Description
Book SynopsisThis book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.
Table of Contents- Chapter 1 Introduction.
- Chapter 2 Fault Diagnosis of Variable Pitch for Wind Turbine Based on Multi-innovation Forgetting Gradient Identification Algorithm.
- Chapter 3 Active Fault-tolerant Linear Parameter Varying Control for the Pitch Actuator of Wind Turbines.
- Chapter 4 Fault Estimation and Fault-tolerant Control of Wind Turbines Using the SDW-LSI Algorithm.
- Chapter 5 A New Fault Diagnosis Approach for the Pitch System of Wind Turbines.
- Chapter 6 A dual-threshold state analysis and fault location method for power system based on random matrix theory.
- Chapter 7 Analysis of grid operation state based on improved MESCM algorithm.
- Chapter 8 Joint Weighted Domain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions.
- Chapter 9 ANS-net: anti-noise Siamese network for bearing fault diagnosis with a few data.
- Chapter 10 Fault Diagnosis of Rolling Bearing Based on Edge Calculation.
