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本文主要研究了灰色理论在大型旋转机械的状态监测与故障诊断中的方法与应用问题。鉴于一般关联度分析方法在故障诊断应用中没有考虑到特征参数对诊断结果的不同影响,本文提出了加权关联度这一新概念,并给出了加权关联度用于旋转机械诊断中的方法与步骤。这种诊断方法能根据诊断结果采用自学习修正方法来修正关联度参数,提高诊断的准确度,并有很好的前景。
This paper mainly studies the gray theory in the large-scale rotating machinery condition monitoring and the breakdown method and the application question. Since the general relevance analysis method does not consider the different influence of the characteristic parameters on the diagnosis results in the fault diagnosis application, a new concept of weighted association degree is proposed in this paper, and the method of weighted association degree used in the diagnosis of rotating machinery is given step. This diagnostic method based on diagnostic results using self-learning correction method to correct the correlation parameters to improve the diagnostic accuracy, and has good prospects.