Academic literature on the topic 'Real-Time Fault Detection'

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Journal articles on the topic "Real-Time Fault Detection"

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Leite, Denis, Aldonso Martins, Diego Rativa, Joao F. L. De Oliveira, and Alexandre M. A. Maciel. "An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis." Sensors 22, no. 16 (August 17, 2022): 6138. http://dx.doi.org/10.3390/s22166138.

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This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach’s particular characteristics are: it uses only data that are commonly available in industrial automation systems; it automates all ML processes without human intervention; a non-ML expert can deploy it; and it considers the behavior of cyclic sequential machines, combining discrete timed events and continuous variables as features. The capacity for fault detection is analyzed in two case studies, using data from a 3D machine simulation system with faulty and non-faulty conditions. The enhancement of the RT-FDD performance when the proposed approach is applied is proved with the Feature Importance, Confusion Matrix, and F1 Score analysis, reaching mean values of 85% and 100% in each case study. Finally, considering that faults are rare events, the sensitivity of the models to the number of faulty samples is analyzed.
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Sanchez, Oscar D., Gabriel Martinez-Soltero, Jesus G. Alvarez, and Alma Y. Alanis. "Real-Time Neural Classifiers for Sensor and Actuator Faults in Three-Phase Induction Motors." Machines 10, no. 12 (December 10, 2022): 1198. http://dx.doi.org/10.3390/machines10121198.

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The main steps involved in a fault-tolerant control (FTC) scheme are the detection of failures, isolation and reconfiguration of control. Fault detection and isolation (FDI) is a topic of interest due to its importance for the controller, since it provides the necessary information to adjust and mitigate the effects of the fault. Generally, the most common failures occur in the actuator or in sensors, so this article proposes a novel model-free scheme for the detection and isolation of sensor and actuator faults of induction motors (IM). The proposed methodology performs the task of detecting and isolating faults over data streams just after the occurrence of the failure of an induction motor (IM), by the occurrence of either disconnection, degradation, failure, or connection damage. Our approach proposes deep neural networks that do not need a nominal model or generate residuals for fault detection, which makes it a useful tool. In addition, the fault-isolation approach is carried out by classifiers that differentiate characteristics independently of the other classifiers. The long short-term memory (LSTM) neural network, bidirectional LSTM, multilayer perceptron and convolutional neural network are used for this task. The proposed sensors’ and actuator’s fault detection and isolation scheme is simple. It can be applied to various problems involving fault detection and isolation schemes. The results show that deep neural networks are a powerful and versatile tool for fault detection and isolation over data streams.
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CHAKKOR, Saad, Mostafa BAGHOURI, and Abderrahmane HAJRAOUI. "INTELLIGENT FAULT DETECTION DEVICE FOR WIND TURBINE IN REAL TIME CONDITION MONITORING." Acta Electrotechnica et Informatica 15, no. 1 (March 1, 2015): 34–41. http://dx.doi.org/10.15546/aeei-2015-0006.

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Abassi, Moez, Omar Khlaief, Oussama Saadaoui, Abdelkader Chaari, and Mohamed Boussak. "Real-time implementation of discrete Fourier transform phase analysis and fault tolerant control for PMSM in electric vehicles." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, no. 1 (January 2, 2018): 432–47. http://dx.doi.org/10.1108/compel-02-2017-0052.

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Purpose Electric vehicles (EVs) require uninterrupted and safe conditions during operations. Therefore, the diagnostic of power devices and electric motor faults are needed to improve the availability of the system. Hence, fault-tolerant control (FTC), which combines switch fault detection, hardware redundancy and post-fault control, is used. This paper aims to propose an accurate open-phase fault detection and FTC of a direct torque control permanent magnet synchronous motor electrical vehicles by using discrete Fourier-transform phase method. Design/methodology/approach The main idea is to propose detection and identification of open-phase fault (faulty leg) among three phases voltage source invertor (VSI)-fed permanent magnet synchronous motor drives. Once the faulty leg is detected and isolated, a redundant phase leg insertion, shared by a three-phase VSI, is done by using independent bidirectional TRIAC switches to conduct FTC system. This accurate fault detection significantly improves system availability and reliability. The proposed method of open-phase fault detection and identification is based only on stator phase current measurement. Findings A novel method is proposed with experimental validation for fault detection, isolation and FTC for a three-phase VSI-fed permanent magnet synchronous motor. Originality/value The novel discrete Fourier-transform phase method is proposed to detect an open phase based on the measurement in real time of the instantaneous phase of stator current components in the stationary frame. The experimental implementation is carried out on powerful dSpace DS1104 controller board based on the digital signal processor TMS320F240. The validity of the proposed method has been experimentally verified.
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Zhang, Chuang, Xiubin Zhao, Chunlei Pang, Liang Zhang, and Bo Feng. "The Influence of Satellite Configuration and Fault Duration Time on the Performance of Fault Detection in GNSS/INS Integration." Sensors 19, no. 9 (May 9, 2019): 2147. http://dx.doi.org/10.3390/s19092147.

