基于SVM的机场供水管网泄漏辨识定位系统研究

Study on position system of leakage identification for water supply network at airport based on SVM

针对供水管网泄漏辨识定位系统,研究了以管网压力、流量参数形成的时间序列数据为基础,应用支持向量机方法建立漏损辨识模型,采用粒子群算法对支持向量机中的c、g参数进行优化,最终通过压力梯度法实现漏点的准确定位。结果表明:所建立模型对管网漏损辨识定位的准确率较高,满足供水管网漏损监测的要求。

Aimed at the position system of leakage identification of water supply pipeline,based on the time series data witch are formed by pipe network pressure and flow parameters,the paper applied support vector machine method to set up leakage identification model. By using particle swarm algorithm to optimize the parameter c,g in support vector machine（ SVM）,it eventually realized accurate positioning through using the method of pressure gradient. The experiment shows that the accuracy of established model of pipeline leakage positioning is higher and can meet the requirements of leakage monitoring of water supply pipe network.