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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CNC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:寿命故障数据通常用于可靠性建模,因为它的优势,集合方便,但在忽略可靠性模型中的失效相关性以进行多种故障位置和原因时,始终存在相对大的误差。因此,提出了基于故障相关程度的可靠性建模,并且将故障相关因子引入参数估计部分,以完全反映可靠性建模中的寿命故障数据的可靠性信息。然后,使用关联规则挖掘技术,基于寿命故障数据研究CNC系统故障位置与故障原因之间的故障相关因子。最后,研究结果表明,引入故障相关因子的模型适用于使用多种故障模式和原因建模CNC系统的寿命故障数据。

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