Titlebook: Structural Health Monitoring; An Advanced Signal P Ruqiang Yan,Xuefeng Chen,Subhas Chandra Mukhopadhy Book 2017 Springer International Publ

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Advanced Signal Processing for Structural Health Monitoring,ent stages, i.e., operational evaluation, data acquisition, feature extraction and diagnosis and prognosis, involved in SHM are briefly discussed, followed by review of each signal processing technique used in SHM, which will be described in the book.

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Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Trahanical signature analysis tool always requires a rich and deep understanding of state-of-the-art technologies, which is often lacked by the on-site staff. In this chapter, we introduce an effective methodology that ensure automatic detection of impulsive transient vibrations occurring during machin

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Time-Frequency Manifold for Machinery Fault Diagnosis,gnals for machinery fault diagnosis. In the framework of the TFM analysis, the phase space reconstruction is firstly employed to reconstruct the dynamic manifold embedded in an analysed signal, then the time-frequency distributions (TFDs) are generated in the reconstructed phase space to represent t

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Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition,is therefore subject to faults easily. Vibration signals collected in the working process have valuable contributions for the presentation of conditions of the rotating machinery. Consequently, using signal processing techniques, these faults could be detected and diagnosed. Empirical mode decomposi