Improved complete ensemble empirical mode decomposition with adaptive noise and composite multiscale permutation entropy for denoising blast vibration signal
Yi-ze Kang,
Ying-kang Yao,
Run-long Dong,
Yong-sheng Jia,
Quan-min Xie,
Jian-ning Wang
Affiliations
Yi-ze Kang
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan, 430056, China; Hubei Key Laboratory of Blasting Engineering, Jianghan University, Wuhan, 430056, China
Ying-kang Yao
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan, 430056, China; Hubei Key Laboratory of Blasting Engineering, Jianghan University, Wuhan, 430056, China; Corresponding author. State Key Laboratory of Precision Blasting, Jianghan University, Wuhan, 430056, China.
Run-long Dong
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan, 430056, China; Hubei Key Laboratory of Blasting Engineering, Jianghan University, Wuhan, 430056, China
Yong-sheng Jia
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan, 430056, China; Hubei Key Laboratory of Blasting Engineering, Jianghan University, Wuhan, 430056, China; Wuhan Explosion & Blasting Co., Ltd., Wuhan, 430056, China
Quan-min Xie
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan, 430056, China; Hubei Key Laboratory of Blasting Engineering, Jianghan University, Wuhan, 430056, China
Jian-ning Wang
China National Machinery Industry Co., Ltd., Beijing, 100080, China
Monitoring the building blast vibration signal is an efficient way to determine the power of blast vibration hazards. Due to the harsh measurement environment, noise is inevitably introduced into the recorded signals. This research presents a denoising approach based on Improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN) and Composite Multiscale Permutation Entropy (CMPE). First, the noisy blast vibration signal is decomposed into different intrinsic mode functions using ICEEMDAN; then multiple intrinsic mode functions (IMFs) are separated into pure and noisy using CMPE, the noisy IMFs are denoised using wavelet thresholding; finally the blast wave is reconstructed using the pure and denoised mixed IMFs. The proposed approach was compared with four other approaches (CEEMDAN-CMPE, VMD-CMPE, SVMD-CMPE, and WST). The results indicate that the proposed approach has better performance and can be considered as an effective denoising method for building blast vibration signals.
