Open AccessResearch on Denoising Method for Improving the Identification Accuracy of Structural Damage
Author(s) -
Chao Luo,
De Qing Guan,
Songbing He,
Fan Gao
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/719/2/022045
Subject(s) - wavelet , noise reduction , computer science , signal (programming language) , noise (video) , identification (biology) , process (computing) , vibration , pattern recognition (psychology) , white noise , algorithm , artificial intelligence , acoustics , physics , telecommunications , botany , image (mathematics) , biology , programming language , operating system
Under the influence of equipment and environment, gaussian white noise will be accompanied in the process of obtaining the measured vibration mode of the structure, thus masking the effective features of signal and disturbing the effect of damage identification. To avoid this problem, this paper presented a new denoising method. Firstly, the multi-index evaluation function constructed by analytic hierarchy process is used to select the optimal wavelet base and the decomposition layers’s number. Secondly, we use the newly constructed wavelet threshold function to research the wavelet coefficients in the high frequency part of the signal to remove the noise coefficients. Simulation results show: the new denoising method is contributing in improving the SNR of vibration signals and reducing the RMS error. The experimental results testified that the new method can effectively increase the accuracy of structural damage identification.