUES

International Nuclear Information System (INIS)

GROVE, E.; LOFARO, R.; SOO, P.; VILLARAN, M.; HSU, F.

2000-01-01

Electric cables in nuclear power plants suffer degradation during service as a result of the thermal and radiation environments in which they are installed. Instrumentation and control cables are one type of cable that provide an important role in reactor safety. Should the polymeric cable insulation material become embrittled and cracked during service, or during a loss-of-coolant-accident (LOCA) and when steam and high radiation conditions are anticipated, failure could occur and prevent the cables from fulfilling their intended safety function(s). A research program is being conducted at Brookhaven National Laboratory to evaluate condition monitoring (CM) techniques for estimating the amount of cable degradation experienced during in-plant service. The objectives of this program are to assess the ability of the cables to perform under a simulated LOCA without losing their ability to function effectively, and to identify CM techniques which may be used to determine the effective lifetime of cables. The cable insulation materials tested include ethylene propylene rubber (EPR) and cross-linked polyethylene (XLPE). Accelerated aging (thermal and radiation) to the equivalent of 40 years of service was performed, followed by exposure to simulated LOCA conditions. The effectiveness of chemical, electrical, and mechanical condition monitoring techniques are being evaluated. Results indicate that several of these methods can detect changes in material parameters with increasing age. However, each has its limitations, and a combination of methods may provide an effective means for trending cable degradation in order to assess the remaining life of cables

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

Energy Technology Data Exchange (ETDEWEB)

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo

2012-12-31

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve

Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods

OpenAIRE

Peng Guo; Nan Bai

2011-01-01

Condition Monitoring (CM) of wind turbines can greatly reduce the maintenance costs for wind farms, especially for offshore wind farms. A new condition monitoring method for a wind turbine gearbox using temperature trend analysis is proposed. Autoassociative Kernel Regression (AAKR) is used to construct the normal behavior model of the gearbox temperature. With a proper construction of the memory matrix, the AAKR model can cover the normal working space for the gearbox. When the gearbox has a...

On-line condition monitoring of nuclear systems via symbolic time series analysis

International Nuclear Information System (INIS)

Rajagopalan, V.; Ray, A.; Garcia, H. E.

2006-01-01

This paper provides a symbolic time series analysis approach to fault diagnostics and condition monitoring. The proposed technique is built upon concepts from wavelet theory, symbolic dynamics and pattern recognition. Various aspects of the methodology such as wavelet selection, choice of alphabet and determination of depth of D-Markov Machine are explained in the paper. The technique is validated with experiments performed in a Machine Condition Monitoring (MCM) test bed at the Idaho National Laboratory. (authors)

Intelligent MONitoring System for antiviral pharmacotherapy in patients with chronic hepatitis C (SiMON-VC

Directory of Open Access Journals (Sweden)

Luis Margusino-Framiñán

2017-01-01

Full Text Available Two out of six strategic axes of pharmaceutical care in our hospital are quality and safety of care, and the incorporation of information technologies. Based on this, an information system was developed in the outpatient setting for pharmaceutical care of patients with chronic hepatitis C, SiMON-VC, which would improve the quality and safety of their pharmacotherapy. The objective of this paper is to describe requirements, structure and features of Si- MON-VC. Requirements demanded were that the information system would enter automatically all critical data from electronic clinical records at each of the visits to the Outpatient Pharmacy Unit, allowing the generation of events and alerts, documenting the pharmaceutical care provided, and allowing the use of data for research purposes. In order to meet these requirements, 5 sections were structured for each patient in SiMON-VC: Main Record, Events, Notes, Monitoring Graphs and Tables, and Follow-up. Each section presents a number of tabs with those coded data needed to monitor patients in the outpatient unit. The system automatically generates alerts for assisted prescription validation, efficacy and safety of using antivirals for the treatment of this disease. It features a completely versatile Indicator Control Panel, where temporary monitoring standards and alerts can be set. It allows the generation of reports, and their export to the electronic clinical record. It also allows data to be exported to the usual operating systems, through Big Data and Business Intelligence. Summing up, we can state that SiMON-VC improves the quality of pharmaceutical care provided in the outpatient pharmacy unit to patients with chronic hepatitis C, increasing the safety of antiviral therapy.

An Intelligent and Secure Health Monitoring Scheme Using IoT Sensor Based on Cloud Computing

Directory of Open Access Journals (Sweden)

Jin-Xin Hu

2017-01-01

Full Text Available Internet of Things (IoT is the network of physical objects where information and communication technology connect multiple embedded devices to the Internet for collecting and exchanging data. An important advancement is the ability to connect such devices to large resource pools such as cloud. The integration of embedded devices and cloud servers offers wide applicability of IoT to many areas of our life. With the aging population increasing every day, embedded devices with cloud server can provide the elderly with more flexible service without the need to visit hospitals. Despite the advantages of the sensor-cloud model, it still has various security threats. Therefore, the design and integration of security issues, like authentication and data confidentiality for ensuring the elderly’s privacy, need to be taken into consideration. In this paper, an intelligent and secure health monitoring scheme using IoT sensor based on cloud computing and cryptography is proposed. The proposed scheme achieves authentication and provides essential security requirements.

Artificial Intelligence Applications to Fire Management

Science.gov (United States)

Don J. Latham

1987-01-01

Artificial intelligence could be used in Forest Service fire management and land-use planning to a larger degree than is now done. Robots, for example, could be programmed to monitor for fire and insect activity, to keep track of wildlife, and to do elementary thinking about the environment. Catching up with the fast-changing technology is imperative.

Intelligent Energy Management System for PV-Battery-based Microgrids in Future DC Homes

Science.gov (United States)

Chauhan, R. K.; Rajpurohit, B. S.; Gonzalez-Longatt, F. M.; Singh, S. N.

2016-06-01

This paper presents a novel intelligent energy management system (IEMS) for a DC microgrid connected to the public utility (PU), photovoltaic (PV) and multi-battery bank (BB). The control objectives of the proposed IEMS system are: (i) to ensure the load sharing (according to the source capacity) among sources, (ii) to reduce the power loss (high efficient) in the system, and (iii) to enhance the system reliability and power quality. The proposed IEMS is novel because it follows the ideal characteristics of the battery (with some assumptions) for the power sharing and the selection of the closest source to minimize the power losses. The IEMS allows continuous and accurate monitoring with intelligent control of distribution system operations such as battery bank energy storage (BBES) system, PV system and customer utilization of electric power. The proposed IEMS gives the better operational performance for operating conditions in terms of load sharing, loss minimization, and reliability enhancement of the DC microgrid.

Past, current and potential utilisation of active and intelligent packaging systems for meat and muscle-based products: A review.

Science.gov (United States)

Kerry, J P; O'Grady, M N; Hogan, S A

2006-09-01

Interest in the use of active and intelligent packaging systems for meat and meat products has increased in recent years. Active packaging refers to the incorporation of additives into packaging systems with the aim of maintaining or extending meat product quality and shelf-life. Active packaging systems discussed include oxygen scavengers, carbon dioxide scavengers and emitters, moisture control agents and anti-microbial packaging technologies. Intelligent packaging systems are those that monitor the condition of packaged foods to give information regarding the quality of the packaged food during transport and storage. The potential of sensor technologies, indicators (including integrity, freshness and time-temperature (TTI) indicators) and radio frequency identification (RFID) are evaluated for potential use in meat and meat products. Recognition of the benefits of active and intelligent packaging technologies by the food industry, development of economically viable packaging systems and increased consumer acceptance is necessary for commercial realisation of these packaging technologies.

