Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring

by B.Eng Hou Bingchang , Dong Wang

Book Details

Format Paperback / Softback

ISBN-10 0443334862

ISBN-13 9780443334863

Publisher Elsevier - Health Sciences Division

Imprint Elsevier - Health Sciences Division

Country of Manufacture GB

Country of Publication GB

Publication Date May 22nd, 2025

Print length 184 Pages

Weight 450 grams

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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.

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.

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