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Study on energy distribution character about post-disaster rescue signal based on CEEMDAN-WPT denoising


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Study on energy distribution character about post-disaster rescue signal based on CEEMDAN-WPT denoising
Huang Jin1Wu Qingliang1Chen Fan2
1.College of Engineering and Technology,Southwest University,Chongqing 400716,China; 2.China Power Construction Road and Bridge Group Co Ltd Beijing 100048,China
post-disaster rescue complete ensemble empirical mode decomposition with adaptive noise wavelet packets band energy
The post-disaster rescue environment of underground projects such as tunnels and mines under construction is complex,and the knock signal for rescue is weak and often submerged in the noise environment. How to effectively pick up the knock signal for rescue is the most important task of post-disaster rescue. Based on the on-site knocking data,different types of knock signals of steel frame,steel pipe and hammer are selected for comparative study. Firstly,the signal is decomposed with the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN). The power spectral density,correlation coefficient and variance contribution methods are used to screen the IMF containing real physical meaning. Then wavelet packet threshold de-noising(WPT)is used to filter the signal hierarchically. Secondly,the wavelet packet band energy of reconstructed signal at each node is obtained by using the wavelet packet analysis module. The energy distribution characteristics of different types of knock signals are studied,and the energy distribution differences in the frequency band are compared. The results show that the energy distribution of different types of knock signals of steel frame,steel pipe and hammer is approximately the same,mostly concentrated in 0~250 Hz. Through more detailed analysis of energy frequency band,the proportion of steel frame knocking on the ground is the least,and the proportion of hammer knocking on the ground is the largest. The research results provide a basis for effective identification of rescue signals after disasters and the selection of sensor parameters of rescue equipment.


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Last Update: 2020-04-20