Optical fiber intrusion signal classification recognition method based on support vector machine

Abstract

The invention discloses an optical fiber intrusion signal recognition method based on a support vector machine, so as to solve the problem of how to accurately and effectively recognize the type of an optical fiber intrusion signal in a phase sensitive optical time domain reflection mechanism. The realization method comprises steps: time-frequency domain features of an optical fiber intrusion signal sample are firstly extracted to serve as a training sample; a kernel function is then used for mapping the sample to high-dimensional space; sequential minimization algorithm is then used for training a support vector machine classifier and mesh optimization and cross validation are used for acquiring the optimal classifier parameters; and finally, the feature vector of a to-be-classified optical fiber intrusion signal is inputted to the classifier, and a corresponding classification result is obtained according to output of the classifier. According to the method of combining the support vector machine and digital features of the optical fiber intrusion signal, the intrusion type can be accurately recognized.

Description

technical field [0001] The invention relates to a support vector machine (SVM)-based optical fiber intrusion signal classification and identification method for vibration source identification of an optical fiber intrusion system. technical background [0002] With the development of society and the advancement of science and technology, underground oil and gas pipelines have now become the main artery of oil and gas transportation. Oil and gas pipeline safety early warning technology is related to the safety of life and property, and has great strategic significance. With the rapid economic development along the pipeline, construction and ground breaking can be seen everywhere along the oil and gas pipeline. Accidents of drilling holes in the pipeline to steal oil and gas occur frequently, which seriously threatens the production safety of the pipeline. The vigorous development of the oil pipeline industry makes the government invest a lot of manpower and material resource...

AI Technical Summary

Problems solved by technology

However, this processing method is greatly affected by noise and interference vibration, which makes the accuracy of identification unstable. Therefore, it is urgent to develop a new method for classification and identification of optical fiber intrusion signals.

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