عنوان

Bayesian networks in fault diagnosis :

9789813271494

9789813271500

9813271493

9813271507

9789813271487

9789813271876

9813271485

9813271876

Bayesian networks in fault diagnosis :

[Book]

practice and application /

editors, Baoping Cai, Yonghong Liu, Jinqui Hu, Zengkai Liu, Shengnan Wu, Renjie Ji.

Hackensack, NJ :

World Scientific Publishing Co. Pte. Ltd.,

[2019]

1 online resource

Includes bibliographical references and index.

Intro; Contents; Preface; 1. Fault Diagnosis; 1.1 Introduction; 1.2 Overview of BNs; 1.3 Procedures of Fault Diagnosis with BNs; 1.3.1. BN structure modeling; 1.3.2. BN parameter modeling; 1.3.3. BN inference; 1.3.4. Fault identification; 1.3.5. Verification and validation; 1.4. Types of BNs for Fault Diagnosis; 1.4.1. BN for fault diagnosis; 1.4.2. DBNs for fault diagnosis; 1.4.3. OOBNs for fault diagnosis; 1.4.4. Other BNs for fault diagnosis; 1.5 Domains of Fault Diagnosis with BNs; 1.5.1. Fault diagnosis for process systems; 1.5.2. Fault diagnosis for energy systems.

1.5.3. Fault diagnosis for structural systems; 1.5.4. Fault diagnosis for manufacturing systems; 1.5.5. Fault diagnosis for network systems; 1.6 Discussions and Research Directions; 1.6.1. Integrated big data and BN fault diagnosis methodology; 1.6.2. BN-based nonpermanent fault diagnosis; 1.6.3. Fast inference algorithms of BNs for online fault diagnosis; 1.6.4. BNs for closed-loop control system fault diagnosis; 1.6.5. Fault identification rules; 1.6.6. Hybrid fault diagnosis approaches; 1.7 Conclusion; References.

2. Multi-Source Information Fusion-Based Fault Diagnosis of Ground-Source Heat Pump Using Bayesian Network; 2.1 Introduction; 2.2 Faults and Fault Symptoms; 2.3 Fault Diagnosis Methodology; 2.3.1. Fault diagnosis based on sensor data; 2.3.1.1. BN structure; 2.3.1.2. BN parameters; 2.3.2. Fault diagnosis based on observed information; 2.3.2.1. BN structure; 2.3.2.2. BN parameters; 2.3.3. Multi-source information fusion-based fault diagnosis; 2.4. Results and Discussion; 2.4.1. Fault diagnosis using evidences from only sensor data.

2.4.2. Fault diagnosis using evidences from sensor data and observed information; 2.5. Conclusion; References; 3. A Data-Driven Fault Diagnosis Methodology in Three-Phase Inverters for PMSM Drive Systems; 3.1. Introduction; 3.2. System Description and Fault Analysis; 3.3. Fault Diagnosis Methodology; 3.3.1. Proposed fault diagnosis methodology; 3.3.2. Signal feature extraction using FFT; 3.3.3. Dimensionality reduction using PCA; 3.3.4. Fault diagnosis using BNs; 3.4. Developments and Validations; 3.4.1. Simulation and experimental setup; 3.4.2. Results; 3.5. Conclusion; References.

4. A Real-Time Fault Diagnosis Methodology of Complex Systems Using Object-Oriented Bayesian Networks; 4.1. Introduction; 4.2. A Proposed Modeling Methodology; 4.2.1. Overview of OOBNs; 4.2.2. Modeling methodology; 4.2.3. Structure of OOBNs; 4.2.4. Parameter of OOBNs; 4.2.5. Model validation; 4.2.6. Fault diagnosis and verification; 4.3. Case Study; 4.3.1. Description of subsea production system; 4.3.2. Fault diagnosis modeling; 4.3.3. Results and discussion; 4.4. Conclusion; References.

5. A Dynamic Bayesian Network-Based Fault Diagnosis Methodology Considering Transient and Intermittent Faults.

0

8

8

8

8

8

"Fault diagnosis is useful for technicians to detect, isolate, identify faults, and troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals with various uncertainty problems. This model is increasingly utilized in fault diagnosis. This unique compendium presents bibliographical review on the use of BNs in fault diagnosis in the last decades with focus on engineering systems. Subsequently, eleven important issues in BN-based fault diagnosis methodology, such as BN structure modeling, BN parameter modeling, BN inference, fault identification, validation, and verification are discussed in various cases. Researchers, professionals, academics and graduate students will better understand the theory and application, and benefit those who are keen to develop real BN-based fault diagnosis system."--

Bayesian networks in fault diagnosis.

9789813271487

Bayesian statistical decision theory.

Fault location (Engineering)

Bayesian statistical decision theory.

Fault location (Engineering)

MATHEMATICS-- Applied.

MATHEMATICS-- Probability & Statistics-- General.

MAT-- 003000

MAT-- 029000

Baoping, Cai

Hu, Jinqiu

Ji, Renjie

Liu, Yonghong

Wu, Shengnan

20200823231944.0

pn

[Book]

Y