Mono-modal feature extraction for bonding quality detection of explosive clad structure with optimized dual-tree complex wavelet transform

Bonding quality detection of explosive clad structure is significant to prevent catastrophic accidents. Multi-modal features related to bonding quality are contained in structural vibration response signal. Different modal feature has different sensitivity to the bonding quality. Extracting the desired mono-modal feature from the vibration response signal is necessary. Due to the mode aliasing easily appeared in the process of extracting the desired mono-modal feature, there is no effective method for this task. Dual-tree complex wavelet with attractive properties such as shift invariance and reduced spectral aliasing may provide a better way to extract the mono-modal feature. However, the fixed basis functions independent of the analyzed signal may weak the advantage of the method and even reduce the accuracy of detection result To overcome this shortcoming, a technique called optimized dual-tree complex wavelet transform (ODTCWT) is proposed in this paper. Based on the analyzed signal, the optimized dual-tree complex wavelet basis function is constructed by searching for the proper parameters of vanishing moment K and the order of filter L. The optimized dual-tree complex wavelet with improved wavelet filters can best matched the modal frequencies of the analyzed signal. The ODTCWT can extract the mono-modal feature from vibration response signal with lower mode aliasing. The feasibility and effectiveness of the method of constructing ODTCWT is illustrated by the simulated signal. The proposed ODTCWT is combined with time entropy to detecting bonding quality of explosive clad pipes. For comparison, un-optimized dual-tree complex wavelet transform (UODTCWT), second-generation wavelet transform (SGWT) and bandpass filter (BPF) are also used for this task to demonstrate the validity of ODTCWT. (C) 2016 Elsevier Ltd. All rights reserved.