Condition Monitoring Of Operating Pipelines With Operational Modal Analysis Application

OpenAIRE

Mironov Aleksey; Doronkin Pavel; Priklonsky Aleksander; Kabashkin Igor

2015-01-01

In the petroleum, natural gas and petrochemical industries, great attention is being paid to safety, reliability and maintainability of equipment. There are a number of technologies to monitor, control, and maintain gas, oil, water, and sewer pipelines. The paper focuses on operational modal analysis (OMA) application for condition monitoring of operating pipelines. Special focus is on the topicality of OMA for definition of the dynamic features of the pipeline (frequencies and mode shapes) i...

Intelligent Buildings and pervasive computing

DEFF Research Database (Denmark)

Grønbæk, Kaj; Kyng, Morten; Krogh, Peter Gall

2001-01-01

computers are everywhere, for everyone, at all times. Where IT becomes a still more integrated part of our environments with processors, sensors, and actuators connected via high-speed networks and combined with new visualiza-tion devices ranging from projections directly in the eye to large panorama......Intelligent Buildings have been the subject of research and commercial interest for more than two decades. The different perspectives range from monitoring and controlling energy consumption over interactive rooms supporting work in offices and leisure in the home, to buildings providing...... information to by-passers in plazas and urban environments. This paper puts forward the hypothesis that the coming decade will witness a dramatic increase in both quality and quantity of intelligent buildings due to the emerging field of pervasive computing: the next generation computing environments where...

Challenges for Research on Intelligence

Directory of Open Access Journals (Sweden)

Earl Hunt

2013-10-01

Full Text Available After 100 years of research, the definition of the field is still inadequate. The biggest challenge we see is moving away from a de-factor definition of intelligence in terms of test scores, but at the same time making clear what the boundaries of the field are. We then present four challenges for the field, two within a biological and two within a social context. These revolve around the issues of the malleability of intelligence and its display in everyday life, outside of a formal testing context. We conclude that developments in cognitive neuroscience and increases in the feasibility of monitoring behavior outside of the context of a testing session offer considerable hope for expansion of our both the biological and social aspects of individual differences in cognition.

Innovative applications of artificial intelligence

Science.gov (United States)

Schorr, Herbert; Rappaport, Alain

Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

Groundwater detection monitoring system design under conditions of uncertainty

NARCIS (Netherlands)

Yenigül, N.B.

2006-01-01

Landfills represent a wide-spread and significant threat to groundwater quality. In this thesis a methodology was developed for the design of optimal groundwater moni-toring system design at landfill sites under conditions of uncertainty. First a decision analysis approach was presented for optimal

Three State-of-the-Art Methods for Condition Monitoring

NARCIS (Netherlands)

Grimmelius, H.T.; Meiler, P.P.; Maas, H.L.M.M.; Bonnier, B.; Grevink, J.S.; Kuilenburg, R.F. van

1999-01-01

This paper describes and compares three different state-of-the-art condition monitoring techniques: first principles, feature extraction, and neural networks. The focus of the paper is on the application of the techniques, not on the underlying theory. Each technique is described briefly and is

Condition monitoring of pumps with co-relating field observations

International Nuclear Information System (INIS)

Mishra, S.K.; Prasad, V.; Sharma, R.B.

1994-01-01

The maintenance of 40 MWth research reactor, Cirus has been carried out for over 30 years following the time based maintenance schedule. With the commissioning of indigenously built 100 MWth nuclear research reactor Dhruva in the year 1985, a systematic work on condition monitoring has been commissioned. Apart from process parameters, which are recorded on hourly basis, vibration, noise, temperature, kurtosis etc. are measured for assessment of condition of pumps. The bearings of flywheel assembly of main pumps, Dhruva broke down almost abruptly during the initial years after first commissioning. The regular measurements of vibration level and kurtosis have greatly helped in avoiding breakdown. In a recent case one newly procured herringbone gear box (300 hp, 1475/1760 rpm) for the primary coolant pump was showing high vibration. In further checking using Fast Fourier Transform (FFT) analyser in a time domain plot the gear teeth damage was indicated. The pump was shut down for inspection and when the gear box was dismantled teeth were found broken. An attempt has been made in this paper to discuss a few interesting field experiences with condition monitoring and correlating field observations on pumps. (author). 3 figs

Communications interface for plant monitoring system

International Nuclear Information System (INIS)

Lee, K.L.; Morgan, F.A.

1988-01-01

This paper presents the communications interface for an intelligent color graphic system which PSE and G developed as part of a plant monitoring system. The intelligent graphic system is designed to off-load traditional host functions such as dynamic graphic updates, keyboard handling and alarm display. The distributed system's data and synchronization problems and their solutions are discussed

Intelligent web data management software architectures and emerging technologies

CERN Document Server

Ma, Kun; Yang, Bo; Sun, Runyuan

2016-01-01

This book presents some of the emerging techniques and technologies used to handle Web data management. Authors present novel software architectures and emerging technologies and then validate using experimental data and real world applications. The contents of this book are focused on four popular thematic categories of intelligent Web data management: cloud computing, social networking, monitoring and literature management. The Volume will be a valuable reference to researchers, students and practitioners in the field of Web data management, cloud computing, social networks using advanced intelligence tools.

Speech intelligibility for normal hearing and hearing-impaired listeners in simulated room acoustic conditions

DEFF Research Database (Denmark)

Arweiler, Iris; Dau, Torsten; Poulsen, Torben

Speech intelligibility depends on many factors such as room acoustics, the acoustical properties and location of the signal and the interferers, and the ability of the (normal and impaired) auditory system to process monaural and binaural sounds. In the present study, the effect of reverberation...... on spatial release from masking was investigated in normal hearing and hearing impaired listeners using three types of interferers: speech shaped noise, an interfering female talker and speech-modulated noise. Speech reception thresholds (SRT) were obtained in three simulated environments: a listening room......, a classroom and a church. The data from the study provide constraints for existing models of speech intelligibility prediction (based on the speech intelligibility index, SII, or the speech transmission index, STI) which have shortcomings when reverberation and/or fluctuating noise affect speech...

Monitoring parameters of technical condition and safety of aircraft using control charts

Directory of Open Access Journals (Sweden)

В.І. Чепіженко

2007-03-01

Full Text Available  The opportunity of control cards use for monitoring of a technical condition parameters and reliability of aviation techniques is considered at its operation on a technical condition.

The Piston Compressor: The Methodology of the Real-Time Condition Monitoring

International Nuclear Information System (INIS)

Naumenko, A P; Kostyukov, V N

2012-01-01

The methodology of a diagnostic signal processing, a function chart of the monitoring system are considered in the article. The methodology of monitoring and diagnosing is based on measurement of indirect processes' parameters (vibroacoustic oscillations) therefore no more than five sensors is established on the cylinder, measurement of direct structural and thermodynamic parameters is envisioned as well. The structure and principle of expert system's functioning of decision-making is given. Algorithm of automatic expert system includes the calculation diagnostic attributes values based on their normative values, formation sets of diagnostic attributes that correspond to individual classes to malfunction, formation of expert system messages. The scheme of a real-time condition monitoring system for piston compressors is considered. The system have consistently-parallel structure of information-measuring equipment, which allows to measure the vibroacoustic signal for condition monitoring of reciprocating compressors and modes of its work. Besides, the system allows to measure parameters of other physical processes, for example, system can measure and use for monitoring and statements of the diagnosis the pressure in decreasing spaces (the indicator diagram), the inlet pressure and flowing pressure of each cylinder, inlet and delivery temperature of gas, valves temperature, position of a rod, leakage through compression packing and others.