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For the integration of global navigation satellite system (GNSS) and inertial navigation system (INS), real-time and accurate fault detection is essential to enhance the reliability and precision of the system. Among the existing methods, the residual chi-square detection is still widely used due to its good real-time performance and sensibility of fault detection. However, further investigation on the performance of fault detection for different observational conditions and fault models is still required. In this paper, the principle of chi-square detection based on the predicted residual and least-squares residual is analyzed and the equivalence between them is deduced. Then, choosing the chi-square detection based on the predicted residual as the research object, the influence of satellite configuration and fault duration time on the performance of fault detection is analyzed in theory. The influence of satellite configuration is analyzed from the number and geometry of visible satellites. Several numerical simulations are conducted to verify the theoretical analysis. The results show that, for a single-epoch fault, the location of faulty measurement and the geometry have little effect on the performance of fault detection, while the number of visible satellites has greater influence on the fault detection performance than the geometry. For a continuous fault, the fault detection performance will decrease with the increase of fault duration time when the value of the fault is near the minimal detectable bias (MDB), and faults occurring on different satellite’s measurement will result in different detection results.
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Wang, Haitao. "Application of Residual-Based EWMA Control Charts for Detecting Faults in Variable-Air-Volume Air Handling Unit System." Journal of Control Science and Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/1467823.

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An online robust fault detection method is presented in this paper for VAV air handling unit and its implementation. Residual-based EWMA control chart is used to monitor the control processes of air handling unit and detect faults of air handling unit. In order to provide a level of robustness with respect to modeling errors, control limits are determined by incorporating time series model uncertainty in EWMA control chart. The fault detection method proposed was tested and validated using real time data collected from real VAV air-conditioning systems involving multiple artificial faults. The results of validation show residual-based EWMA control chart with designing control limits can improve the accuracy of fault detection through eliminating the negative effects of dynamic characteristics, serial correlation, normal transient changes of system, and time series modeling errors. The robust fault detection method proposed can provide an effective tool for detecting the faults of air handling units.
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Ali, Mohamed Hassan, Abdelhamid Rabhi, Ahmed El Hajjaji, and Giuseppe M. Tina. "Real Time Fault Detection in Photovoltaic Systems." Energy Procedia 111 (March 2017): 914–23. http://dx.doi.org/10.1016/j.egypro.2017.03.254.

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Wang, Jie, and Jiwei Liu. "Fault-Tolerant Strategy for Real-Time System Based on Evolvable Hardware." Journal of Circuits, Systems and Computers 26, no. 07 (March 17, 2017): 1750111. http://dx.doi.org/10.1142/s0218126617501110.

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The evolvable hardware (EHW) is widely used in the design of fault-tolerant system. Fault-tolerant system is really a real-time system, and the recovery time is necessary in fault detection and recovery. However, when applying EHW, real-time characteristic is usually ignored. In this paper, a fault-tolerant strategy based on EHW is proposed. The recovery time, predicted by the fault tree analysis (FTA), is considered as a constraint condition. A configuration library is set up in the design phase to accelerate the repair process of the anticipated faults. An evolvable algorithm (EA) based on similarity is applied to evolve the repair circuit for the unanticipated faults. When the library reaches the upper, the target system is reconfigured by the EA-repair technology. Extensive experiments are conducted to show that our method can improve the fault-tolerance of the system while satisfying the real-time requirement on FPGA platform. In a long run system, our method can keep a higher fault recovery rate.
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El Merraoui, Khadidja, Abdellaziz Ferdjouni, and M’hamed Bounekhla. "Real time observer-based stator fault diagnosis for IM." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (February 1, 2020): 210. http://dx.doi.org/10.11591/ijece.v10i1.pp210-222.

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This paper proposes a delta connected IM model that takes the Stator winding Inter-Turn Short Circuit (SITSC) fault into account. In order to detect the fault and evaluate its severity, an observer based FDI method is suggested. It allows the generation of residual using extended Kalman filter (EKF). To overcome the problem of the EKF initialization, the cyclic optimization method is applied to determine its tuning parameters. The advantage of the proposed approach is the real-time quantification of the fault severity and the quick fault detection. Using numerical simulation under both the healthy and the faulty conditions, the proposed IM model and EKF-based FDI approach are confirmed. Experimental results obtained by a real-time implementation on test-bench validate the simulated results.
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Zhang, Chuang, Xiubin Zhao, Chunlei Pang, Yong Wang, Liang Zhang, and Bo Feng. "Improved Fault Detection Method Based on Robust Estimation and Sliding Window Test for INS/GNSS Integration." Journal of Navigation 73, no. 4 (February 28, 2020): 776–96. http://dx.doi.org/10.1017/s0373463319000778.

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Real-time and accurate fault detection and isolation is very important to ensure the reliability and precision of integrated inertial navigation and global navigation satellite systems. In this paper, the detection performance of a residual chi-square method is analysed, and on this basis an improved method of fault detection is proposed. The local test based on a standardised residual is introduced to detect and identify faulty measurements directly. Differing from the traditional method, two appropriate thresholds are selected to calculate the weight factor of each measurement, and the gain matrix is adjusted adaptively to reduce the influence of the undetected faulty measurement. The sliding window test, which uses past measurements, is also added to further improve the fault detection performance for small faults when the local test based on current measurements cannot judge whether a fault has occurred or not. Several simulations are conducted to evaluate the proposed method. The results show that the improved method has better fault detection performance than the traditional detection method, especially for small faults, and can improve the reliability and precision of the navigation system effectively.
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Dissertations / Theses on the topic "Real-Time Fault Detection"

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Marrison, N. A. "Real time fault detection and diagnosis in dynamic engineering systems using constraint analysis." Thesis, University of Glasgow, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309807.

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CHAO, YUE. "Fault Detection and Diagnosis of Electro-Mechanical Systems Based on Real-time Data." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1215092937.

