1st Edition
Filter-Based Fault Diagnosis and Remaining Useful Life Prediction
Chapter 1. Introduction
1.1 Introduction
1.2 Fault Diagnosis
1.3 Remaining Useful Life Prediction
1.4 Outline of This Book
Chapter 2. Filter/Estimator Design of Networked Multirate Sampled Systems with Network-induced Phenomena
2.1 Estimator Design with Measurement Quantization and Sensor Failures
2.2 Finite-time Filter Design with Event-based Relay and Fading Channels
2.3 Conclusion
Chapter 3. Fault Detection of Networked Multirate Systems with Filter-based Methods
3.1 Fault Detection with Fading Measurements and Randomly Occurring Faults
3.2 Fault Detection with Dynamic Quantization and Intermittent Faults
3.3 Conclusion
Chapter 4. Fault Diagnosis of Multirate Time-varying Systems with Filter-based Methods
4.1 Event-based Fault Diagnosis with Constrained Fault
4.2 Event-based Fault Diagnosis with Bounded Unknown Fault
4.3 Conclusion
Chapter 5. Fault Diagnosis of Modular Multilevel Converters with Machine Learning Methods
5.1 Fault Diagnosis with Mixed Kernel Support Tensor Machine
5.2 Fault Diagnosis with Synchrosqueezing Transform and Optimized Deep CNN
5.3 Conclusion
Chapter 6. Remaining Useful Life Prediction of Industrial Components with Filterbased Methods
6.1 Remaining Useful Life Prediction with Adaptive UKF and SVR
6.2 Remaining Useful Life Prediction with ALF Optimized PF and LSTM
6.3 Remaining Useful Life Prediction with Degradation Point Detection and EKF
6.4 Conclusion
Chapter 7. Remaining Useful Life Prediction of Industrial Components with Machine Learning Methods
7.1 Remaining Useful Life Prediction with WPT and Optimized SVR
7.2 Remaining Useful Life Prediction with Complete Ensemble EMD and GRU
7.3 Remaining Useful Life Prediction with PSR and Error Compensation
7.4 Conclusion
Chapter 8. Conclusions and Future Topics
Biography
Yong Zhang