A New Dimension of Business Intelligence: Location-based Intelligence

OpenAIRE

Zeljko Panian

2012-01-01

Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

A New Fault Diagnosis Algorithm for PMSG Wind Turbine Power Converters under Variable Wind Speed Conditions

Directory of Open Access Journals (Sweden)

Yingning Qiu

2016-07-01

Full Text Available Although Permanent Magnet Synchronous Generator (PMSG wind turbines (WTs mitigate gearbox impacts, they requires high reliability of generators and converters. Statistical analysis shows that the failure rate of direct-drive PMSG wind turbines’ generators and inverters are high. Intelligent fault diagnosis algorithms to detect inverters faults is a premise for the condition monitoring system aimed at improving wind turbines’ reliability and availability. The influences of random wind speed and diversified control strategies lead to challenges for developing intelligent fault diagnosis algorithms for converters. This paper studies open-circuit fault features of wind turbine converters in variable wind speed situations through systematic simulation and experiment. A new fault diagnosis algorithm named Wind Speed Based Normalized Current Trajectory is proposed and used to accurately detect and locate faulted IGBT in the circuit arms. It is compared to direct current monitoring and current vector trajectory pattern approaches. The results show that the proposed method has advantages in the accuracy of fault diagnosis and has superior anti-noise capability in variable wind speed situations. The impact of the control strategy is also identified. Experimental results demonstrate its applicability on practical WT condition monitoring system which is used to improve wind turbine reliability and reduce their maintenance cost.

Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Directory of Open Access Journals (Sweden)

Hui-ying Chen

2013-01-01

Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.

Intelligent computer-aided training and tutoring

Science.gov (United States)

Loftin, R. Bowen; Savely, Robert T.

1991-01-01

Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

Intelligent monitoring of water chemistry - Diagnostic expert system DIWATM

International Nuclear Information System (INIS)

Metzner, W.; Streit, K.

2002-01-01

For fast and comprehensive evaluation of power plant water chemistry conditions and reliable diagnosis in the event of disturbances considerable advantages are provided by employment of the Diagnostic Expert System DIWA. The interface to the process control system (I and C) and the integration of the DIWA system in the office PC network are the preconditions that DIWA operates as a monitoring system in real time. The performance of diagnosis, which are processed by a fuzzy-logic-supported knowledge base ensures not only the detection of all disturbances but also different analyses of the plant operation mode. By editing the knowledge base the Al of the system can increase without system programming. (authors)

Intelligent Mobile Sensor System for drum inspection and monitoring - Volume 2. Final report, October 1, 1993 - April 22, 1995

International Nuclear Information System (INIS)

1995-01-01

The objective of the Intelligent Mobile Sensor System (IMSS) project was to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort was a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The system has an integrated sensor suite for problem-drum detection, and creates and maintains a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which portions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 96% of drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort was separated into three phases of which phase three is now complete. The first phase demonstrated an integrated system (maturity level IVa) for monitoring and inspection activities for waste storage facility operations. The second phase demonstrated a prototype system appropriate for operational use in an actual storage facility. The prototype employed an integrated design that considered operational requirements, hardware costs, maintenance, safety, and robustness. The final phase has demonstrated the commercial viability of the vehicle in operating waste storage facilities at Fernald, Ohio and the Idaho National Engineering Laboratory (INEL). This report summarizes the system upgrades performed in phase 3 and the evaluation of the IMSS Phase 3 system and vehicle

Intelligent Mobile Sensor System for drum inspection and monitoring - Volume 1. Final report, October 1, 1993 - April 22, 1995

International Nuclear Information System (INIS)

1995-01-01

The objective of the Intelligent Mobile Sensor System (IMSS) project is to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort is a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The device is capable of operating in the narrow free aisle space between rows of stacked drums. The system has an integrated sensor suite for problem-drum detection, and is linked to a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which portions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 96% of drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort is separated into three phases of which phase two is now complete. The first phase demonstrated an integrated system (maturity level IVa) for monitoring and inspection activities for waste storage facility operations. The second phase demonstrated a prototype system appropriate for operational use in an actual storage facility. The prototype provides an integrated design that considers operational requirements, hardware costs, maintenance, safety, and robustness. The final phase will demonstrate commercial viability using the prototype vehicle in a pilot waste operations and inspection project. This report summarizes the design and evaluation of the new IMSS Phase 2 system and vehicle

Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods

Directory of Open Access Journals (Sweden)

Peng Guo

2011-11-01

Full Text Available Condition Monitoring (CM of wind turbines can greatly reduce the maintenance costs for wind farms, especially for offshore wind farms. A new condition monitoring method for a wind turbine gearbox using temperature trend analysis is proposed. Autoassociative Kernel Regression (AAKR is used to construct the normal behavior model of the gearbox temperature. With a proper construction of the memory matrix, the AAKR model can cover the normal working space for the gearbox. When the gearbox has an incipient failure, the residuals between AAKR model estimates and the measurement temperature will become significant. A moving window statistical method is used to detect the changes of the residual mean value and standard deviation in a timely manner. When one of these parameters exceeds predefined thresholds, an incipient failure is flagged. In order to simulate the gearbox fault, manual temperature drift is added to the initial Supervisory Control and Data Acquisitions (SCADA data. Analysis of simulated gearbox failures shows that the new condition monitoring method is effective.

Improving the speech intelligibility in classrooms

Science.gov (United States)

Lam, Choi Ling Coriolanus

One of the major acoustical concerns in classrooms is the establishment of effective verbal communication between teachers and students. Non-optimal acoustical conditions, resulting in reduced verbal communication, can cause two main problems. First, they can lead to reduce learning efficiency. Second, they can also cause fatigue, stress, vocal strain and health problems, such as headaches and sore throats, among teachers who are forced to compensate for poor acoustical conditions by raising their voices. Besides, inadequate acoustical conditions can induce the usage of public address system. Improper usage of such amplifiers or loudspeakers can lead to impairment of students' hearing systems. The social costs of poor classroom acoustics will be large to impair the learning of children. This invisible problem has far reaching implications for learning, but is easily solved. Many researches have been carried out that they have accurately and concisely summarized the research findings on classrooms acoustics. Though, there is still a number of challenging questions remaining unanswered. Most objective indices for speech intelligibility are essentially based on studies of western languages. Even several studies of tonal languages as Mandarin have been conducted, there is much less on Cantonese. In this research, measurements have been done in unoccupied rooms to investigate the acoustical parameters and characteristics of the classrooms. The speech intelligibility tests, which based on English, Mandarin and Cantonese, and the survey were carried out on students aged from 5 years old to 22 years old. It aims to investigate the differences in intelligibility between English, Mandarin and Cantonese of the classrooms in Hong Kong. The significance on speech transmission index (STI) related to Phonetically Balanced (PB) word scores will further be developed. Together with developed empirical relationship between the speech intelligibility in classrooms with the variations

Intelligence analysis – the royal discipline of Competitive Intelligence

Directory of Open Access Journals (Sweden)

František Bartes

2011-01-01

Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

Real-Time Business Intelligence in the MIRABEL Smart Grid System

DEFF Research Database (Denmark)

Fischer, Ulrike; Kaulakiene, Dalia; Khalefa, Mohamed

2012-01-01

of energy related data, and must be able to react rapidly (but intelligently) when conditions change, leading to substantial real-time business intelligence challenges. This paper discusses these challenges and presents data management solutions in the European smart grid project MIRABEL. These solutions......) data. Experimental studies show that the proposed solutions support important real-time business intelligence tasks in a smart grid system....

