An adaptive wavelet denoising method for the measuring system of EMP signals

Author(s):  
Shi Lihua ◽  
Chen Bin ◽  
Zhou Binhua ◽  
Gao Cheng
2016 ◽  
Vol 16 (1) ◽  
pp. 116-125 ◽  
Author(s):  
Xin-Hua Wang ◽  
Yu-Lin Jiao ◽  
Yong-Chao Niu ◽  
Jie Yang

Abstract Traditional wavelet denoising method cannot eliminate complex high-pressure pipe signals effectively. In the updated wavelet adaptive algorithm, this thesis defines the constraints in order to reconstruct the signals accurately. According to the minimum mean square error criterion, the results predict the weight coefficient and get the optimal linear predictive value. Adopting the improved algorithm under the same condition, this thesis concluded that Db6 increased the complexity of wavelet algorithm by 50% by comparative experiments. It will be more conducive to the realization of hardware and the feasibility of real-time denoising. Dual adaptive wavelet denoising method improved SNR by 50%. This denoising method will play a key role in the detection rate of high-pressure pipe in the online leakage detection system.


2012 ◽  
Vol 546-547 ◽  
pp. 686-690
Author(s):  
Hui Juan Hao ◽  
Ji Yong Xu ◽  
Juan Li

In order to reduce the noise of acquisition signal in laser cutting, an adaptive wavelet denoising method is proposed in this paper. Based on the analysis of the limitations of traditional threshold method, the particle swarm optimization algorithm is used to select the optimal threshold of wavelet. Compared with the commonly hard and soft threshold method, the experiment results show that the method used in this paper is relatively stable, and can reduce noise excellently. The method can provide more accurate signal for quality analysis in laser cutting .So the method can be used in noise denoising of pulse-induced acoustic sound.


2012 ◽  
Vol 42 (2) ◽  
pp. 171-179 ◽  
Author(s):  
Sergey Vaisman ◽  
Shimrit Yaniv Salem ◽  
Gershon Holcberg ◽  
Amir B. Geva

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