An SVM-Based Recognition Method for Safety Monitoring Signals of Oil and Gas Pipeline

2018 3rd International Conference on Insulating Materials, Material Application and Electrical Engineering

材料科学;无线电电子学;电工学

Chen, Yang^1 ; Zhao, Jianhui^1 ; Li, Fan^1

School of Instrumentation Science and Optoelectronics Engineering, Beihang University, Beijing

100191, China^1

关键词: Distributed optical fiber;    Empirical risk minimization;    Oil-and-Gas pipelines;    Optical fiber interferometers;    Recognition methods;    Threshold de-noising;    Traditional learning;    Wavelet Packet Decomposition;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/452/3/032008/pdf
DOI  :  10.1088/1757-899X/452/3/032008

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

An SVM-based recognition method for the safety of oil and gas pipeline was proposed due to limitation of the traditional learning methods based on empirical risk minimization. The vibration signals along the pipelines are obtained with the distributed optical fiber vibration sensor on the basis of Mach-Zehnder optical fiber interferometer theory. The wavelet packet threshold denoising is used to preprocess the signal. Then the eigenvectors of vibration signals were extracted through the energy-pattern method based on wavelet packet decomposition. At last the vibration signals were recognized by support vector machine (SVM) through the eigenvectors with a view to detecting whether abnormal events happened along the pipelines.