Research on Leakage State Classification of Pipelines Based on Wavelet Packet Analysis and Support Vector Machines

摘要：

Aimed at the problem during the pipeline leakage state detecting process, that the datum which the sensor directly surveys are quite big and the characteristic are not strong, this paper brings forward one pipeline leakage state classification method, which combines the wavelet packet analysis and support vector machines. Through using the wavelet packet to the original data, carrying on the frequency band decomposing and the energy analysis, obtains the characteristic that can most reflect the classified essence. State sorter constituted by the support vector machines, only needs a few training samples, can make signal frequency band energy as the eigenvector to recognize and classify. The experiment datum shows that, this method effectively realizes the classified recognition of leakage state.

作者: Na Liu Lixin Zhang Yanyan Zhao

作者单位: Department of Automation, Beijing Institute of Petrochemical Technology, Beijing, 102617, P.R. China Department of Computer Application, Beijing University of Chemical Technology, Beifing, 100029, P.R.

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 235-239

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）