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轨交系统中的设施和设备主要包含了工务、供电、通信信号、车辆4大子系统,其中的检测手段广泛,涉及的标准众多。故障的检测、综合分析的基础是预报警数据的过滤和检索,上层平台开展工作的基础就是将海量数据中的异常数据过滤出来形成安监事件。本文运用模糊理论的隶属函数,论述参数模糊标准和自然语言如何被翻译成检测标准,从而触发安监事件,进而形成综合分析、诊断和工单。
The facilities and equipment in the rail transit system mainly include four major sub-systems of public works, power supply, communication signals and vehicles, among which there are a wide range of testing methods and many standards involved. Fault detection, comprehensive analysis is based on the pre-alarm data filtering and retrieval, the basis for the work carried out by the upper platform is to filter out abnormal data in a large amount of data to form a safety and security incident. This paper uses membership function of fuzzy theory to discuss how parameter fuzzy standard and natural language are translated into testing standards so as to trigger safety monitoring events and form comprehensive analysis, diagnosis and work order.