基于经验模态分解的管道预警系统信号多尺度混沌特性分析方法

提出了一种用于油气管道安全预警系统的检测信号多尺度混沌特性分析的新方法。该预警系统基于Mach-Zehnder光纤干涉仪原理,沿管道同沟敷设一条光缆,利用其中的三条单膜光纤构成分布式微振动测试传感器,实时检测管道沿途发生的泄漏及其他异常事件。多尺度混沌特性分析方法是利用经验模态分解(EMD)方法对典型的异常事件振动信号进行分解,再分别对分解得到的固有模态(IMF)分量进行混沌特性分析,计算出不同尺度下的关联维数。该方法可更清晰地描述检测信号在不同尺度下的混沌特性。利用现场试验得到的信号对该方法进行验证的结果表明,利用多尺度混沌特性分析方法更容易有效地区分几种典型异常事件。

Multi-scale chaotic characteristic analysis of detection signals in pipeline pre-warning system based on empirical mode decomposition

A multi scale chaotic characteristic analysis method was proposed based on the empirical mode decomposition (EMD) for analyzing the detected signals in oil gas pipeline pre warning system. The pre warning system was based on the principles of Mach Zehnder optical fiber interferometer. An optical cable laid along the pipeline in the same ditch and three single mode optical fibers in the optical cable were made up the distributed micro vibrant measuring sensor to detect the leakage and other abnormal events along the pipeline in realtime. The vibration signals of abnormal events were decomposed by the EMD method. The components of intrinsic mode function (IMF) obtained from the EMD were analyzed by using the multi scale chaotic characteristic analysis method, and the correlation dimensions under different scales were calculated. This method can characterize the chaotic traits of the detected vibration signals more clearly. The field signal test proved that this method was more effective in recognizing the typical abnormal events. 