Fault Diagnosis of CNC Machine Tool Based on Bayesian Formula

Ying Yu, Ming Chen, Ying Lei Li
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Abstract

Bayesian formula is used to determine diagnosis sequence when several fault trees meet requirements. Bayesian prior probability is usually determined through expert or the user's subjective judgment and historical experience. If there is lack of expert experience, the determination of priori probability is very difficult. A real-time priori probability calculation method is proposed, which needn’t any priori-knowledge and can regulate automatic on the monitoring parameters. It takes into account the multiple diagnosis impact and more flexible than fixed priori probability according application.
基于贝叶斯公式的数控机床故障诊断
当多个故障树满足要求时,采用贝叶斯公式确定诊断顺序。贝叶斯先验概率通常是通过专家或用户的主观判断和历史经验确定的。如果缺乏专家经验,先验概率的确定是非常困难的。提出了一种实时先验概率计算方法,该方法不需要任何优先级知识,可以对监测参数进行自动调节。它考虑了多重诊断的影响,根据应用比固定的先验概率更灵活。
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