Model architecture of intelligent data mining oriented urban transportation information

Science.gov (United States)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

Artificial intelligence: the future in nuclear plant maintenance

International Nuclear Information System (INIS)

Norgate, G.

1984-01-01

The role of robotics and remote handling equipment in future nuclear power plant maintenance activities is discussed in the context of artificial intelligence applications. Special requirements manipulators, control systems, and man-machine interfaces for nuclear applications are noted. Tasks might include inspection with cameras, eddy current probes, and leak detectors; the collection of material samples; radiation monitoring; and the disassembly, repair and reassembly of a variety of system components. A robot with vision and force sensing and an intelligent control system that can access a knowledge base is schematically described. Recent advances in image interpretation systems are also discussed

Intelligent structures and design of energy related facilities

International Nuclear Information System (INIS)

Namba, Haruyuki

1994-01-01

Possibility of applying intelligent structural concepts to civil design of energy plants is discussed. Intelligent structures, which are now common in aerospace engineering field, are also referred to as adaptive structures or smart structures depending on cases. Among various existing concepts, reconfigurable structures, precise shape control, structural monitoring using smart materials of optical fiber sensors, and relation with recent innovative communication technologies are focused from civil engineering point of view. Application of such new technologies will help to enhance design of energy related plants, which include multiplex functions which need to be very reliable and safe. (author)

A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ System for Structural Health Monitoring of Civil Structures

Directory of Open Access Journals (Sweden)

Gwanghee Heo

2017-07-01

Full Text Available In this paper, a data compression technology-based intelligent data acquisition (IDAQ system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform. The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF manner. In addition, the embedded software technology (EST has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size.

"SmartMonitor"--an intelligent security system for the protection of individuals and small properties with the possibility of home automation.

Science.gov (United States)

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-06-05

"SmartMonitor" is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the "SmartMonitor" system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons.

Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

OpenAIRE

Hanafi, Rustam

2010-01-01

The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

International Nuclear Information System (INIS)

Kazarov, A; Miotto, G Lehmann; Magnoni, L

2012-01-01

to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

Science.gov (United States)

Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-06-01

to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

Thinking about Intelligence Within, Without, and Beyond the State

OpenAIRE

Gill, Peter

2014-01-01

The reform or ‘democratization’ of intelligence has been studied in many countries essentially as a process of transition from authoritarian or ‘counterintelligence’ states to liberal democratic regimes in which security and intelligence agencies are subject to (more or less) democratic control and oversight. These studies have contributed to the growth in comparative studies of intelligence but have often ignored some key issues, including the conditions for the very existence of ‘state’ int...

Employing Artificial Intelligence To Minimise Internet Fraud

Directory of Open Access Journals (Sweden)

Edward Wong Sek Khin

2009-12-01

Full Text Available Internet fraud is increasing on a daily basis with new methods for extracting funds from government, corporations, businesses in general, and persons appearing almost hourly. The increases in on-line purchasing and the constant vigilance of both seller and buyer have meant that the criminal seems to be one-step ahead at all times. To pre-empt or to stop fraud before it can happen occurs in the non-computer based daily transactions of today because of the natural intelligence of the players, both seller and buyer. Currently, even with advances in computing techniques, intelligence is not the current strength of any computing system of today, yet techniques are available which may reduce the occurrences of fraud, and are usually referred to as artificial intelligence systems.This paper provides an overview of the use of current artificial intelligence (AI techniques as a means of combating fraud.Initially the paper describes how artificial intelligence techniques are employed in systems for detecting credit card fraud (online and offline fraud and insider trading.Following this, an attempt is made to propose the using of MonITARS (Monitoring Insider Trading and Regulatory Surveillance Systems framework which use a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing. Finally, the paper discusses future research agenda to the role of using MonITARS system.

Intelligent networks recent approaches and applications in medical systems

CERN Document Server

Ahamed, Syed V

2013-01-01

This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear

Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops

Directory of Open Access Journals (Sweden)

Cunji Zhang

2015-12-01

Full Text Available Radio Frequency Identification (RFID technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi® Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops.

Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops

Science.gov (United States)

Zhang, Cunji; Yao, Xifan; Zhang, Jianming

2015-01-01

Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi® Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops. PMID:26633418

Nanosensors for a Monitoring System in Intelligent and Active Packaging

Directory of Open Access Journals (Sweden)

Guillermo Fuertes

2016-01-01

Full Text Available A theoretical wireless nanosensor network (WNSN system that gives information about the food packaging condition is proposed. The protection effectiveness is estimated by measuring many factors, such as the existence of microorganisms, bacteria, gases, and contaminants. This study is focused on the detection of an antimicrobial agent (AA attached on a polymer forming an active integrated package. All monitoring technologies for food conservation are analyzed. Nanobiosensor nanomachine (NM, which converts biological or chemical signals into electrical signals, is used. A mathematical model, which describes the constituent’s emigration from the package to food, is programmed in MatLab software. The results show three nanobiosensors forming a WNSN. The nanobiosensors are able to carry out the average concentration for different spots in the package. This monitoring system shows reading percentages in three degrees and different colors: excellent (green, good (cyan, and lacking (red. To confirm the utility of the model, different simulations are performed. Using the WNSNs, results of AA existing in food package (FP through time were successfully obtained.

Intelligent data management for real-time spacecraft monitoring

Science.gov (United States)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

PERSONALIZED MEDICINE: GENOME, ELECTRONIC HEALTH AND INTELLIGENT SYSTEMS. PART 2. MOLECULAR GENETICS AND METHODS OF INTELLECTUAL ANALYSIS

Directory of Open Access Journals (Sweden)

B. A. Kobrinskii

2017-01-01

Full Text Available The transition to personalized medicine in practical terms should combine the problems of molecular-genetic predisposition to diseases with transient states in the organism in the direction of possible pathology. Classification and monitoring of the state can be  effectively carried out using artificial intelligence methods. Various intellectual approaches are considered in different conditions for  monitoring patient.

Monitoring the Microcirculation in Critical Conditions: Possibilities and Limitations

Directory of Open Access Journals (Sweden)

T. O. Tokmakova

2012-01-01

Full Text Available The paper provides an analytical review of the references on the role of microcirculatory disorders in the development of critical conditions, the significance of circulatory monitoring, specifically, to make a presumptive prognosis of multiple organ dysfunction. It defines main directions in the diagnosis and correction of microcirculatory disorders as direct (infusion therapy and indirect (influence on the components of a systemic inflammatory response, by extending to microcirculatory correction microcirculatory exposures. Key words: critical conditions, multiple organ dysfunction, procedures to evaluate and correct microcirculation.

Development of an Intelligent Maximum Power Point Tracker Using an Advanced PV System Test Platform

DEFF Research Database (Denmark)

Spataru, Sergiu; Amoiridis, Anastasios; Beres, Remus Narcis

2013-01-01

The performance of photovoltaic systems is often reduced by the presence of partial shadows. The system efficiency and availability can be improved by a maximum power point tracking algorithm that is able to detect partial shadow conditions and to optimize the power output. This work proposes...... an intelligent maximum power point tracking method that monitors the maximum power point voltage and triggers a current-voltage sweep only when a partial shadow is detected, therefore minimizing power loss due to repeated current-voltage sweeps. The proposed system is validated on an advanced, flexible...... photovoltaic inverter system test platform that is able to reproduce realistic partial shadow conditions, both in simulation and on hardware test system....