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Kane, Thomas John S. M. Massachusetts Institute of Technology. "The NILM Dashboard : watchstanding and real-time fault detection using Non-intrusive Load Monitoring." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122320.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019
Thesis: S.M. in Naval Architecture and Marine Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 119-122).
Non-intrusive Load Monitoring (NILM) measures power at a central point in an electrical network and disaggregates individual load schedules from the overall power stream. This thesis presents the NILM Dashboard, a data-analysis and user interface tool that provides real-time machinery monitoring and fault diagnostics using NILM data. The Dashboard was developed and deployed for use onboard US Coast Guard Cutters to act as an automatic watchstander and condition-based maintenance aid. The effectiveness of the system is demonstrated on power data collected from electrical panels in the ship's engine room. Case studies are used to evaluate the Dashboard's ability to detect fault conditions in electromechanical systems.
by Thomas John Kane.
S.M.
S.M. in Naval Architecture and Marine Engineering
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
S.M.inNavalArchitectureandMarineEngineering Massachusetts Institute of Technology, Department of Mechanical Engineering
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Djuric, Natasa. "Real-time supervision of building HVAC system performance." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Engineering Science and Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-2215.

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This thesis presents techniques for improving building HVAC system performance in existing buildings generated using simulation-based tools and real data. Therefore, one of the aims has been to research the needs and possibilities to assess and improve building HVAC system performance. In addition, this thesis aims at an advanced utilization of building energy management system (BEMS) and the provision of useful information to building operators using simulation tools.

Buildings are becoming more complex systems with many elements, while BEMS provide many data about the building systems. There are, however, many faults and issues in building performance, but there are legislative and cost-benefit forces induced by energy savings. Therefore, both BEMS and the computer-based tools have to be utilized more efficiently to improve building performance.

The thesis consists of four main parts that can be read separately. The first part explains the term commissioning and the commissioning tool work principal based on literature reviews. The second part presents practical experiences and issues introduced through the work on this study. The third part deals with the computer-based tools application in design and operation. This part is divided into two chapters. The first deals with improvement in the design, and the second deals with the improvement in the control strategies. The last part of the thesis gives several rules for fault diagnosis developed using simulation tools. In addition, this part aims at the practical explanation of the faults in the building HVAC systems.

The practical background for the thesis was obtained though two surveys. The first survey was carried out with the aim to find the commissioning targets in Norwegian building facilities. In that way, an overview of the most typical buildings, HVAC equipment, and their related problems was obtained. An on-site survey was carried out on an example building, which was beneficial for introducing the building maintenance structure and the real hydronic heating system faults.

Coupled simulation and optimization programs (EnergyPlus and GenOpt) were utilized for improving the building performances. These tools were used for improving the design and the control strategies in the HVAC systems. Buildings with a hydronic heating system were analyzed for the purpose of improving the design. Since there are issues in using the optimization tool, GenOpt, a few procedures for different practical problems have been suggested. The optimization results show that the choice of the optimization functions influences significantly the design parameters for the hydronic heating system.

Since building construction and equipment characteristics are changing over time, there is a need to find new control strategies which can meet the actual building demand. This problem has been also elaborated on by using EnergyPlus and GenOpt. The control strategies in two different HVAC systems were analyzed, including the hydronic heating system and the ventilation system with the recovery wheel. The developed approach for the strategy optimization includes: involving the optimization variables and the objective function and developing information flow for handling the optimization process.

The real data obtained from BEMS and the additional measurements have been utilized to explain faults in the hydronic heating system. To couple real data and the simple heat balance model, the procedure for the model calibration by use of an optimization algorithm has been developed. Using this model, three operating faults in the hydronic heating system have been elaborated.

Using the simulation tools EnergyPlus and TRNSYS, several fault detection and diagnosis (FDD) rules have been generated. The FDD rules were established in three steps: testing different faults, calculating the performance indices (PI), and classifying the observed PIs. These rules have been established for the air cooling system and the hydronic heating system. The rules can diagnose the control and the component faults. Finally, analyzing the causes and the effects of the tested faults, useful information for the building maintenance has been descriptively explained.

The most important conclusions are related to a practical connection of the real data and simulation-based tools. For a complete understanding of system faults, it is necessary to provide real-life information. Even though BEMS provides many building data, it was proven that BEMS is not completely utilized. Therefore, the control strategies can always be improved and tuned to the actual building demands using the simulation and optimization tools. It was proven that many different FDD rules for HVAC systems can be generated using the simulation tools. Therefore, these FDD rules can be used as manual instructions for the building operators or as a framework for the automated FDD algorithms.


Denne avhandlingen presenterer noen fremgangsmåter for forbedring av ytelser for VVS-tekniske anlegg i eksisterende bygninger basert på bruk av simuleringsverktøy og virkelige måledata. Ett av målene har vært å undersøke behov og muligheter for vurdering og forbedring av ytelser for VVS-anlegg i bygninger. I tillegg har denne avhandlingen hatt som mål å fremme bruk av SD-anlegg samt å fremskaffe nyttig informasjon til driftspersonalet.

Bygninger blir stadig mer kompliserte systemer som inneholder flere og flere komponenter mens SD-anlegg håndterer en stadig større mengde data fra bygningsinstallasjoner. På den ene siden registreres det ofte feil og problemer med hensyn til ytelsene til de VVS-tekniske installasjonene. På den andre siden innføres det stadig strengere lovmessige pålegg og kost-nyttekrav motivert i energieffektiviseringen. SD-anlegg og databaserte verktøy bør derfor brukes mer effektivt for forbedring av ytelsene.

