基于贝叶斯理论的城市管网故障检测模型

Urban Network Malfunction Monitoring Model Based on Bayesian Theorem

随着现在城市信息化建设的加快,城市的正常运转离不开城市地下管网的支持。但是城市地下管网一般规模较大,分布范围广阔,而且故障发生时具有相当的隐蔽性。因此,给城市的发展和社会财富带来严重的隐患。城市管网的故障识别及定位技术一直是近些年来相关企业的研究热门。基于SCADA系统检测到的数据,引进统计学概率论中的基本定理—贝叶斯定理来建立管网的在线检测与定位模型,用以帮助对城市管网的运行状态进行分析检测,并对故障进行定位。一定程度上解决了模拟误差、测量误差、测点配置等不确定因素所带来模型检测数据的不确定性问题。

With the accelerating of informatization in city now,normal operation of a city will not go well without the support of the urban network. However,the scale of urban network is huge,while the network is widely distributed and equipped with concealed problems when fault occurs. Thus,it brings serious hidden troubles to the city’ s development as well as social fortune. For recent years,the technol-ogy of monitoring urban network malfunction and positioning has been a hot research project in related enterprises. Build up a online mo-nitoring and positioning system of network based on data seized by SCADA system and Bayesian theorem which is the basic theorem in statistical probability theory to analyze and detect the running state of urban network as well as positioning malfunction. To some degree the model solves the uncertainty of data detected by model brought by uncertain factors such as simulation error,measurement error or measuring point configuration.