Intelligent data analysis: the best approach for chronic heart failure (CHF) follow up management.

Science.gov (United States)

Mohammadzadeh, Niloofar; Safdari, Reza; Baraani, Alireza; Mohammadzadeh, Farshid

2014-08-01

Intelligent data analysis has ability to prepare and present complex relations between symptoms and diseases, medical and treatment consequences and definitely has significant role in improving follow-up management of chronic heart failure (CHF) patients, increasing speed ​​and accuracy in diagnosis and treatments; reducing costs, designing and implementation of clinical guidelines. The aim of this article is to describe intelligent data analysis methods in order to improve patient monitoring in follow and treatment of chronic heart failure patients as the best approach for CHF follow up management. Minimum data set (MDS) requirements for monitoring and follow up of CHF patient designed in checklist with six main parts. All CHF patients that discharged in 2013 from Tehran heart center have been selected. The MDS for monitoring CHF patient status were collected during 5 months in three different times of follow up. Gathered data was imported in RAPIDMINER 5 software. Modeling was based on decision trees methods such as C4.5, CHAID, ID3 and k-Nearest Neighbors algorithm (K-NN) with k=1. Final analysis was based on voting method. Decision trees and K-NN evaluate according to Cross-Validation. Creating and using standard terminologies and databases consistent with these terminologies help to meet the challenges related to data collection from various places and data application in intelligent data analysis. It should be noted that intelligent analysis of health data and intelligent system can never replace cardiologists. It can only act as a helpful tool for the cardiologist's decisions making.

Intelligence analysis – the royal discipline of Competitive Intelligence

OpenAIRE

František Bartes

2011-01-01

The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

Technological monitoring radar: a weak signals interpretation tool for the identification of strategic surprises

Directory of Open Access Journals (Sweden)

Adalton Ozaki

2011-07-01

Full Text Available In the current competitive scenario, marked by rapid and constant changes, it is vital that companies actively monitor the business environment, in search of signs which might anticipate changes. This study poses to propose and discuss a tool called Technological Monitoring Radar, which endeavours to address the following query: “How can a company systematically monitor the environment and capture signs that anticipate opportunities and threats concerning a particular technology?”. The literature review covers Competitive Intelligence, Technological Intelligence, Environmental Analysis and Anticipative Monitoring. Based on the critical analysis of the literature, a tool called Technological Monitoring Radar is proposed comprising five environments to be monitored (political, economical, technological, social and competition each of which with key topics for analysis. To exemplify the use of the tool, it is applied to the smartphone segment in an exclusively reflexive manner, and without the participation of a specific company. One of the suggestions for future research is precisely the application of the proposed methodology in an actual company. Despite the limitation of this being a theoretical study, the example demonstrated the tool´s applicability. The radar prove to be very useful for a company that needs to monitor the environment in search of signs of change. This study´s main contribution is to relate different fields of study (technological intelligence, environmental analysis and anticipative monitoring and different approaches to provide a practical tool that allows a manager to identify and better visualize opportunities and threats, thus avoiding strategic surprises in the technological arena.Key words: Technological monitoring. Technological intelligence. Competitive intelligence. Weak signals.

Artificial intelligence applications in the intensive care unit.

Science.gov (United States)

Hanson, C W; Marshall, B E

2001-02-01

To review the history and current applications of artificial intelligence in the intensive care unit. The MEDLINE database, bibliographies of selected articles, and current texts on the subject. The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. All literature relevant to the topic was reviewed. Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

New oil condition monitoring system, Wearsens® enables continuous, online detection of critical operating conditions and wear damage

Directory of Open Access Journals (Sweden)

Manfred Mauntz

2015-12-01

Full Text Available A new oil sensor system is presented for the continuous, online measurement of the wear in turbines, industrial gears, generators, hydraulic systems and transformers. Detection of change is much earlier than existing technologies such as particle counting, vibration measurement or recording temperature. Thus targeted, corrective procedures and/or maintenance can be carried out before actual damage occurs. Efficient machine utilization, accurately timed preventive maintenance, increased service life and a reduction of downtime can all be achieved. The presented sensor system effectively controls the proper operation conditions of bearings and cogwheels in gears. The online diagnostics system measures components of the specific complex impedance of oils. For instance, metal abrasion due to wear debris, broken oil molecules, forming acids or oil soaps, result in an increase of the electrical conductivity, which directly correlates with the degree of contamination of the oil. For additivated lubricants, the stage of degradation of the additives can also be derived from changes in the dielectric constant. The determination of impurities or reduction in the quality of the oil and the quasi continuous evaluation of wear and chemical aging follow the holistic approach of a real-time monitoring of an alteration in the condition of the oil-machine system. Once the oil condition monitoring sensors are installed on the wind turbine, industrial gearbox and test stands, the measuring data can be displayed and evaluated elsewhere. The signals are transmitted to a web-based condition monitoring system via LAN, WLAN or serial interfaces of the sensor unit. Monitoring of the damage mechanisms during proper operation below the tolerance limits of the components enables specific preventive maintenance independent of rigid inspection intervals.

Artificial Intelligence in Cardiology.

Science.gov (United States)

Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

2018-06-12

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Intelligence in youth and health at age 50

Science.gov (United States)

Wraw, Christina; Deary, Ian J.; Gale, Catharine R.; Der, Geoff

2015-01-01

Background The link between intelligence in youth and all-cause mortality in later-life is well established. To better understand this relationship, the current study examines the links between pre-morbid intelligence and a number of specific health outcomes at age 50 using the NLSY-1979 cohort. Methods Participants were the 5793 participants in the NLSY-79 who responded to questions about health outcomes at age 50. Sixteen health outcomes were examined: two were summary measures (physical health and functional limitation), 9 were diagnosed illness conditions, 4 were self-reported conditions, and one was a measure of general health status. Linear and logistic regressions were used, as appropriate, to examine the relationship between intelligence in youth and the health outcomes. Age, sex and both childhood and adult SES, and its sub-components – income, education, & occupational prestige – are all adjusted for separately. Results & conclusion Higher pre-morbid intelligence is linked with better physical health at age 50, and a lower risk for a number of chronic health conditions. For example, a 1 SD higher score in IQ was significantly associated with increased odds of having good, very good, or excellent health, with an odds ratio of 1.70 (C.I. 1.55–1.86). Thirteen of the illness outcomes were significantly and negatively associated with IQ in youth; the odds ratios ranged from 0.85 for diabetes/high blood sugar to 0.65 for stroke, per one standard deviation higher score in IQ. Adjustment for childhood SES led to little attenuation but adult SES partially mediated the relationship for a number of conditions. Mediation by adult SES was not consistently explained by any one of its components—income, education, and occupation status. The current findings contribute to our understanding of lower intelligence as a risk factor for poor health and how this may contribute to health inequalities. PMID:26766880

Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

Energy Technology Data Exchange (ETDEWEB)

Sheng, S.

2012-07-01

The Gearbox Reliability Collaborative (GRC) at the National Wind Technology Center (NWTC) tested two identical gearboxes. One was tested on the NWTCs 2.5 MW dynamometer and the other was field tested in a turbine in a nearby wind plant. In the field, the test gearbox experienced two oil loss events that resulted in damage to its internal bearings and gears. Since the damage was not severe, the test gearbox was removed from the field and retested in the NWTCs dynamometer before it was disassembled. During the dynamometer retest, some vibration data along with testing condition information were collected. These data enabled NREL to launch a Wind Turbine Gearbox Condition Monitoring Round Robin project, as described in this report. The main objective of this project was to evaluate different vibration analysis algorithms used in wind turbine condition monitoring (CM) and find out whether the typical practices are effective. With involvement of both academic researchers and industrial partners, the project sets an example on providing cutting edge research results back to industry.

