Topic
Fault detection and isolation
About: Fault detection and isolation is a research topic. Over the lifetime, 46115 publications have been published within this topic receiving 641536 citations.
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Book•
01 Jan 2000
TL;DR: This chapter discusses Signal Estimation, which automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and changing the values of coefficients in a model to facilitate change detection.
Abstract: INTRODUCTION Extended Summary. Applications. SIGNAL ESTIMATION On--Line Approaches. Off--Line Approaches. PARAMETER ESTIMATION Adaptive Filtering. Change Detection Based on Sliding Windows Change Detection Based on Filter Banks STATE ESTIMATION Kalman Filtering Change Detection Based on Likelihood Ratios Change Detection Based on Multiple Models Change Detection Based on Algebraical Consistency Tests THEORY Evaluation Theory Linear Estimation A. Signal models and notation B. Fault detection terminology
1,170 citations
TL;DR: A state-of-the-art review of the methods and applications of data-driven fault detection and diagnosis that have been developed over the last two decades are provided to draw attention from the systems and control community and the process control community.
1,154 citations
TL;DR: This paper considers the application of a particular sliding mode observer to the problem of fault detection and isolation using the equivalent output injection concept to explicitly reconstruct fault signals.
1,141 citations
TL;DR: An introduction to the field of fault detection and diagnosis is given, which begins with a consideration of a knowledge-based procedure that is based on analytical and heuristic information, and different methods of Fault detection are considered, which extract features from measured signals and use process and signal models.
1,090 citations
Book•
29 Sep 2006TL;DR: The author examines the development of the Diagnostic Framework for Electrical/Electronic Systems and its applications in CBM/PHM systems, as well as some of the techniques used in model-Based Reasoning and other methods for Fault Diagnosis.
Abstract: PREFACE. ACKNOWLEDGMENTS. PROLOGUE. 1 INTRODUCTION. 1.1 Historical Perspective. 1.2 Diagnostic and Prognostic System Requirements. 1.3 Designing in Fault Diagnostic and Prognostic Systems. 1.4 Diagnostic and Prognostic Functional Layers. 1.5 Preface to Book Chapters. 1.6 References. 2 SYSTEMS APPROACH TO CBM/PHM. 2.1 Introduction. 2.2 Trade Studies. 2.3 Failure Modes and Effects Criticality Analysis (FMECA). 2.4 System CBM Test-Plan Design. 2.5 Performance Assessment. 2.6 CBM/PHM Impact on Maintenance and Operations: Case Studies. 2.7 CBM/PHM in Control and Contingency Management. 2.8 References. 3 SENSORS AND SENSING STRATEGIES. 3.1 Introduction. 3.2 Sensors. 3.3 Sensor Placement. 3.4 Wireless Sensor Networks. 3.5 Smart Sensors. 3.6 References. 4 SIGNAL PROCESSING AND DATABASE MANAGEMENT SYSTEMS. 4.1 Introduction. 4.2 Signal Processing in CBM/PHM. 4.3 Signal Preprocessing. 4.4 Signal Processing. 4.5 Vibration Monitoring and Data Analysis. 4.6 Real-Time Image Feature Extraction and Defect/Fault Classification. 4.7 The Virtual Sensor. 4.8 Fusion or Integration Technologies. 4.9 Usage-Pattern Tracking. 4.10 Database Management Methods. 4.11 References. 5 FAULT DIAGNOSIS. 5.1 Introduction. 5.2 The Diagnostic Framework. 5.3 Historical Data Diagnostic Methods. 5.4 Data-Driven Fault Classification and Decision Making. 5.5 Dynamic Systems Modeling. 5.6 Physical Model-Based Methods. 5.7 Model-Based Reasoning. 5.8 Case-Based Reasoning (CBR). 5.9 Other Methods for Fault Diagnosis. 5.10 A Diagnostic Framework for Electrical/Electronic Systems. 5.11 Case Study: Vibration-Based Fault Detection and Diagnosis for Engine Bearings. 5.12 References. 6 FAULT PROGNOSIS. 6.1 Introduction. 6.2 Model-Based Prognosis Techniques. 6.3 Probability-Based Prognosis Techniques. 6.4 Data-Driven Prediction Techniques. 6.5 Case Studies. 6.6 References. 7 FAULT DIAGNOSIS AND PROGNOSIS PERFORMANCE METRICS. 7.1 Introduction. 7.2 CBM/PHM Requirements Definition. 7.3 Feature-Evaluation Metrics. 7.4 Fault Diagnosis Performance Metrics. 7.5 Prognosis Performance Metrics. 7.6 Diagnosis and Prognosis Effectiveness Metrics. 7.7 Complexity/Cost-Benefit Analysis of CBM/PHM Systems. 7.8 References. 8 LOGISTICS: SUPPORT OF THE SYSTEM IN OPERATION. 8.1 Introduction. 8.2 Product-Support Architecture, Knowledge Base, and Methods for CBM. 8.3 Product Support without CBM. 8.4 Product Support with CBM. 8.5 Maintenance Scheduling Strategies. 8.6 A Simple Example. 8.7 References. APPENDIX. INDEX.
1,000 citations