Application of Wavelet Packet and Support Vector Machine to Leak Detection in Pipeline

被引：2
|
作者：
Liu Na [1 ]
Zhao Yanyan [2 ]
机构：
[1] Beijing Inst Petrochem Technol, Dept Automat, Beijing 102617, Peoples R China
[2] Beijing Univ Chem Technol, Dept Comp Applicat, Beijing 100029, Peoples R China
来源：
2008 ISECS INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT, VOL 1, PROCEEDINGS | 2008年
关键词：
Acoustic Emission; Feature extraction; Support Vector Machine; Pipeline Leak; Wavelet packet;
D O I：
10.1109/CCCM.2008.346
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Acoustic emission (AE) technology is one of the promising methods for pipeline leak detection. But AE signal of pipeline leak carry the non-stationary feature information. Therefore, one major problem is feature extraction of AE signal from noise and complexity in transmission. This paper analyzes the characteristics of AE signal to acquire effective waveform signal, applies wavelet package to construct and reconstruct signal, extracts feature vectors to set up training sample, and establishes a support vector machines (SVM) fault classifier to diagnosis. Experimental results show that the identification rate can be up to 100% for pipeline leak.
引用
收藏
页码：66 / +
页数：2
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