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Preface; Contents; About the Editors; 1 Advanced Signal Processing for Structural Health Monitoring; Abstract; 1 Introduction; 2 Structural Health Monitoring; 2.1 Operational Evaluation; 2.2 Data Acquisition; 2.3 Feature Extraction; 2.4 Diagnosis and Prognosis; 3 Signal Processing in SHM; References; 2 Signal Post-processing for Accurate Evaluation of the Natural Frequencies; Abstract; 1 Introduction; 2 Motivation; 3 Standard Frequency Evaluation; 4 Simple Methods to Improve the Frequency Readability; 5 Description and Implementation of the Iterative Algorithm
6 Testing the Algorithm Efficiency7 Conclusions; Acknowledgements; References; 3 Holobalancing Method and Its Improvement by Reselection of Balancing Object; Abstract; 1 Introduction; 2 Construction of Holospectrum; 2.1 Basic Condition Required; 2.2 Three-Dimensional Holospectrum (3dH); 3 Introduction of Holobalancing Method; 3.1 Initial Phase Point (IPP); 3.2 Precession Angle Compensation; 3.3 Differential Holospectrum and Transfer Matrix; 3.4 The Balancing Procedure; 4 Balancing Object Reselection; 4.1 Characteristic and Deficiency of the IPV; 4.2 Precession Decomposition
4.3 Balancing Object Selection: Characteristic Analysis of IPV+ and IPV− [7]5 Experimental Verification and Case Study; 5.1 Experimental Verification; 5.2 Case Study; 6 Conclusion and Discussion; References; 4 Wavelet Transform Based on Inner Product for Fault Diagnosis of Rotating Machinery; Abstract; 1 Introduction; 2 Wavelet Transform Based on Inner Product; 2.1 Inner Product; 2.2 CWT, DWT and WPT; 2.3 Inner Product Validation of WT in RMFD; 3 Adaptive Multiwavelet for RMFD; 3.1 Summary of Multiwavelet Theory; 3.2 Adaptive Multiwavelet Construction; 3.3 Experimental Study; 4 Discussion
5 ConclusionReferences; 5 Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Transient Vibration; Abstract; 1 A Brief Introduction; 2 Spectral Kurtosis and Fast Kurtogram; 2.1 Signal Modelling; 2.2 Spectral Kurtosis; 2.3 Illustration Example of Spectral Kurtosis; 3 Wavelet Based Kurtogram and Its Development; 3.1 STFT Based Kurtogram; 3.2 Fast Kurtogram; 3.3 Wavelet Packet Based Kurtogram; 4 Wavelet Tight Frame Based Kurtogram; 4.1 Limitation of Original Kurtogram; 4.2 Quasi-Analytic Wavelet Tight Frame
4.3 Spatial-Spectral Ensemble Kurtosis and Its Kurtogram4.4 Numerical Simulations and Engineering Applications; 5 Adaptive Super-Wavelet Based Kurtogram; 5.1 Adaptive Super-Wavelet Transform; 5.2 A Sparse Indictor: Fault Feature Ratio (FFR); 5.3 Adaptive ESW Based Kurtogram; 5.4 Engineering Applications; 6 Conclusions; Acknowledgements; References; 6 Time-Frequency Manifold for Machinery Fault Diagnosis; Abstract; 1 Introduction; 2 Time-Frequency Manifold Analysis; 2.1 Principle; 2.2 Phase Space Reconstruction; 2.3 Time-Frequency Distribution; 2.4 TFM Learning
6 Testing the Algorithm Efficiency7 Conclusions; Acknowledgements; References; 3 Holobalancing Method and Its Improvement by Reselection of Balancing Object; Abstract; 1 Introduction; 2 Construction of Holospectrum; 2.1 Basic Condition Required; 2.2 Three-Dimensional Holospectrum (3dH); 3 Introduction of Holobalancing Method; 3.1 Initial Phase Point (IPP); 3.2 Precession Angle Compensation; 3.3 Differential Holospectrum and Transfer Matrix; 3.4 The Balancing Procedure; 4 Balancing Object Reselection; 4.1 Characteristic and Deficiency of the IPV; 4.2 Precession Decomposition
4.3 Balancing Object Selection: Characteristic Analysis of IPV+ and IPV− [7]5 Experimental Verification and Case Study; 5.1 Experimental Verification; 5.2 Case Study; 6 Conclusion and Discussion; References; 4 Wavelet Transform Based on Inner Product for Fault Diagnosis of Rotating Machinery; Abstract; 1 Introduction; 2 Wavelet Transform Based on Inner Product; 2.1 Inner Product; 2.2 CWT, DWT and WPT; 2.3 Inner Product Validation of WT in RMFD; 3 Adaptive Multiwavelet for RMFD; 3.1 Summary of Multiwavelet Theory; 3.2 Adaptive Multiwavelet Construction; 3.3 Experimental Study; 4 Discussion
5 ConclusionReferences; 5 Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Transient Vibration; Abstract; 1 A Brief Introduction; 2 Spectral Kurtosis and Fast Kurtogram; 2.1 Signal Modelling; 2.2 Spectral Kurtosis; 2.3 Illustration Example of Spectral Kurtosis; 3 Wavelet Based Kurtogram and Its Development; 3.1 STFT Based Kurtogram; 3.2 Fast Kurtogram; 3.3 Wavelet Packet Based Kurtogram; 4 Wavelet Tight Frame Based Kurtogram; 4.1 Limitation of Original Kurtogram; 4.2 Quasi-Analytic Wavelet Tight Frame
4.3 Spatial-Spectral Ensemble Kurtosis and Its Kurtogram4.4 Numerical Simulations and Engineering Applications; 5 Adaptive Super-Wavelet Based Kurtogram; 5.1 Adaptive Super-Wavelet Transform; 5.2 A Sparse Indictor: Fault Feature Ratio (FFR); 5.3 Adaptive ESW Based Kurtogram; 5.4 Engineering Applications; 6 Conclusions; Acknowledgements; References; 6 Time-Frequency Manifold for Machinery Fault Diagnosis; Abstract; 1 Introduction; 2 Time-Frequency Manifold Analysis; 2.1 Principle; 2.2 Phase Space Reconstruction; 2.3 Time-Frequency Distribution; 2.4 TFM Learning