Detection of the abnormal events along the oil and gas pipeline and multi-scale chaotic character analysis of the detected signals

This paper studies the monitoring principle of abnormal events along oil and gas pipelines, which is conducted by a Mach?Zehnder optical fiber interferometer based distributed optical fiber pipeline pre-warning system. The detected signals of three typical abnormal events are analyzed by a multi-scale chaotic character analysis method based on orthogonal wavelet packet decomposition. In this pre-warning system, an optical cable is laid parallel to the pipeline in the same ditch and three single mode optical fibers in the optical cable make up the distributed micro-vibration measuring sensor. Using this system, leakage and other abnormal events can be detected by the sensor in real time and located with good precision. By orthogonal wavelet packet decomposition, the detected signals are analyzed by a multi-scale chaotic character analysis method, which calculates the correlation dimension under different frequency scales, resulting in more distinguishable differences among the three kinds of signals. The method proves more effective in recognizing the typical abnormal events by signals obtained from the experiment field.