Condition Monitoring and Management from Acoustic Emissions

DEFF Research Database (Denmark)

Pontoppidan, Niels Henrik Bohl

2005-01-01

In the following, I will use technical terms without explanation as it gives the freedom to describe the project in a shorter form for those who already know. The thesis is about condition monitoring of large diesel engines from acoustic emission signals. The experiments have been focused...... is the analysis of the angular position changes of the engine related events such as fuel injection and valve openings, caused by operational load changes. With inspiration from speech recognition and voice effects the angular timing changes have been inverted with the event alignment framework. With the event...

Condition monitoring approach for permanent magnet synchronous motor drives based on the INFORM method

OpenAIRE

Arellano-Padilla, J.; Sumner, M.; Gerada, C.

2016-01-01

This paper proposes a monitoring scheme based on saliency tracking to assess the health condition of PMSM drives operating under non stationary conditions. The evaluated scheme is based on the INFORM methodology, which is associated to the accurate sensorless control of PM drives without zero speed limitation. The result is a monitoring scheme that is able to detect faults that would be very difficult to evaluate under nonstationary conditions. A relevant aspect of the proposed scheme is that...

Vibration condition monitoring of planetary gearbox under varying external load

Energy Technology Data Exchange (ETDEWEB)

Bartelmus, W.; Zimroz, R. [Wroclaw University of Technology, Wroclaw (Poland)

2009-01-15

The paper shows that for condition monitoring of planetary gearboxes it is important to identify the external varying load condition. In the paper, systematic consideration has been taken of the influence of many factors on the vibration signals generated by a system in which a planetary gearbox is included. These considerations give the basis for vibration signal interpretation, development of the means of condition monitoring, and for the scenario of the degradation of the planetary gearbox. Real measured vibration signals obtained in the industrial environment are processed. The signals are recorded during normal operation of the diagnosed objects, namely planetary gearboxes, which are a part of the driving system used in a bucket wheel excavator, used in lignite mines. It has been found that the most important factor of the proper planetary gearbox condition is connected with perturbation of arm rotation, where an arm rotation gives rise to a specific vibration signal whose properties are depicted by a short-time Fourier transform (STFT) and Wigner-Ville distribution presented as a time-frequency map. The paper gives evidence that there are two dominant low-frequency causes that influence vibration signal modulation, i.e. the varying load, which comes from the nature of the bucket wheel digging process, and the arm/carrier rotation. These two causes determine the condition of the planetary gearboxes considered.

Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.

Science.gov (United States)

Labovitz, Daniel L; Shafner, Laura; Reyes Gil, Morayma; Virmani, Deepti; Hanina, Adam

2017-05-01

This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulants, while reducing the need for monitoring, have also placed pressure on patients to self-manage. Suboptimal adherence goes undetected as routine laboratory tests are not reliable indicators of adherence, placing patients at increased risk of stroke and bleeding. A randomized, parallel-group, 12-week study was conducted in adults (n=28) with recently diagnosed ischemic stroke receiving any anticoagulation. Patients were randomized to daily monitoring by the artificial intelligence platform (intervention) or to no daily monitoring (control). The artificial intelligence application visually identified the patient, the medication, and the confirmed ingestion. Adherence was measured by pill counts and plasma sampling in both groups. For all patients (n=28), mean (SD) age was 57 years (13.2 years) and 53.6% were women. Mean (SD) cumulative adherence based on the artificial intelligence platform was 90.5% (7.5%). Plasma drug concentration levels indicated that adherence was 100% (15 of 15) and 50% (6 of 12) in the intervention and control groups, respectively. Patients, some with little experience using a smartphone, successfully used the technology and demonstrated a 50% improvement in adherence based on plasma drug concentration levels. For patients receiving direct oral anticoagulants, absolute improvement increased to 67%. Real-time monitoring has the potential to increase adherence and change behavior, particularly in patients on direct oral anticoagulant therapy. URL: http://www.clinicaltrials.gov. Unique identifier: NCT02599259. © 2017 American Heart Association, Inc.

A design condition for incorporating human judgement into monitoring systems

International Nuclear Information System (INIS)

Tanaka, K.; Klir, G.J.

1999-01-01

In safety monitoring, there exists an uncertainty situation in which the sensor cannot detect whether or not the monitored object is in danger. For the uncertainty zone identified by a non-homogeneous safety monitoring system that utilizes two types of sensors with different thresholds, operators or experts are expected to judge whether the real state is safe or dangerous on the basis of additional information from a detailed inspection or other related sensors output. However, the activities for inspection performed by relevant humans may require additional cost and introduce inspection errors. The present article proposes two types of an automatic monitoring system not involving any human inspection or a human-machine (H-M) cooperative monitoring system with inspection. In order to compare the systems, an approach based on the Dempster-Shafer theory is proposed as uncertainty analysis by this theory (it is simpler than by the traditional Bayesian approach). By comparing their expected losses as a result of failed dangerous failures or failed safe failures as well as the inspection errors, the condition is determined under which H-M cooperative systems incorporating human judgements are more effective than automatic monitoring systems

Verification of the machinery condition monitoring technology by fault simulation tests

International Nuclear Information System (INIS)

Maehara, Takafumi; Watanabe, Yukio; Osaki, Kenji; Higuma, Koji; Nakano, Tomohito

2009-01-01

This paper shows the test items and equipments introduced by Japan Nuclear Energy Safety Organization to establish the monitoring technique for machinery conditions. From the result of vertical pump simulation tests, it was confirmed that fault analysis was impossible by measuring the accelerations on both motor and pump column pipes, however, was possible by measuring of pump shaft vibrations. Because hydraulic whirls by bearing wear had significant influences over bearing misalignments and flow rates, the monitoring trends must be done under the same condition (on bearing alignments and flow rates). We have confirmed that malfunctions of vertical pumps can be diagnosed using measured shaft vibration by ultrasonic sensors from outer surface of pump casing on the floor. (author)

Condition monitoring of a motor-operated valve using estimated motor torque

International Nuclear Information System (INIS)

Chai, Jangbom; Kang, Shinchul; Park, Sungkeun; Hong, Sungyull; Lim, Chanwoo

2004-01-01

This paper is concerned with the development of data analysis methods to be used in on-line monitoring and diagnosis of Motor-Operated Valves (MOVs) effectively and accurately. The technique to be utilized includes the electrical measurements and signal processing to estimate electric torque of induction motors, which are attached to most of MOV systems. The estimated torque of an induction motor is compared with the directly measured torque using a torque cell in various loading conditions including the degraded voltage conditions to validate the estimating scheme. The accuracy of the estimating scheme is presented. The advantages of the estimated torque signatures are reviewed over the currently used ones such as the current signature and the power signature in several respects: accuracy, sensitivity, resolution and so on. Additionally, the estimated torque methods are suggested as a good way to monitor the conditions of MOVs with higher accuracy. (author)

Run II performance of luminosity and beam condition monitors at CMS

Energy Technology Data Exchange (ETDEWEB)

Leonard, Jessica Lynn [DESY, Hamburg (Germany)

2016-07-01

The BRIL (Beam Radiation Instrumentation and Luminosity) system of CMS consists of instrumentation to measure the luminosity online and offline, and to monitor the LHC beam conditions inside CMS. An accurate luminosity measurement is essential to the CMS physics program, and measurement of the beam background is necessary to ensure safe operation of CMS. Many of the BRIL subsystems have been upgraded and others have been added for LHC Run II to complement the existing measurements. The beam condition monitor (BCM) consists of several sets of diamond sensors used to measure online luminosity and beam background with a single-bunch-crossing resolution. The BCM also detects when beam conditions become unfavorable for CMS running and may trigger a beam abort to protect the detector. The beam halo monitor (BHM) uses quartz bars to measure the background of the incoming beams at larger radii. The pixel luminosity telescope (PLT) consists of telescopes of silicon sensors designed to provide a CMS online and offline luminosity measurement. In addition, the forward hadronic calorimeter (HF) delivers an independent luminosity measurement, making the whole system robust and allowing for cross-checks of the systematics. An overview of the performance during 2015 LHC running for the new/updated BRIL subsystems will be given, including the uncertainties of the luminosity measurements.