Avhandlingen består av fire hoveddeler hvor hver del kan leses separat. Den første delen, som er basert på literatturstudie, forklarer funksjonskontroll som begrep og prinsipper for oppbygging av verktøy for funksjonskontroll. Den andre delen presenterer praktisk erfaring og problemstillinger utviklet og behandlet i løpet av arbeidet med avhandlingen. Den tredje delen handler om anvendelse av databaserte verktøy for forbedring av ytelsen for VVS-tekniske installasjoner. Den tredje delen er delt opp i to kapitler, hvorav et handler om forbedring av systemløsninger og et om forbedring av styringsstrategier. Den siste delen presenterer flere regler for feilsøking og diagnostisering utviklet gjennom bruk av simuleringsverktøy. I tillegg gir denne delen en praktisk forklaring av feilene i de VVS-anleggene som er behandlet i undersøkelsen.

Det praktiske grunnlaget for avhandlingen er etablert gjennom to undersøkelser. Den første var en spørreundersøkelse som hadde til hensikt å kartlegge målsetninger for funksjonskontroll i norske bygninger. Gjennom dette ble det etablert en oversikt over de mest typiske bygninger med tilhørende VVS-anlegg og de mest forekommende problemene. En dypere undersøkelse ble utført på ett casebygg. Denne undersøkelsen viste seg å være nyttig både for kartlegging av betydningen av organisering av driften av bygningen og for avdekking av de virkelige feilene i det vannbårne oppvarmingssystemet.

En kobling mellom et simulerings- og et optimaliseringsprogram (EnergyPlus og GenOpt) har vært benyttet for forbedring av ytelsene for de VVS-tekniske installasjonene. Disse verktøyene har vært brukt for forbedring av både systemløsningene og styringsstrategiene for VVS-anlegg. Bygninger med vannbåren oppvarmingssystem har vært analysert for å forbedre systemløsningen. På grunn av begrensninger i bruken av optimaliseringsverktøyet GenOpt, har det blitt utviklet egne prosedyrer for håndtering av visse typer problemstillinger hvor denne begrensningen opptrer. Resultatene for optimaliseringen viser at valg av objektfunksjoner påvirker betydelig parametrene i det vannbårne oppvarmingssystemet.

Endringer i egenskapene til både bygningskonstruksjoner og utstyr som skjer på grunn av aldring over tiden, gjør det nødvendig med tilpassning av styringsstrategier slik at det virkelige behovet kan bli dekket. Denne problemstillingen har vært analysert ved bruk av EnergyPlus og GenOpt. Styringsstrategiene for to forskjellige VVS-anlegg, et vannbåret oppvarmingssystem og et ventilasjonsanlegg med varmegjenvinner har blitt behandlet. Den utviklete prosedyren for optimalisering av styringsstrategien består av følgende steg: innføring av optimaliseringsvariabler og objektfunksjon, samt utvikling av informasjonsflyt for behandling av optimaliseringsprosessen.

De virkelige data, både fra SD-anlegg og tilleggsmålinger, har vært benyttet for praktisk forklaring av feilene i oppvarmingssystemet. En prosedyre for modellkalibrering basert på bruk av en optimaliseringsalgoritme som kobler sammen de virkelige data og en enkel varmebalansemodell har blitt foreslått. Tre konkrete driftsfeil i oppvarmingssystemet har blitt belyst gjennom bruk av denne varmebalansemodellen.

Flere regler for feilsøking og diagnostisering har blitt utviklet ved hjelp av simuleringsverktøyene EnergyPlus and TRNSYS. Denne utviklingen har bestått av tre ulike steg: testing av bestemte feil, beregning av ytelsesindikatorer og til slutt klassifisering av de observerte ytelsesindikatorer. Reglene har blitt utviklet for et system av aggregater for luftkjøling og for et vannbåret oppvarmingssystem. Reglene kan diagnostisere både styringsfeil og komponentfeil. Til slutt presenteres informasjon som er nyttig for drift av VVS-tekniske installasjoner i bygninger basert på en analyse av årsakene for og virkningene av de feil som er behandlet.

De viktigste konklusjonene er knyttet til praktisk kombinasjon av virkelige måleverdier og simuleringsverktøy. Informasjon fra det virkelig liv er helt nødvendig for å få en god forståelse av feil som oppstår i anlegg. Det er også vist at potensialet som ligger i alle de data som er tilgjengelige gjennom SD-anlegg, ikke er fullt utnyttet. Gjennom bruk av simuleringsverktøy kan styringsstrategiene alltid bli bedre tilpasset og innjustert til de virkelige behov i bygningen. Simuleringsverktøy kan også brukes for utvikling av prosedyrer for feilsøking og diagnostisering i VVS-tekniske anlegg. Disse prosedyrene kan brukes enten som en veileder for manuell feilsøking og detektering eller som grunnlag for utvikling av automatiserte algoritmer.


Paper II, VI and VII are reprinted with kind permission from Elsevier, sciencedirect.com
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Farfan-Ramos, Luis. "Real-time Fault Diagnosis of Automotive Electrical Power Generation and Storage System." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1303129393.

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Capitanu, Calin. "Fault Detection, Isolation and Recovery : Analysis of two scheduling algorithms." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300128.

