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Structural Health Monitoring
An Advanced Signal Processing Perspective
Buch von Ruqiang Yan (u. a.)
Sprache: Englisch

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Beschreibung
This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.
This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.
Zusammenfassung

Focuses on newly-developed signal processing techniques and their applications to various mechanical and structural systems

Encompasses interdisciplinary areas, such as smart materials, sensors and actuators, damage diagnosis and prognosis, signal and image processing algorithms, and wireless intelligent sensing

Written by leading experts in the field

Includes supplementary material: [...]

Inhaltsverzeichnis
Advanced Signal Processing for Structural Health Monitoring.- Signal Post-Processing for Accurate Evaluation of the Natural Frequencies.- Holobalancing Method and its Improvement by Reselection of Balancing Object.- Wavelet Transform Based On Inner Product for Fault Diagnosis of Rotating Machinery.- Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Transient Vibration.- Time-Frequency Manifold for Machinery Fault Diagnosis.- Matching Demodulation Transform and its Application in Machine Fault Diagnosis.- Compressive Sensing: A New Insight to Condition Monitoring of Rotary Machinery.- Sparse Representation of the Transients in Mechanical Signals.- Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition.- Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring.- Time-Frequency Demodulation Analysis Based on LMD and Its Applications.- On The Use of Stochastic Resonance in Mechanical Fault Signal Detection.
Details
Erscheinungsjahr: 2017
Fachbereich: Nachrichtentechnik
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: xi
375 S.
109 s/w Illustr.
175 farbige Illustr.
375 p. 284 illus.
175 illus. in color.
ISBN-13: 9783319561257
ISBN-10: 3319561251
Sprache: Englisch
Herstellernummer: 978-3-319-56125-7
Einband: Gebunden
Redaktion: Yan, Ruqiang
Mukhopadhyay, Subhas Chandra
Chen, Xuefeng
Herausgeber: Ruqiang Yan/Xuefeng Chen/Subhas Chandra Mukhopadhyay
Auflage: 1st edition 2017
Hersteller: Springer Nature Switzerland
Springer International Publishing
Springer International Publishing AG
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 241 x 160 x 27 mm
Von/Mit: Ruqiang Yan (u. a.)
Erscheinungsdatum: 05.05.2017
Gewicht: 0,746 kg
Artikel-ID: 109045451
Zusammenfassung

Focuses on newly-developed signal processing techniques and their applications to various mechanical and structural systems

Encompasses interdisciplinary areas, such as smart materials, sensors and actuators, damage diagnosis and prognosis, signal and image processing algorithms, and wireless intelligent sensing

Written by leading experts in the field

Includes supplementary material: [...]

Inhaltsverzeichnis
Advanced Signal Processing for Structural Health Monitoring.- Signal Post-Processing for Accurate Evaluation of the Natural Frequencies.- Holobalancing Method and its Improvement by Reselection of Balancing Object.- Wavelet Transform Based On Inner Product for Fault Diagnosis of Rotating Machinery.- Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Transient Vibration.- Time-Frequency Manifold for Machinery Fault Diagnosis.- Matching Demodulation Transform and its Application in Machine Fault Diagnosis.- Compressive Sensing: A New Insight to Condition Monitoring of Rotary Machinery.- Sparse Representation of the Transients in Mechanical Signals.- Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition.- Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring.- Time-Frequency Demodulation Analysis Based on LMD and Its Applications.- On The Use of Stochastic Resonance in Mechanical Fault Signal Detection.
Details
Erscheinungsjahr: 2017
Fachbereich: Nachrichtentechnik
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: xi
375 S.
109 s/w Illustr.
175 farbige Illustr.
375 p. 284 illus.
175 illus. in color.
ISBN-13: 9783319561257
ISBN-10: 3319561251
Sprache: Englisch
Herstellernummer: 978-3-319-56125-7
Einband: Gebunden
Redaktion: Yan, Ruqiang
Mukhopadhyay, Subhas Chandra
Chen, Xuefeng
Herausgeber: Ruqiang Yan/Xuefeng Chen/Subhas Chandra Mukhopadhyay
Auflage: 1st edition 2017
Hersteller: Springer Nature Switzerland
Springer International Publishing
Springer International Publishing AG
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 241 x 160 x 27 mm
Von/Mit: Ruqiang Yan (u. a.)
Erscheinungsdatum: 05.05.2017
Gewicht: 0,746 kg
Artikel-ID: 109045451
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