地下管线监测系统振动信号识别研究

Underground Pipeline Monitoring System for Vibration Signal Recognition Research

地下管线监测技术对于保障管线的安全运行具有重要意义,现有的声波预警系统存在识别误报率较高等问题,本文对声波监测系统在数据处理算法方面进行优化改进。振动信号识别系统是基于神经网络模式识别技术开发的,智能分析系统能对收到的信号进行分类处理,并能够自动学习人工处理模式,逐步修正判别误差,加强信号判别的准确程度。通过现场测试验证所提算法的有效性和可行性均得到了提高。

Underground pipeline monitoring technology is of great significance to protect the safety of pipeline operation,the existing acoustic warning system is to identify the problem of high rate of false positives,in this paper,the acoustic monitoring system in the aspect of data processing algorithm is optimized to improve. Vibration signal recognition system is developed based on the neural network pattern recognition technology,intelligent analysis system can classify the received signal processing,and can automatically learn artificial processing mode,step by step discriminant error correction,the accuracy of the reinforcement signal discrimination. The effectiveness and feasibility of the proposed algorithm are improved by field test.