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Unmanned, as well as manned space missions have seen a high failure rate in the early era of space technology. However, this decreased a lot since technology advanced and engineers learnt from previous experiences and improved critical real time systems with fault detection mechanisms. Fault detection, isolation and recovery, nowadays, is generally available in every flying device. However, the cost of hardware can bottleneck the process of creating such a system that is both robust and responsive. This thesis analyses the possibility of implementing a fault detection, isolation and recovery system inside of a single-threaded, cooperative scheduling operating system. The thesis suggests a cooperative implementation of such a system, where every task is responsible for parts of the fault detection. The analysis is done from both the integration layer, across the operating system and its tasks, as well as from the inside of the detection system, where two key components are implemented and analyzed: debug telemetry and operation modes. Results show that it is possible to implement a fault detection system that is spread across all the components of the satellite and acts cooperatively. Furthermore, the comparison with a traditional, dedicated fault detection system proves that errors can be caught faster with a cooperative mechanism.
Obemannade såväl som bemannade rymduppdrag har sett ett högt misslyckande i rymdteknikens tidiga era. Detta har dock förbättrats mycket sedan ingenjörer började lära sig av sina tidigare erfarenheter och utrustade kritiska realtidssystem med feldetekteringsmekanismer. Idag är alla flygande enheter utrustade med feldetekterings-, isolerings- och återställningsmekanismer. Däremot kan kostnaden för hårdvara vara ett problem för processen att skapa ett sådant system som är både robust och mottagligt. Denna uppsats analyserar möjligheten att implementera ett feldetekterings-, isolerings- och återställningssystem inuti ett enkelgängat samarbetsplaneringssystem. Denna uppsats föreslår ett samarbete för implementering av ett sådant system, där varje uppgift ansvarar för delar av feldetekteringen. Analysen görs från både integrationsskiktet, över operativsystemet och dess uppgifter, samt från insidan av detekteringssystemet, där två nyckelkomponenter implementeras och analyseras. Resultaten visar att det är möjligt att implementera ett feldetekteringssystem som täcker alla satellitkomponenter och som är mottaglig. Dessutom visar jämförelsen med ett traditionellt, dedikerat feldetekteringssystem att fel kan fångas snabbare med en mottagligmekanism.
Misiunile spat,iale cu oameni, atât cât s, i fara oameni, au avut o rata a es, ecurilor destul de ridicata în perioada init,iala a erei tehnologiei spat,iale. În schimb, aceasta a scazut semnificativ odata cu dezvoltarea tehnologiei, dar s, i datorita faptului ca inginerii au învat,at din experient,ele precendente s, i au îmbunatat, it sistemele critice în timp real cu mecanisme de detect,ie a erorilor. Sisteme de detect,ie, izolare s, i recuperare din erori sunt disponibile astazi în aproape toate sistemele spat,iale. Însa, costul echipamentelor poate împiedica crearea unor astfel de sisteme de detect,ie, care sa fie robuste s, i responsive. Aceasta teza analizeaza posibilitatea implementarii unui sistem de detect,ie, izolare s, i recuperare de la erori într-un satelit care este echipat cu un procesor cu un singur fir de execut,ie, care are un sistem de planificare cooperativ în sistemul de operare. Aceasta teza sugereaza o implementare cooperativa a unui astfel de sistem, unde fiecare proces este responsabil de câte o parte din detectarea erorilor. Analiza este realizata atât din perspectiva integrarii în sistemul de operare s, i procesele acestuia, cât s, i din interiorul acestui sistem de detect,ie, unde doua elemente importante sunt implementate s, i analizate: telemetria de depanare s, i modurile de operare. Rezultatele arata faptul ca este posibila implementarea unui sistem de detect,ie care este împart, it în toate componentele sistemului unui satelit s, i se comporta cooperativ. Mai departe, comparat,ia cu un sistem tradit,ional, dedicat, de detect,ie a erorilor arata ca erorile pot fi detectate mai rapid cu un sistem cooperativ.
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Singh, Bhanu Pratap. "Real-time detection of stator resistance unbalances in three phase drives." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286813.

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An estimated 30% of the faults in Induction Machine (IM) are related to its stator. These faults are mostly in the form of an Inter-Turn Short Circuit (ITSC) fault i.e., when two winding inside the stator of IM are shorted due to insulation failure. However, ITSC fault can be avoided by detecting them in advance and then scheduling the maintenance of the IM. This thesis studies two methods for detecting this incipient ITSC fault in a three-phase IM and then estimating the stator resistance unbalance due to the ITSC fault. The first method is based on the asymmetry caused in the IM by the ITSC fault. As a result of this asymmetry, the negative sequence components of the stator voltages and the stator currents are generated inside the IM. A healthy IM also have these negative sequence components due to the manufacturing process and the supply voltage unbalances. The characteristics and the compensation methods of these negative sequence components in a healthy IM are discussed. The results show that after compensating the negative sequence components in a healthy machine, they can be used for detecting an ITSC fault and then to calculate the fault quantities as well as the stator resistance unbalances. The second method for detecting an ITSC fault is based on analysing the stator resistance unbalances. A three-phase drive is used to inject DC voltage in the stationary reference frame. The DC current generated by this DC voltage is measured and then by applying Ohm’s law stator phase resistances are calculated. In a healthy IM, the phase resistances are balanced. However, in case of ITSC fault in any of the phases, the phase resistance of that phase deviates from those of the other two phases which can be utilized for detecting ITSC fault.
Uppskattningsvis 30% av alla fel i induktionsmaskiner (IM) är kopplad till dess stator. Dessa fel är i huvudsak Inter-Turn Short Circuit (ITSC)-fel, dvs. två lindningar inom IM:ens stator blir kortsluta pga. ett isoleringsfel. Emellertid kan man undvika ITSC-fel genom att detektera dem i förhand och planera underhåll. Det här examensarbetet undersöker två metoder för att detektera ett förestående ITSC-fel i en tre-fas IM. Den första metoden är baserad på asymmetrin i IM:er pga. ITSC-felet. Resultatet av den här asymmetrin är att en negativ sekvens genereras i IM:ens statorspänning och statorström. En oskadad IM kan också visa dessa negativa sekvenser pga. tillverksprocessen och statorspänningsobalanser. Egenskaperna och kompensationsmetoderna för dessa negativa sekvenser i en oskadad IM kommer att diskuteras. Resultaten visar att efter kompenseringen av de negativa sekvenserna i en oskadad IM, kan de användas för att detektera ITSC-fel och efteråt för att beräkna felstorheter och även statormotståndobalanser. Den andra metoden för att detektera ITSC-fel är baserad på en undersökning av statormotståndobalanser. Ett tre-fas-drivsystem används för att injektera likspänning i den stationära referensramen. Likströmmen som följer av denna likspänning mäts och statorfasmotstånden beräkna efteråt med Ohms lag. I en oskadad IM är fasmotstånden balanserade. Däremot, när ett ITSC-fel uppstår i en fas, avviker fasmotståndet i den felaktiga fasen från de andra två fasernas, vilket kan användas för att detektera ITSC-fel.
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Pasdar, Amir Mehdi. "Real-Time Health Monitoring of Power Networks Based on High Frequency Behavior." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1415873192.

