基于小波能谱和小波信息熵的管道异常振动事件识别方法

提出了基于小波能谱和小波信息熵的油气管道异常振动事件识别方法。基于Mach-Zehnder光纤干涉仪原理的分布式光纤油气管道安全监测系统实时检测管道沿途振动信号,对测量的时间序列进行小波变换,根据小波系数计算小波能谱与小波信息熵,通过小波能谱和小波信息熵值两种测度识别不同的管道安全异常事件。港枣线成品油管道的现场实验结果表明,该方法可以快速有效地识别管道周围发生的泄漏及其他异常情况,其总体识别准确率达到98.5%,有效降低了误报警率,具有较强的在线工况识别能力。

A recognition method with wavelet energy spectrum and wavelet information entropy for abnormal vibration events of a petroleum pipeline

A recognition method for safety-detection events of oil and gas pipeline based on the wavelet energy spectrum and wavelet information entropy is studied, which is used in the distributed optical fiber oil and gas pipeline safety detection system based on the principle of Mach-Zehnder optical fiber interferometer for the safety of oil and gas pipeline. In this pre-warning system an optical cable is laid along the pipeline in the same ditch and three single mode optical fibers in the optical cable build up the distributed micro-vibrant measuring sensor. The vibration signal caused by Leakage and other abnormal events can be detected by the system in real-time. The detection signals of abnormal events were decomposed into sub signals in different frequency band by use of wavelet transform with multi-resolution analysis. Thus both frequency band energy features and wavelet information entropy of above-mentioned detection signals are extracted; the system can recognize abnormal intrusion events which have occurred along the pipeline through the wavelet energy spectrum and wavelet information entropy in real-time. Finally, the experimental data obtained at GangZao products pipeline are used to evaluate the method and the overall recognition accuracy rate achieves 98.5％, which proves the feasibility and effectiveness of this method.