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Structural health monitoring = an ad...

Yan, Ruqiang.

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Structural health monitoring = an advanced signal processing perspective /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Structural health monitoring/ edited by Ruqiang Yan, Xuefeng Chen, Subhas Chandra Mukhopadhyay.
Reminder of title:	an advanced signal processing perspective /
other author:	Yan, Ruqiang.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xi, 375 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Structural health monitoring. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-56126-4
ISBN:	9783319561264

Structural health monitoring = an advanced signal processing perspective /
Structural health monitoringan advanced signal processing perspective /[electronic resource] :edited by Ruqiang Yan, Xuefeng Chen, Subhas Chandra Mukhopadhyay. - Cham :Springer International Publishing :2017. - xi, 375 p. :ill. (some col.), digital ;24 cm. - Smart sensors, measurement and instrumentation,v.262194-8402 ;. - Smart sensors, measurement and instrumentation ;v.26..

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.

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.

ISBN: 9783319561264

Standard No.: 10.1007/978-3-319-56126-4doiSubjects--Topical Terms:

1622271
Structural health monitoring.

LC Class. No.: TA656.6

Dewey Class. No.: 624.17

Structural health monitoring = an advanced signal processing perspective /
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245 0 0 $a Structural health monitoring $h [electronic resource] : $b an advanced signal processing perspective / $c edited by Ruqiang Yan, Xuefeng Chen, Subhas Chandra Mukhopadhyay.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xi, 375 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Smart sensors, measurement and instrumentation, $x 2194-8402 ; $v v.26
505 0 $a 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.
520 $a 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.
650 0 $a Structural health monitoring. $3 1622271
650 1 4 $a Engineering. $3 586835
650 2 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Biomedical Engineering. $3 720279
650 2 4 $a Industrial and Production Engineering. $3 891024
650 2 4 $a Measurement Science and Instrumentation. $3 1066390
700 1 $a Yan, Ruqiang. $3 1531766
700 1 $a Chen, Xuefeng. $3 1057505
700 1 $a Mukhopadhyay, Subhas Chandra. $3 907837
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830 0 $a Smart sensors, measurement and instrumentation ; $v v.26. $3 3236446
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-56126-4
950 $a Engineering (Springer-11647)