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Chouichi, Aabir. "Real-time detection and control of machine/chamber mismatching in the semi- conductor industry." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEM001.

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Dans toutes les industries manufacturières, les chambres mises en parallèles sur une même opération de production sont censées donner un résultat similaire et offrir des produits de qualité identique. Ceci n'est toutefois pas toujours le cas dans les unités de production.Le maintien d'une performance stable des chambres parallèles dans l'industrie des semi-conducteurs est un véritable défi car les machines traitent simultanément un grand nombre de produits dans le but de maximiser le rendement et optimiser l'utilisation des machines. Le travail de thèse consiste à proposer une méthodologie permettant de détecter et de corriger en temps réel ces différences de performance en exploitant toutes les données disponibles, utilisées habituellement de façon séparée, pour identifier les causes racines de toute différence significative entre les chambres traitant des produits identiques.L'approche proposée consiste d'abord à détecter les écarts existants entre les chambres parallèles en se référant aux mesures des paramètres physiques. Les données des capteurs sont ensuite analysées pour mettre en évidence les indicateurs causant ces écarts. Ces indicateurs sont ajustés grâce à un mécanisme de contrôle efficace composé de deux parties : La métrologie virtuelle et la régulation. Tout d'abord, l'impact du réglage des paramètres d'entrée des chambres sur la qualité des produits est modélisé. Les modèles créés sont ensuite utilisés pour mettre en œuvre des boucles de régulation dont le but est de faire correspondre les indicateurs source de variabilité, et compenser ainsi l'erreur de sortie
In the manufacturing industries, the machines/chambers placed in parallel on the same production operation are expected to have similar capabilities and, most importantly, to yield identical product quality. However, this is usually not the case in real practice due to the systematic variations accumulated in time. Maintaining stable performance of parallel machines/chambers in the semiconductor industry is a critical challenge given the fact that, in the large-scale production environment, machines/chambers can process a large number of products simultaneously to maximize throughput and optimize machine utilization. Un- surprisingly, after processing very different settings, called recipes, the conditions of parallel machines/chambers will be no longer the same. This thesis proposes a methodology to detect and correct the performance differences in real-time by using all the available data, namely: measurements of physical parameters, data from sensors installed on machines, data from the control loops, and maintenance data. The core idea is to integrate the different sources of data, which are usually used separately, to identify the root causes of any significant differences among the machines/chambers that process identical recipes.The proposed approach starts by detecting existing gaps between parallel machines/ chambers by referring to the measurements of physical parameters since they reflect the quality of manufactured products. The sensor data are then analyzed to highlight the in- dicators that cause these discrepancies. These indicators are adjusted through an effective control mechanism composed of two parts: 1) virtual metrology and 2) process regulation. First, the impact of recipe changes on product quality is quantified by modeling the link between the inputs and outputs of the mismatched machines/chambers. The constructed models are then used to implement the revised control loops to match as much as possible the controllable input factors and compensate for the output errors
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García-Gutiérrez, Luis Antonio. "Développement d'un contrôle actif tolérant aux défaillances appliqué aux systèmes PV." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30071.

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Cette thèse de doctorat aborde la problématique de la réalisation d'un système de contrôle actif de détection de défaut et diagnosis (FDD) pour un système de conversion photovoltaïque. Ce type de système de production d'énergie électrique est composé de panneaux solaires, d'un dispositif MPPT, d'un convertisseur de courant DC-DC, d'un onduleur DC-AC et d'une charge. Le système de contrôle actif à tolérance de pannes qui a été développé dans cette thèse est composé de deux étages : * Un étage assurant la fonction de diagnostic et comprenant les fonctions de détection de défauts, la fonction d'isolement de défauts, l'identification de défauts et l'estimation de l'ampleur du/des défaut(s) * Une fonction de reconfiguration du système photovoltaïque. Ce manuscrit est divisé en quatre chapitres : * Introduction au problème et révision de l'état de la technique * Modélisation mathématique du système photovoltaïque avec une validation expérimental de ce dernier effectué sur la plateforme PV de caractérisation du bâtiment réel ADREAM (Laboratoire LAAS-CNRS) * Conception et mise en œuvre du système de diagnostic de pannes du système photovoltaïque comprenant un Système actif à tolérance de pannes * Un système de diagnostic expérimental en cours de développement à l'aide d'un dispositif FPGA
This work contributes by developing an active fault tolerant control (AFTC) for Photovoltaic (PV) systems. The fault detection and diagnosis (FDD) methodology is based on the analysis of a model that compares real-time measurement. We use a high granularity PV array model in the FDD tool to allow faults to be detected in complex conditions. Firstly, the research focuses on fault detection in complex shadow conditions. A real-time approach is presented to emulate the electrical characteristics of PV modules under complex shadow conditions. Using a precise emulators approach is a real challenge to study the high non-linearity and the complexity of PV systems in partial shading. The real-time emulation was validated with simple experimental results under failure conditions to design specific fault-detection algorithms in a first sample. The second part of the research addresses the FDD method for DC/DC and DC/AC power converters that are connected to the grid. Primary results allowed us to validate the system's recovery for normal operating points after a fault with this complete AFTC approach. Emulations based on the simulation of distributed power converters, fault detection methodologies based on a model, and a hybrid diagnostician were then presented
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Books on the topic "Real-Time Fault Detection"

1

M, Smith L., and United States. National Aeronautics and Space Administration., eds. Final report for grant titled: SSME propellant path leak detection real-time. [Washington, DC: National Aeronautics and Space Administration, 1994.

