Research on fault source identification of gas pipeline based on WPT-PCA-GMHMM
In order to overcome the problem of low aperture recognition accuracy caused by large amplitude change of leakage signal of gas pipeline under pressure fluctuation,a leakage source feature recognition model based on WPT-PCA-GMMMM is proposed.The acoustic emission detection experiment of pipeline leakage under pressure fluctuation was carried out,and the wavelet packet energy spectrum of acoustic emission signal under different working conditions was extracted by wavelet packet transformation(WPT).Then the frequency band energy was decorrelated and dimensionally reduced by principal component analysis(PCA).Finally,the data and labels were divided into training set and test set,and the Gaussian mixed-hidden Markov model(GMHMM)was used to realize the classification and identification of pipeline pressure and leakage aperture.The results show that the overall accuracy of the proposed model reaches 95.20%,the accuracy of leakage aperture reaches 99.95%,and the accuracy of notable leakage identification reaches 100%,which has excellent performance compared with BPNN and SVM in the environment of both sufficient samples and small samples.
国家科技期刊平台
NSTL
万方数据
维普
