Open Access
Fault Diagnosis Techniques for Dynamic Systems
Zhou Dong-Hua,HU Yan-Yan +1 more
TLDR
A novel classiflcation framework is proposed, which divides fault diagnosis approaches into two classes: qual- itative analysis approaches and quantitative analysis approaches, with emphasis on the data-driven approaches.Abstract:
A novel classiflcation framework is proposed, which divides fault diagnosis approaches into two classes: qual- itative analysis approaches and quantitative analysis approaches The basic idea, main research progresses, and typical applications of each method are discussed in detail, with emphasis on the data-driven approaches The state-of-the-art of fault prediction is also outlined Finally, some problems and development trends of the research on fault diagnosis are pointed outread more
Citations
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Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures
TL;DR: A comprehensive review of the mechanisms, features, and diagnosis of various faults in LIBSs, including internal battery faults, sensor faults, and actuator faults are provided.
Journal ArticleDOI
A survey of fault diagnosis for swarm systems
Liguo Qin,Xiao He,Donghua Zhou +2 more
TL;DR: Fault diagnosis algorithms for swarm systems are classified according to their architectures, fault types and approaches, respectively, followed by characteristics of faults in swarm systems.
Journal Article
Review on Fault Diagnosis Techniques for Closed-loop Systems
TL;DR: In this article, a review of fault diagnosis for closed-loop systems is presented, and some challenging problems and promising research directions are pointed out, as well as some simulation examples are employed to illustrate the diferent fault diagnosis performances between typical openloop systems and closedloop systems.
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Roller bearing safety region estimation and state identification based on LMD–PCA–LSSVM
TL;DR: Local mean decomposition (LMD), principal component analysis (PCA) and least square support vector machine (LSSVM) are used comprehensively for the estimation of the safety region and the identification of normal state and faulty state for the roller bearing operational status.
Journal ArticleDOI
A New Fault Diagnosis Method Based on Fault Tree and Bayesian Networks
Rong-xing Duan,Hui-lin Zhou +1 more
TL;DR: A novel method for diagnosing faults using fault tree analysis and Bayesian networks (BN) to optimize system diagnosis and a diagnostic decision tree (DDT) was generated to guide the maintenance personnel to repair the system.
References
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Journal ArticleDOI
Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
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Paper: A survey of design methods for failure detection in dynamic systems
TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
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A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods
TL;DR: This three part series of papers is to provide a systematic and comparative study of various diagnostic methods from different perspectives and broadly classify fault diagnosis methods into three general categories and review them in three parts.
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A review of process fault detection and diagnosis: Part III: Process history based methods
TL;DR: This final part discusses fault diagnosis methods that are based on historic process knowledge that need to be addressed for the successful design and implementation of practical intelligent supervisory control systems for the process industries.
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Analytical redundancy and the design of robust failure detection systems
E. Chow,Alan S. Willsky +1 more
TL;DR: In this article, a robust failure detection and identification (FDI) process is viewed as consisting of two stages: residual generation and decision making, and it is argued that a robust FDI system can be achieved by designing a robust residual generation process.