Structural Health Monitoring
An Advanced Signal Processing Perspective
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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.
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: sn.pub/extras
Autor*in
Ruqiang Yan
Themen in »Structural Health Monitoring«
Structural Health Monitoring Signal Processing Condition Monitoring Fault Diagnostics Wavelet Theory Time-frequency Analysis Empirical Mode Decomposition Sparse Representation Wind Turbine Gas Turbine Machine Tools