人工智能方法在热模锻压力机故障诊断技术中的应用

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为提高热模锻压力机生产过程中故障诊断的效率,对热模锻压力机的故障机理进行了分析;应用规则推理与案例推理的智能方法对热模锻压力机的故障诊断进行研究。结合热模锻压力机的特点并针对两种推理技术各自的局限性,提出了将规则推理与案例推理相结合的、适用于热模锻压力机故障诊断的人工智能方法;构建了热模锻压力机生产过程中故障诊断的故障树,并得到导致故障现象的最小割集;建立了表示故障案例的五元组,以离合器打滑与制动器打滑为例进行案例推理的分析。本研究在一定程度上解决了知识获取困难的问题。 In order to improve the efficiency of fault diagnosis in the process of hot die forging press, the failure mechanism of hot die forging press was analyzed. The fault diagnosis of hot die forging press was studied by using rule reasoning and case reasoning intelligent method. Combined with the characteristics of hot die forging press and the limitations of each of the two inference technologies, an artificial intelligence method that combines rule reasoning with case reasoning and is suitable for fault diagnosis of hot die forging presses is proposed. The fault tree of the fault diagnosis in the process of the press is obtained, and the minimal cut set that leads to the fault phenomenon is obtained. The quintuple representing the fault case is established, and the case inference is analyzed by taking the clutch slip and the brake slip as examples. To a certain extent, this study solves the problem of knowledge acquisition difficulties.
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