应用分布式光纤进行酸性气体管道健康监测

Application of distributed fiber optics for acid gas pipeline health monitoring

酸性气体管道泄漏危害巨大,管道运行状态监控尤为重要。采用分布式光纤传感器对管道进行健康监控,并采集无外部扰动、管道泄漏及第三方入侵三种情况下的声音信号。对采集的声音信号进行分析,达到对不同入侵信号准确分类的目的,进而为酸性气体管道的在线监控提供理论基础。采用小波包分解算法提取各子频能量特征组成特征向量,并用卡方检验的方法挑选相关特征,用三个隐藏层的BP神经网络模型作为信号分类器,其分类准确率达到99.5%。

The leakage of acid gas pipeline is very harmful,so the monitoring of pipeline operation atatus is particularly important.The distributed acoustic sensing is used to monitor the health of the pipeline and collect sound signals under three conditions:no external disturbance,pipeline leakage and third-party intrusion.The collected sound signals are analyzed to achieve the purpose of accurate classification of different intrusion signals,thus providing a theoretical basis for online monitoring of acid gas pipelines.The wavelet packet decomposition algorithm is mainly used to extract the sub frequency energy features to form the feature vector,and the chi-square test method is used to select the relevant features.The BP neural network model with three hidden layers is used as the signal classifier,with the classification accuracy of 99.5%.