赵会军, 武伟强, 王克华, 王小兵, 周宁, 王树立. 基于次声波法的油气管道泄漏检测与定位[J]. 油气储运, 2012, 31(3): 215-218. DOI: 10.6047/j.issn.1000-8241.2012.03.016
引用本文: 赵会军, 武伟强, 王克华, 王小兵, 周宁, 王树立. 基于次声波法的油气管道泄漏检测与定位[J]. 油气储运, 2012, 31(3): 215-218. DOI: 10.6047/j.issn.1000-8241.2012.03.016
Zhao Huijun, Wu Weiqiang, Wang Kehua, Wang Xiaobing, Zhou Ning, Wang Shuli. Infrasonic wave-based leakage detection and location technology for oil & gas pipelines[J]. Oil & Gas Storage and Transportation, 2012, 31(3): 215-218. DOI: 10.6047/j.issn.1000-8241.2012.03.016
Citation: Zhao Huijun, Wu Weiqiang, Wang Kehua, Wang Xiaobing, Zhou Ning, Wang Shuli. Infrasonic wave-based leakage detection and location technology for oil & gas pipelines[J]. Oil & Gas Storage and Transportation, 2012, 31(3): 215-218. DOI: 10.6047/j.issn.1000-8241.2012.03.016

基于次声波法的油气管道泄漏检测与定位

Infrasonic wave-based leakage detection and location technology for oil & gas pipelines

  • 摘要: 基于次声波法的管道泄漏检测与定位,是通过检测泄漏流体湍射流作用于管壁产生的次声波而进行泄漏检测与定位。对管道泄漏时检测到的低频声波信号进行分析,泄漏信号在频域的特征表现在10 Hz以内,因此选择0.4 Hz、3.8 Hz和7.2 Hz的次声波特征频率作为检测特征量。当发现信号中同时存在两个特征频率功率谱及其能量顺序比率突变时,及时将异常数据及其GPS时间发送给监控主机。监控主机根据接收到的一端基站发送的异常发生时的GPS时间,结合被监控管道的长度和泄漏信号的传播速度,计算出另一端基站捕捉到异常信号的起始时间和数据长度,并向该端基站呼叫对应时间段的数据,然后联合两端数据,依据神经网络模型进行泄漏诊断。根据两端基站检测到异常信号发生的GPS时间的时间差,次声波传播速度和上、下游传感器之间的距离,可以确定泄漏点的具体位置。

     

    Abstract: Infrasonic wave-based leakage detection and location technology for oil & gas pipelines is a way, which detects the infrasonic wave signal generated by the jetting fluid acted on pipe walls to inspect and locate the leakage point. The infrasonic wave frequency at 0.4 Hz, 3.8 Hz and 7.2 Hz are taken as test characteristic because the frequency domain characteristic of leakage signal is within 10 Hz. The abnormal data and GPS time will be sent to a center monitor after the mutation of 2 power spectrum of characteristic frequencies and changed energy order ratios themselves are detected, the center monitor calculates the start-time and data length of captured anomalous signals from the other end stations, then calls the data from the end stations, and makes further leakage diagnoses according to the two ends data and neural network model. Meanwhile, the leakage points can be located according to the GPS time lag of anomalous signals from the two stations, the propagation velocity of infrasonic wave and the monitored length of pipeline.Key words: pipeline, infrasonic wave, leakage detection, location

     

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