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John, Rushby, and Langley Research Center, eds. Model-based reconfiguration: Diagnosis and recovery. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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Crow, Judy. Model-based reconfiguration: Diagnosis and recovery. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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Litt, John. Sensor fault detection and diagnosis simulation of a helicopter engine in an intelligent control framework. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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Mehmet, Kurtkaya, Duyar Ahmet, United States. National Aeronautics and Space Administration., and U.S. Army Research Laboratory., eds. Sensor fault detection and diagnosis simulation of a helicopter engine in an intelligent control framework. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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United States. National Aeronautics and Space Administration., ed. OPAD-EDIFIS real-time processing: Final report, contract NAS8-38609 D.O. 177. [Washington, DC: National Aeronautics and Space Administration, 1997.

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United States. National Aeronautics and Space Administration., ed. OPAD-EDIFIS real-time processing: Final report, contract NAS8-38609 D.O. 177. [Washington, DC: National Aeronautics and Space Administration, 1997.

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United States. National Aeronautics and Space Administration., ed. OPAD-EDIFIS real-time processing: Final report, contract NAS8-38609 D.O. 177. [Washington, DC: National Aeronautics and Space Administration, 1997.

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Model-based reconfiguration: Diagnosis and recovery. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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OPAD-EDIFIS real-time processing: Final report, contract NAS8-38609 D.O. 177. [Washington, DC: National Aeronautics and Space Administration, 1997.

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Book chapters on the topic "Real-Time Fault Detection"

1

Pouliezos, A. D., and G. S. Stavrakakis. "Fault Detection and Diagnosis Methods in the Absence of Process Model." In Real Time Fault Monitoring of Industrial Processes, 1–92. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-015-8300-8_1.

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Guo, Ying, Josh Wall, Jiaming Li, and Sam West. "Real-Time HVAC Sensor Monitoring and Automatic Fault Detection System." In Sensors for Everyday Life, 39–54. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47322-2_3.

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Nair, Yedu C., Sachin Kumar, and K. P. Soman. "Real-Time Automotive Engine Fault Detection and Analysis Using BigData Platforms." In Advances in Intelligent Systems and Computing, 507–14. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3153-3_50.

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Arenella, Alessandro, Antonio Greco, Alessia Saggese, and Mario Vento. "Real Time Fault Detection in Photovoltaic Cells by Cameras on Drones." In Lecture Notes in Computer Science, 617–25. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59876-5_68.

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Ciampi, Anna, Annalisa Appice, Donato Malerba, and Angelo Muolo. "An Intelligent System for Real Time Fault Detection in PV Plants." In Sustainability in Energy and Buildings, 235–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27509-8_19.

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Ryu, Sang-Moon, and Dong-Jo Park. "Checkpointing for the Reliability of Real-Time Systems with On-Line Fault Detection." In Embedded and Ubiquitous Computing – EUC 2005, 194–202. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596356_22.

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Niharika and Lini Mathew. "Real Time Analysis of Artificial Neural Network-Based Fault Detection and Fault Location in the AC Microgrid." In Advances in Intelligent Systems and Computing, 325–41. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3590-9_25.

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Sahu, Sourav Kumar, and Debomita Ghosh. "Spectral Kurtosis-Based Fault Detection for a Highly Penetrated Distributed Generation: A Real-Time Analysis." In Advances in Smart Grid Automation and Industry 4.0, 649–56. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7675-1_65.

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Adhikari, Shuma, Subir Datta, Nidul Sinha, and Bappa Roy. "Detection and Classification of Fault in Transmission Line Using PAC Technology Based Real Time SCADA System." In Learning and Analytics in Intelligent Systems, 313–20. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42363-6_37.

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Thunem, Harald P. J., and Atoosa P. J. Thunem. "Fault Detection in Real-Time Software Systems using Neuro-Fuzzy Tools for Signal Validation and Diagnosis." In Probabilistic Safety Assessment and Management, 1858–63. London: Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-410-4_298.

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Conference papers on the topic "Real-Time Fault Detection"

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Torres, Melitsa J., Jose D. Posada, Jaime R. Garcia, and Marco E. Sanjuan. "Real-Time Fault Detection Application for Natural Gas Pipelines." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-88927.

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The implementation of fault detection techniques in industrial systems for process monitoring has proven to be a useful tool to process operators supervising the plant’s operation conditions. As plants become more instrumented, more data is available for fault detection applications, if they are capable of demonstrate anticipation and low false alarm rates. A regional Natural Gas transportation system deals with these types of drawbacks. While the improvements are carried out, some effort should be done in order to improve the safety in operations. In this paper a data-driven technique was used to detect fault conditions along the pipeline, sectioning it in five partitions to increase the detection sensibility. To overcome the lack of quality in data, simulation software intended to gas controllers training and pipeline operation was used to simulate leaks scenarios. Some historic data with high quality is also used to create normal operation condition models by means of Principal Component Analysis. All simulated faults were detected in a reduced time gap and recent events related to third-party actions showed the tool proficiency to detecting faults in real time. In addition, it considers a fault normalized index per section indicating the fault persistence and aggressiveness in a single plot.
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Mathias, Pia, Johann Laurent, Pierre Bomel, and Hugo Kerhascoet. "Real Time Heading Sensors Fusion and Fault Detection." In SNAME 24th Chesapeake Sailing Yacht Symposium. SNAME, 2022. http://dx.doi.org/10.5957/csys-2022-014.

