Fault Detection and Diagnosis最新文献

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Fault Residuals Based on Distributed Discrete-Time Linear Kalman Filtering 基于分布离散时间线性卡尔曼滤波的故障残差
Fault Detection and Diagnosis Pub Date : 2018-11-05 DOI: 10.5772/INTECHOPEN.80296
D. Krokavec, A. Filasová
{"title":"Fault Residuals Based on Distributed Discrete-Time Linear Kalman Filtering","authors":"D. Krokavec, A. Filasová","doi":"10.5772/INTECHOPEN.80296","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.80296","url":null,"abstract":"The chapter is concerned with the application of distributed discrete-time linear Kalman filtering with decentralized structure of sensors in fault residual generation. Two variants of distributed Kalman filtering algorithms are introduced, giving the incidence of equiva- lent functional realization structure of fault residual filters. The obtained solutions use Kalman filter innovations in a nonstandard way to generate residuals with significantly higher dynamic signal range. The obtained results, offering structures for fault detection filter realization, are illustrated with a numerical example to note the effectiveness of the approach.","PeriodicalId":358379,"journal":{"name":"Fault Detection and Diagnosis","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128254696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fault Diagnosis of Hybrid Computing Systems Using Chaotic-Map Method 基于混沌映射方法的混合计算系统故障诊断
Fault Detection and Diagnosis Pub Date : 2018-11-05 DOI: 10.5772/INTECHOPEN.79978
N. Rao, B. Philip
{"title":"Fault Diagnosis of Hybrid Computing Systems Using Chaotic-Map Method","authors":"N. Rao, B. Philip","doi":"10.5772/INTECHOPEN.79978","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.79978","url":null,"abstract":"Computing systems are becoming increasingly complex with nodes consisting of a com- bination of multi-core central processing units (CPUs), many integrated core (MIC) and graphics processing unit (GPU) accelerators. These computing units and their intercon- nections are subject to different classes of hardware and software faults, which should be detected to support mitigation measures. We present the chaotic-map method that uses the exponential divergence and wide Fourier properties of the trajectories, combined with memory allocations and assignments to diagnose component-level faults in these hybrid computing systems. We propose lightweight codes that utilize highly parallel chaotic-map computations tailored to isolate faults in arithmetic units, memory elements and intercon- nects. The diagnosis module on a node utilizes pthreads to place chaotic-map threads on CPU and MIC cores, and CUDA C and OpenCL kernels on GPU blocks. We present experimental diagnosis results on five multi-core CPUs; one MIC; and, seven GPUs with typical diagnosis run-times under a minute.","PeriodicalId":358379,"journal":{"name":"Fault Detection and Diagnosis","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125720593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A Comparative Study on Some Fault Diagnosis Techniques in Three-Phase Inverter Fed Induction Motors 三相变频调速异步电动机几种故障诊断技术的比较研究
Fault Detection and Diagnosis Pub Date : 2018-11-05 DOI: 10.5772/INTECHOPEN.79960
Bilal Djamal Eddine Cherif, A. Bendiabdellah, MokhtarBendjebbar, Laribi Souad
{"title":"A Comparative Study on Some Fault Diagnosis Techniques in Three-Phase Inverter Fed Induction Motors","authors":"Bilal Djamal Eddine Cherif, A. Bendiabdellah, MokhtarBendjebbar, Laribi Souad","doi":"10.5772/INTECHOPEN.79960","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.79960","url":null,"abstract":"The growing importance of power conversion systems and their dependency on the performance and reliability of static converters has motivated extensive research efforts in this field. A variety of different techniques have been applied to detect open-circuit faults in power converters. The present chapter is focusing on the techniques of detection and localization of open-circuit faults in a three phase voltage source inverter fed induction motor. A comparative study is carried out between different detection techniques: the Park current vectors and its enhancement by using the polar coordinates, the mean value of the currents, the stator current spectrum analysis and the measurement of the current drop. The aim of this comparison is to investigate the relative strengths and weaknesses of the different techniques and evaluate the performance of each detection technique studied. The comparison study focuses on the time detection, the localization ability and the hardware aspect. To validate these techniques, an experimental setup is developed in our diagnostic group laboratory which consists of a two-level voltage source inverter controlled by a DSPACE-1104, Card to generate the PWM vector control of the induction motor. The obtained simulation and experimental results illustrate well the detection feasibility of each technique as well as the benefits and merits of the performed comparative study.","PeriodicalId":358379,"journal":{"name":"Fault Detection and Diagnosis","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128855334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model 基于统计模型的风力发电机组预防性维护与故障检测
Fault Detection and Diagnosis Pub Date : 2018-11-05 DOI: 10.5772/INTECHOPEN.80071
I. Kuiler, M. Adonis, A. Raji
{"title":"Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model","authors":"I. Kuiler, M. Adonis, A. Raji","doi":"10.5772/INTECHOPEN.80071","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.80071","url":null,"abstract":"Vigilant fault diagnosis and preventive maintenance has the potential to significantly decrease costs associated with wind generators. As wind energy continues the upward growth in technology and continued worldwide adoption and implementation, the application of fault diagnosis techniques will become more imperative. Fault diagnosis and preventive maintenance techniques for wind turbine generators are still at an early stage compared to matured strategies used for generators in conventional power plants. The cost of wind energy can be further reduced if failures are predicted in advance of a major structural failure, which leads to less unplanned maintenance. High maintenance cost of wind turbines means that predictive strategies like fault diagnosis and preventive maintenance techniques are necessary to manage life cycle costs of critical components. Squirrel-Cage Induction Generators (SCIG) are the prevailing generator type and are more robust and cheaper to manufacturer compared to other generator types used in wind turbines. A statistical model was developed using SCADA data to estimate the relationships between winding temperatures and other variables. Predicting faults in stator windings are challenging because the unhealthy condition rapidly evolves into a functional failure.","PeriodicalId":358379,"journal":{"name":"Fault Detection and Diagnosis","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114998562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Hybrid Fault Diagnosis Method Based on Mechanical-Electrical Intersectional Characteristics for Generators 基于机电相交特征的发电机混合故障诊断方法
Fault Detection and Diagnosis Pub Date : 2018-11-05 DOI: 10.5772/INTECHOPEN.79955
Yu‐Ling He, Yue-Xin Sun
{"title":"Hybrid Fault Diagnosis Method Based on Mechanical-Electrical Intersectional Characteristics for Generators","authors":"Yu‐Ling He, Yue-Xin Sun","doi":"10.5772/INTECHOPEN.79955","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.79955","url":null,"abstract":"In this chapter, a new hybrid fault diagnosis method based on the mechanical-electrical intersectional characteristics for turbo-generators is proposed. Different from other studies, this method not only employs the rotor vibration characteristics but also uses the stator vibration features and the circulating current properties inside the parallel branches of the same phase. Detailed theoretical analysis, as well as the experimental verification study, is carried out to demonstrate the proposed method. It is shown that in the proposed criterion for the method, the combining faulty characteristics for the single rotor eccentric- ity fault, the single rotor interturn short circuit fault, and the composite fault composed of the rotor eccentricity and the rotor interturn short circuit are all unique. The running conditions can be accurately and quickly identified by the proposed method. The work proposed in this chapter offers a new thought for the condition monitoring and the fault diagnosis of generators.","PeriodicalId":358379,"journal":{"name":"Fault Detection and Diagnosis","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125256250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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