Computational intelligence in biomedical imaging

CERN Document Server

2014-01-01

This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients’ medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians’ decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational inte...

Radiation monitoring system based on EPICS

International Nuclear Information System (INIS)

Wang Weizhen; Li Jianmin; Wang Xiaobing; Hua Zhengdong; Xu Xunjiang

2008-01-01

Shanghai Synchrotron Radiation Facility (SSRF for short) is a third-generation light source building in China, including a 150 MeV injector, 3.5 GeV booster, 3.5 GeV storage ring and an amount of beam line stations. During operation, a mass of Synchrotron Radiation will be produced by electrons in the booster and the storage ring. Bremsstrahlung and neutrons will also be produced as a result of the interaction between the electrons, especially the beam loss, and the wall of the vacuum beam pipe. SSRF Radiation Monitoring System is established for monitoring the radiation dosage of working area and environment while SSRF operating. The system consists of detectors, intelligent data-collecting modules, monitoring computer, and managing computer. The software system is developed based on EPICS (Experimental Physics and Industrial Control System), implementing the collecting and monitoring the data output from intelligent modules, analyzing the data, and so on. (authors)

Guaranteeing robustness of structural condition monitoring to environmental variability

Science.gov (United States)

Van Buren, Kendra; Reilly, Jack; Neal, Kyle; Edwards, Harry; Hemez, François

2017-01-01

Advances in sensor deployment and computational modeling have allowed significant strides to be recently made in the field of Structural Health Monitoring (SHM). One widely used SHM strategy is to perform a vibration analysis where a model of the structure's pristine (undamaged) condition is compared with vibration response data collected from the physical structure. Discrepancies between model predictions and monitoring data can be interpreted as structural damage. Unfortunately, multiple sources of uncertainty must also be considered in the analysis, including environmental variability, unknown model functional forms, and unknown values of model parameters. Not accounting for these sources of uncertainty can lead to false-positives or false-negatives in the structural condition assessment. To manage the uncertainty, we propose a robust SHM methodology that combines three technologies. A time series algorithm is trained using "baseline" data to predict the vibration response, compare predictions to actual measurements collected on a potentially damaged structure, and calculate a user-defined damage indicator. The second technology handles the uncertainty present in the problem. An analysis of robustness is performed to propagate this uncertainty through the time series algorithm and obtain the corresponding bounds of variation of the damage indicator. The uncertainty description and robustness analysis are both inspired by the theory of info-gap decision-making. Lastly, an appropriate "size" of the uncertainty space is determined through physical experiments performed in laboratory conditions. Our hypothesis is that examining how the uncertainty space changes throughout time might lead to superior diagnostics of structural damage as compared to only monitoring the damage indicator. This methodology is applied to a portal frame structure to assess if the strategy holds promise for robust SHM. (Publication approved for unlimited, public release on October-28

Policy based Agents in Wireless Body Sensor Mesh Networks for Patient Health Monitoring

OpenAIRE

Kevin Miller; Suresh Sankaranarayanan

2009-01-01

There is presently considerable research interest in using wireless and mobile technologies in patient health monitoring particularly in hospitals and nursing homes. For health monitoring,, an intelligent agent based hierarchical architecture has already been published by one of the authors of this paper. Also, the technique of monitoring and notifying the health of patients using an intelligent agent, to the concerned hospital personnel, has also been proposed. We now present the details of ...

The development of condition monitoring for the safety of rotating machine in PWR using motor current signature analysis

International Nuclear Information System (INIS)

Syaiful Bakhri

2013-01-01

Condition monitoring of rotating machine is essential to guarantee the safety operation as well as to improve the efficiency of nuclear power plants operations. One of the promising condition monitoring techniques which has been preferred currently since it is simple, non-invasive and inexpensive is Motor Stator Signature Analysis (MCSA). However, the investigation of the MCSA technique using a compact, low cost, and having industrial class hardware which is capable for nuclear power plant applications has been limited. The research is aimed to develop condition monitoring method based on MCSA utilizing a compact industrial class for nuclear power plant. The investigation includes development of condition monitoring based on real-time FPGA-CompatRIO hardware, development of a custom built display module for early warning system, testing of the monitoring hardware, fault frequency analysis of electric motors including the performances of fault detections. The condition monitoring system is able to execute a fault detection task around 164 ms, to recognize accurately fault frequencies of stator shorted turn for about 75%, broken rotor bar around 95%, eccentricity 65%, mechanical misalignment 85%, including supply voltage unbalances 100%. The condition monitoring system based on its performance assessments could become a suitable alternative not only for rotating machines but also condition monitoring for other nuclear reactor components. (author)

Real Time In-circuit Condition Monitoring of MOSFET in Power Converters

Directory of Open Access Journals (Sweden)

Shakeb A. Khan

2015-03-01

Full Text Available Abstract:This paper presents simple and low-cost, real time in-circuit condition monitoring of MOSFET in power electronic converters. Design metrics requirements like low cost, small size, high power factor, low percentage of total harmonic distortion etc. requires the power electronic systems to operate at high frequencies and at high power density. Failures of power converters are attributed largely by aging of power MOSFETs at high switching frequencies. Therefore, real time in-circuit prognostic of MOSFET needs to be done before their selection for power system design. Accelerated aging tests are performed in different circuits to determine the wear out failure of critical components based on their parametric degradation. In this paper, the simple and low-cost test beds are designed for real time in-circuit prognostics of power MOSFETs. The proposed condition monitoring scheme helps in estimating the condition of MOSFETs at their maximum rated operating condition and will aid the system designers to test their reliability and benchmark them before selecting in power converters.

SIM2PeD– Intelligent monitoring system for prevention of diabetic foot

African Journals Online (AJOL)

Tuoyo Aghomotsegin

2016-10-12

Oct 12, 2016 ... integrated with a mobile device to capture individuals' data, entitled Mobile ... Key words: Intelligent module, diabetes, application, diabetic foot. ..... treatment of 575 diabetic foot ulcers at home, Ph.D. thesis, University.

The Relationship between the Wechsler Intelligence Scale for Children-Revised and the Wechsler Intelligence Scale for Children-III Scales and Subtests for Gifted Children.