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In modern offshore racing, performance often depends on two main factors: a good autopilot and the right strategy decisions taken by the skipper. Some sensors are crucial to ensure the quality of those two keys of success, among which we can mention the heading sensors. Unfortunately, those sensors, whether magnetometers or GNSS based, are subject to disturbances and faults of various origins: magnetic disturbances from other devices, GPS fix or reception issues, sensor drift, etc. These sensor faults can cause an autopilot’s solution to diverge which can result in serious damage to the boat or the crew. Assurance of a valid measurement is therefore a key point to ensure reliability of autopilot systems and skipper’s decisions. This paper presents a method to produce consistent values of true heading and yaw rate while detecting sensor faults. The proposed solution relies on the hypothesis that sensors using different technologies and placed in different spots inside the boat will not be subject to identical and synchronised disturbances. Thus, by intelligently fusing the information coming from several sources, a continuous and consistent true heading measure can be maintained. A simple dynamic model for the heading and yaw rate is implemented and an asynchronous filter update is done depending on available measures. The difference between the estimated and the measured states is used to determine whether a sensor is faulty or valid and the update is done consequently; then the information on sensors status and quality of the estimation can be propagated. In the paper, we detail a method to detect faults in heading sensors and to provide a substitution value if necessary. The proposed model is validated by test campaigns that were conducted using both data logs and on-board tests. Results show that we can improve and maintain true heading measurement quality and detect and isolate faulty sensors.
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He, Hongbo, David Menicucci, Thomas Caudell, and Andrea Mammoli. "Real-Time Fault Detection for Solar Hot Water Systems Using Adaptive Resonance Theory Neural Networks." In ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54885.

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The objective of this work is to design and test a real-time solar hot water (SHW) fault detection system that can reliably detect anticipated and unforeseen faults using only those sensors that are normally required to operate a system. The fault detection system includes a data acquisition module and a hierarchical Adaptive Resonance Theory (ART)-based neural network fault detection module. The data acquisition system logs the collector fin temperature and the water tank heat exchanger outlet temperature. The detection module uses a hierarchical ART neural network that can detect faults and classify them by level of severity. The hierarchical ART neural network is trained with information collected from a verified solar hot water system TRNSYS (Transient Systems Simulation program) model. The TRNSYS model uses weather data for Albuquerque, NM, extracted from the National Solar Radiation Data Base (NSRDB), for the 5-year period 2000–2004. The neural network is trained under different weather conditions. The simulation and experimental results show that the trained fault detection system has the capability to detect expected faults including pump faults, impeller degradation, thermosyphon and potential unexpected ones. Simulated and experimental test results are presented.
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Shalimov, A., and R. Smeliansky. "Program compaction for real-time applications." In Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics, edited by C. Vallet, D. Choukroun, C. Philippe, G. Balas, A. Nebylov, and O. Yanova. Les Ulis, France: EDP Sciences, 2013. http://dx.doi.org/10.1051/eucass/201306469.

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Mauclair, C., and G. Durrieu. "Analysis of real-time networks with monte carlo methods." In Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics, edited by C. Vallet, D. Choukroun, C. Philippe, G. Balas, A. Nebylov, and O. Yanova. Les Ulis, France: EDP Sciences, 2013. http://dx.doi.org/10.1051/eucass/201306501.

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Aydin, Ilhan, Mehmet Karakose, and Erhan Akin. "FPGA based real time fuzzy fault detection algorithm." In 2010 International Conference of Soft Computing and Pattern Recognition (SoCPaR). IEEE, 2010. http://dx.doi.org/10.1109/socpar.2010.5686535.

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Arias-Esquivel, Yeiner, Carlos Salazar-Garcia, and Jeferson Gonzalez-Gomez. "Real-time vibration analysis for structure fault detection." In 2016 IEEE 36th Central American and Panama Convention (CONCAPAN XXXVI). IEEE, 2016. http://dx.doi.org/10.1109/concapan.2016.7942358.

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Ju, Xiaoming, Jiehao Zhang, and Yizhong Zhang. "Real-Time BIST for Fault Detection in FPGA." In 2013 International Conference on Information Science and Technology Applications. Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/icista.2013.8.

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Boi-Ukeme, Joseph, Cristina Ruiz-Martin, and Gabriel Wainer. "Real-Time Fault Detection and Diagnosis of CPS Faults in DEVS." In 2020 IEEE 6th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application (DependSys). IEEE, 2020. http://dx.doi.org/10.1109/dependsys51298.2020.00017.

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Gupta, Sonal, Shweta Meena, and Vahiuddin Syed Khaja. "Real-Time Double Fault Tolerant Full Adder Design Using Fault Detection." In 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2018. http://dx.doi.org/10.1109/iccons.2018.8662961.

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Reports on the topic "Real-Time Fault Detection"

1

Jaw, Link, Karl Reichard, and Pattada Kallappa. Real Time Supervisors and Monitors for Performing Health Monitoring and Fault Detection for Systems Operating in Multiple Regimes. Fort Belvoir, VA: Defense Technical Information Center, February 2003. http://dx.doi.org/10.21236/ada411672.

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