Machine Performance Degradation Assessment

Name: Machine Performance Degradation Assessment
Price: 170 USD
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ISBN: 9780443440076

Convex Optimization Models and Their Interpretable Data Fusion Applications

by Dong Wang, Tongtong Yan

1st Edition

Publisher: Elsevier

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Book Details

Print ISBN	9780443440076
eText ISBN	9780443440083
Publisher	Elsevier
Publishing Year	2025
Edition	1st Edition
Language	English
Pages	152

In Machine Performance Degradation Assessment: Convex Optimization Models and Their Interpretable Data Fusion Applications, 1st Edition, Dong Wang and Tongtong Yan present fundamental theories for machine performance monitoring. The work provides advanced techniques for formulating mechanical degradation properties into convex optimization models designed specifically for health index construction.

The book structures its technical coverage around signal processing technology and feature extraction and selection. By examining how physical signals reflect machinery condition, the authors present interpretable data fusion applications. A key element of this mathematical coverage includes generalized health index weight optimization models relying on amplitude fusion in the frequency domain.

This text provides dedicated analytical tools for academic and institutional researchers in mechanical engineering alongside researchers in statistical mathematics. Industry professionals involved in machinery health monitoring will also benefit from its systematic presentation of convex optimization and health index construction.

Chapter 1: Machine performance degradation assessment
- • 1.1 Introduction
- • 1.2 Dataset collection
- • 1.3 Signal processing technology
- • 1.4 Feature extraction and selection
- • 1.5 Data fusion technology
- • 1.6 Health index construction
- • 1.7 Conclusions
- • 1.8 References
Chapter 2: Fundamentals of convex optimization
- • 2.1 Introduction
- • 2.2 Convex set
- • 2.3 Convex function
- • 2.4 Convex optimization problems
- • 2.5 Conclusions
- • 2.6 References
Chapter 3: Machine degradation processes related mathematical properties
- • 3.1 Introduction
- • 3.2 Different patterns of machine degradation processes
- • 3.3 Desirable properties of health indices and their evaluation
- • 3.4 Spectral amplitude fusion based generalized health indices
- • 3.5 Conclusions
- • 3.6 References
Chapter 4: Generalized health index weight optimization models based on degradation properties and amplitude fusion in the frequency domain
- • 4.1 Introduction
- • 4.2 Convex degradation model of separation property
- • 4.3 Convex degradation model of intra-class and inter-class properties
- • 4.4 Convex degradation model of separation and monotonicity properties
- • 4.5 Convex degradation model of separation, monotonicity and shapeness properties
- • 4.6 Convex degradation model of separation and fitness properties
- • 4.7 Convex degradation model of signal to noise ratio of a generalized health index
- • 4.8 Conclusions
- • 4.9 References
Chapter 5: Generalized health index weight optimization models based on fault feature sparsity and amplitude fusion in the envelope spectral domain
- • 5.1 Introduction
- • 5.2 Sparsity property of fault transients
- • 5.3 Sparse and flexible convex-hull representation based convex degradation model
- • 5.4 Maximum entropy principle and weight sparsity regularization based convex degradation model
- • 5.5 Monotonicity and weight sparsity regularization based convex degradation model
- • 5.6 Sparsity preserving projection and baselined hyperdisk model based convex degradation model
- • 5.7 Conclusions
- • 5.8 References
Chapter 6: Conclusions
- • 6.1 References