Science.gov (United States)

Sabatino, David A.; And Others

1995-01-01

This study determines the comparability of the Wechsler Intelligence Scale for Children-Revised and the Wechsler Intelligence Scale for Children-III in relation to gifted children. Results indicate that both tests produce remarkably similar scale and subtest scores when administered under clinical conditions. (JPS)

From Smart to Intelligent Sensors: A Case Study

Directory of Open Access Journals (Sweden)

Vincenzo Di Lecce

2012-03-01

Full Text Available This paper showcases the opportunity of embedding intelligence in smart sensor devices with particular reference to air quality monitoring applications. The work bases upon recent findings attained and published by authors in the field of information extraction from measurements signals and smart sensor research. Smart sensors are commonly conceived as hardware/software transducers able to lift the source physical signal(s to the application target level. This entails an intricate twist of physical measurements and application-level bits of information. When measures are noisy or ambiguous, information extraction is demanding and thus requires artificial intelligence to intervene in the data interpretation process. Experience gained with handcrafted prototypes allowed us to harness the complexity of bringing artificial intelligence inside physical measurements. To provide a complete picture of the encountered criticalities, the chosen semantic model, the carried out and the obtained results are reported and discussed.

Intelligent, net or wireless enabled fluorosensors for high throughput monitoring of assorted crops

International Nuclear Information System (INIS)

Barócsi, Attila

2013-01-01

Phenotypic characterization of assorted crops of different genotypes requires large data sets of diverse types for statistical reliability. Temporal monitoring of plant fluorescence is able to capture the dynamics of the photosynthesis process that is summarized in a number of parameters for which the genotypic heritability can be calculated. In this paper, an intelligent sensor system is presented that is capable of high-throughput production of baseline-corrected temporal fluorescence curves with many feature points. These are obtained by integrating several (direct and modulated) measurement methods applied at different wavelengths. Simultaneously, temporal change of the sample's emission and the ambient reference temperatures are recorded. Multiple sensors can be deployed easily in large span greenhouse environments with centralized data collection over wired or wireless infrastructure. The unique features of the sensors are a compact, embedded signal guiding fibre optic system, instrument-standard variable tubular detector and source modules, net or wireless enabling for remote control and fast, quasi real-time data collection. Along with the instrumentation, some representative phenotyping data are also presented that were taken on a subset of pepper recombinant inbred line population. It is also demonstrated that transient fluorescence feature points yield high heritability, offering a high confidence level for distinguishing the pepper genotypes. (paper)

Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

Science.gov (United States)

Rash, James L. (Editor)

1990-01-01

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Research on Land Ecological Condition Investigation and Monitoring Technology

Science.gov (United States)

Lv, Chunyan; Guo, Xudong; Chen, Yuqi

2017-04-01

The ecological status of land reflects the relationship between land use and environmental factors. At present, land ecological situation in China is worrying. According to the second national land survey data, there are about 149 million acres of arable land located in forests and grasslands area in Northeast and Northwest of China, Within the limits of the highest flood level, at steep slope above 25 degrees; about 50 million acres of arable land has been in heavy pollution; grassland degradation is still serious. Protected natural forests accounted for only 6% of the land area, and forest quality is low. Overall, the ecological problem has been eased, but the local ecological destruction intensified, natural ecosystem in degradation. It is urgent to find out the situation of land ecology in the whole country and key regions as soon as possible. The government attaches great importance to ecological environment investigation and monitoring. Various industries and departments from different angles carry out related work, most of it about a single ecological problem, the lack of a comprehensive surveying and assessment of land ecological status of the region. This paper established the monitoring index system of land ecological condition, including Land use type area and distribution, quality of cultivated land, vegetation status and ecological service, arable land potential and risk, a total of 21 indicators. Based on the second national land use survey data, annual land use change data and high resolution remote sensing data, using the methods of sample monitoring, field investigation and statistical analysis to obtain the information of each index, this paper established the land ecological condition investigation and monitoring technology and method system. It has been improved, through the application to Beijing-Tianjin-Hebei Urban Agglomeration, the northern agro-pastoral ecological fragile zone, and 6 counties (cities).

Life cycle management. Condition monitoring of wind power plants; Life-cycle-management. Zustandsueberwachung von Windenergieanlagen

Energy Technology Data Exchange (ETDEWEB)

Wolff, R. [cmc GmbH, Kiel (Germany)

2013-06-01

The author of the contribution under consideration reports on maintenance strategies and condition monitoring in the field of wind energy. Beside the components in the drive train of wind turbines under consideration, the condition monitoring of the hardware systems and their software is explained. A brief overview of the field of machinery diagnosis and an explanation of the transmission of the measured data follow. Additional sensors such as sensors for the rotor blade monitoring, oil particles counter or oil quality sensors are described. In the field of diagnostic certainty, special follow-up studies such as video endoscopy, analysis of oil or grease, filter testing and material testing are discussed. The information from these thematic fields is used in the life-cycle management database for operationally relevant evaluations and considerations of economy of condition monitoring systems.

Influence factor analysis of atmospheric electric field monitoring near ground under different weather conditions

International Nuclear Information System (INIS)

Wan, Haojiang; Wei, Guanghui; Cui, Yaozhong; Chen, Yazhou

2013-01-01

Monitoring of atmospheric electric field near ground plays a critical role in atmospheric environment detecting and lightning warning. Different environmental conditions (e.g. buildings, plants, weather, etc.) have different influences on the data's coherence in an atmospheric electric field detection network. In order to study the main influence factors of atmospheric electric field monitoring under different weather conditions, with the combination of theoretical analysis and experiments, the electric field monitoring data on the ground and on the top of a building are compared in fair weather and thunderstorm weather respectively in this paper. The results show that: In fair weather, the field distortion due to the buildings is the main influence factor on the electric field monitoring. In thunderstorm weather, the corona ions produced from the ground, besides the field distortion due to the buildings, can also influence the electric field monitoring results.

Web Intelligence and Artificial Intelligence in Education

Science.gov (United States)

Devedzic, Vladan

2004-01-01

This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

Intelligible Artificial Intelligence

OpenAIRE

Weld, Daniel S.; Bansal, Gagan

2018-01-01

Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

PROBLEMS OF CREATION THE MONITORING SYSTEM CONCERNING THE CONDITION OF INFORMATIZATION OF THE GENERAL EDUCATION INSTITUTIONS

Directory of Open Access Journals (Sweden)

Valeriy Yu. Bykov

2010-08-01

Full Text Available In the article the problems, which appear under the creation of monitoring systems concerning the condition of informatization of general educational institutions, such as definition of monitoring object and list of parameters that will be traced during the monitoring, technologies of obtaining and actualization of data parameters, that are to be monitored, formats of data submission and ways of its processing, monitoring time period etc. are considered. In the article some decision of these problems are offered. Here is also mentioned the data of some characteristics and possibilities of the creation of monitoring systems concerning the condition of informatization of general educational institutions in Ukraine.

Naturalist Intelligence Among the Other Multiple Intelligences [In Bulgarian

Directory of Open Access Journals (Sweden)

R. Genkov

2007-09-01

Full Text Available The theory of multiple intelligences was presented by Gardner in 1983. The theory was revised later (1999 and among the other intelligences a naturalist intelligence was added. The criteria for distinguishing of the different types of intelligences are considered. While Gardner restricted the analysis of the naturalist intelligence with examples from the living nature only, the present paper considered this problem on wider background including objects and persons of the natural sciences.

TO THE PROBLEM OF CORRELATION OF SOCIAL AND OTHER KINDS OF INTELLIGENCE

OpenAIRE

E. V. Grib

2017-01-01

The article considers the problem of the relationship of three types of intelligence: social, emotional and logical. Interest in social intelligence (SI) is determined by the need of society to reveal the "social capacity" of a person and develop them. Social intelligence is seen as a necessary condition for successful mastering of professional skills and adapt in a professional environment. Development of social intelligence becomes an important part of the educational process. Social intell...

Intelligent monitoring system for real-time geologic CO2 storage, optimization and reservoir managemen

Science.gov (United States)