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Smart Structures and Systems
  Volume 10, Number 3, September 2012, pages 253-269

A split spectrum processing of noise-contaminated wave signals for damage identification
X.T. Miao, Lin Ye, F.C. Li, X.W. Sun, H.K. Peng, Ye Lu and Guang Meng

    A split spectrum processing (SSP) method is proposed to accurately determine the time-of-flight (ToF) of damage-scattered waves by comparing the instantaneous amplitude variation degree (IAVD) of a wave signal captured from a damage case with that from the benchmark. The fundamental symmetrical (S0) mode in aluminum plates without and with a notch is assessed. The efficiency of the proposed SSP method and Hilbert transform in determining the ToF of damage-scattered S0 mode is evaluated for damage identification when the wave signals are severely contaminated by noise. Broadband noise can overwhelm damage-scattered wave signals in the time domain, and the Hilbert transform is only competent fordetermining the ToF of damage-scattered S0 mode in a noise-free condition. However, the calibrated IAVD of the captured wave signal is minimally affected by noise, and the proposed SSP method is capable of determining the ToF of damage-scattered S0 mode accurately even though the captured wave signal is severely contaminated by broadband noise, leading to the successful identification of damage (within an error on the order of the damage size) using a triangulation algorithm.
Key Words
    split spectrum processing (SSP); instantaneous amplitude variation degree (IAVD); time of flight (ToF); guided waves; broadband noise; triangulation algorithm
X.T. Miao, F.C. Li, X.W. Sun and Guang Meng : State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
Lin Ye and Ye Lu : Laboratory of Smart Materials and Structures (LSMS), Centre for Advanced Materials Technology (CAMT), School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, NSW 2006, Australia
H.K. Peng : Shanghai Institute of Satellite Engineering, Shanghai 200240, China

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