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Research on Reliability Modeling of CNC System Based on Association Rule Mining

机译:基于关联规则挖掘的数控系统可靠性建模研究

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Lifetime failure data is often used in reliability modeling because of its advantage of convenient collection, but relatively large errors always existed when ignoring importance of failure correlation in reliability modeling for multiple failure positions and causes. Therefore, a reliability modeling based on degree of failure correlation was proposed, and failure correlation factor is introduced into parameter estimation part to fully reflect reliability information of lifetime failure data in reliability modeling. Then, using association rule mining technology, based on lifetime failure data to study failure correlation factor between failure positions and failure causes of CNC system. Finally, the study results show that the model which introduces failure correlation factor is suitable for modeling lifetime failure data of CNC system with multiple failure modes and causes.
机译:终生故障数据由于其方便收集的优点而经常用于可靠性建模,但是当忽略故障关联在多个故障位置和原因的可靠性建模中的重要性时,始终存在相对较大的错误。因此,提出了一种基于失效相关度的可靠性建模方法,并将失效相关因子引入参数估计部分,以充分反映寿命建模中寿命失效数据的可靠性信息。然后,运用关联规则挖掘技术,基于寿命失效数据,研究数控系统失效位置与失效原因之间的失效相关因子。最后,研究结果表明,引入故障相关因子的模型适用于具有多种故障模式和原因的数控系统的生命周期故障数据建模。

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