Abstract: When small leak occurs in the natural gas pipeline, it is difficult to identify the leak scale and aperture. It is proposed a small leak aperture recognition method based on local mean decomposition(LMD) envelope spectrum entropy and SVM. The leakage signals are decomposed into a number of production functions(PFs) components which have physical significance instantaneous frequencies. And then calculate the PFs kurtosis values and according to this select the principal PF components which contain most of leakage information. Further the wavelet packet decomposition and band energy distribution method are used to analyze the principal PF components and then reconstruct them. The Hilbert transform is applied to these reconstructed principal PF components and the corresponding envelope spectrums are obtained. Combining the concept of information entropy, the envelope spectrum entropy is proposed and calculates the entropy values. The normalized envelope spectrum entropy as the leakage feature is input the support vector machine(SVM) and the leak aperture classification is accomplished. By analyzing the acquired pipeline leakage signals in the field experiments, the results show that this method can effectively identify the different leak apertures.

Key words: envelope spectrum entropy, local mean decomposition, pipeline small leak recognition, support vector machine(SVM)