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Structure Design of Intelligent Fault Diagnosis System Based on Data Mining

机译:基于数据挖掘的智能故障诊断系统结构设计

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To solve the limitations of intelligent fault diagnosis system, a new intelligent fault diagnosis method based on data mining is presented. After a brief discussion of the general structure of Intelligent Fault Diagnosis System based on Data Mining (IFDSDM), the function of its subsystem is described, followed with the structure of knowledge base and the method of knowledge representation. IFDSDM efficiently integrates the knowledge acquisition, reasoning mechanism, IKDD (improved knowledge discovery in databases system) mining and Web-based open fault diagnosis system into IFDS. Thus, IFDSDM is a new type of integrated intelligent fault diagnosis system with two networks and six bases. It improves and expands the function of conventional IFDS. What's more, it overcomes some of the limitations of IFDS.
机译:为解决智能故障诊断系统的局限性,提出了一种基于数据挖掘的新的智能故障诊断方法。在简要讨论基于数据挖掘(IFDSDM)的智能故障诊断系统的一般结构之后,描述了其子系统的功能,随后是知识库的结构和知识表示的方法。 IFDSDM有效地集成了知识获取,推理机制,IKDD(在数据库系统中改进了知识发现)挖掘和基于Web的开放故障诊断系统到IFDS中。因此,IFDSDM是一种新型的集成智能故障诊断系统,具有两个网络和六个基础。它改进并扩展了传统IFD的功能。更重要的是,它克服了IFDS的一些局限性。

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