Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring

Dong Wang, Bingchang Hou (Autoren)

Buch | Softcover

184 Seiten

2025
Elsevier - Health Sciences Division (Verlag)
9780443334863 (ISBN)

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Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring presents newly designed sparsity measures and their advanced signal processing technologies for machine condition monitoring and fault diagnosis. This book systematically covers new sparsity measures including a quasiarithmetic mean ratio framework for fault signatures quantification, a generalized Gini index, as well as classic sparsity measures based on signal processing technologies and a cycle-embedded sparsity measure based on new impulsive mode decomposition technology. This book additionally includes a sparsity measure data-driven framework–based optimized weights spectrum theory and its relevant advanced signal processing technologies.

Dr Dong Wang has over 15 years of research experience on machine condition monitoring and fault diagnosis. Dr. Wang’s research focuses on the theoretical foundations of fault feature extraction and their applications to machine condition monitoring, fault diagnosis and prognostics. Dr. Wang has published over 150 journal papers (the first author for 40+ papers) Bingchang Hou received his B.Eng. degree in Mechanical Engineering from Chongqing University, Chongqing, China, in 2020. Since Sep. 2020, he is pursuing his Ph.D. degree in Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China. His research interests include machine condition monitoring and fault diagnosis, prognostics and health management, sparsity measures, signal processing, and machine learning

1. Introduction and background
2. Basic signal processing transforms and analysis
3. Newly advanced sparsity measures for fault signature quantification
4. Classic and advanced sparsity measures-based signal processing technologies
5. Sparsity measures data-driven framework based signal processing technologies
6. Outlook References

Erscheinungsdatum	11.02.2025
Verlagsort	Philadelphia
Sprache	englisch
Maße	152 x 229 mm
Gewicht	310 g
Themenwelt	Mathematik / Informatik ► Informatik
	Technik ► Maschinenbau
	Technik ► Nachrichtentechnik
ISBN-13	9780443334863 / 9780443334863
Zustand	Neuware