(eBook PDF) Bayesian Networks in Fault Diagnosis: Practice and Application – Digital Ebook – Instant Delivery Download
Product details:
- ISBN: 9789813271500
- Author: Baoping Cai, Yonghong Liu, Jinqiu Hu, Zengkai Liu, Shengnan Wu, Renjie Ji
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.
Table of contents:
Chapter 1: Fault Diagnosis
Chapter 2: Multi-Source Information Fusion-Based Fault Diagnosis of Ground-Source Heat Pump Using Bayesian Network
Chapter 3: A Data-Driven Fault Diagnosis Methodology in Three-Phase Inverters for PMSM Drive Systems
Chapter 4: A Real-Time Fault Diagnosis Methodology of Complex Systems Using Object-Oriented Bayesian Networks
Chapter 5: A Dynamic Bayesian Network-Based Fault Diagnosis Methodology Considering Transient and Intermittent Faults
Chapter 6: An Integrated Safety Prognosis Model for Complex System Based on Dynamic Bayesian Network and Ant Colony Algorithm
Chapter 7: An Intelligent Fault Diagnosis System for Process Plant Using a Functional HAZOP and DBN Integrated Methodology
Chapter 8: DBN-Based Failure Prognosis Method Considering the Response of Protective Layers for Complex Industrial Systems
Chapter 9: Fault Diagnosis for a Solar-Assisted Heat Pump System Under Incomplete Data and Expert Knowledge
Chapter 10: An Approach for Developing Diagnostic Bayesian Network Based on Operation Procedures
Chapter 11: A DBN-Based Risk Assessment Model for Prediction and Diagnosis of Offshore Drilling Incidents
Chapter 12: A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network
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Data-Driven and Model-Based Methods for Fault Detection and Diagnosis 1st Edition – eBook PDF
