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Short-term fault prediction of mechanical rotating parts on the basis of fuzzy-grey optimising method

机译：基于模糊灰色优化方法的机械旋转零件短期故障预测

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摘要

This paper presents a multidimensional fault characteristic parameter model for rotating parts for the purpose of mechanical fault diagnosis technology. Specifically, a fuzzy-grey optimising prediction method is presented to foretell short-term faults. The method is able to set up a prediction model with as few as four data and also can effectively handle the non-linearity of prediction data. The optimising factor τ{sup}* is determined to make the prediction data closest to the original data. Taking a rolling bearing of an oil-line pump as an example to forecast its fault characteristic parameters and comparing with GM(1,1), the experiment results show that ideal effects of precision examination have been obtained, and the method proves feasible and practical.
机译：为实现机械故障诊断技术，本文提出了一种旋转零件的多维故障特征参数模型。具体地，提出了一种模糊灰色优化预测方法来预测短期故障。该方法能够建立少至四个数据的预测模型，并且还可以有效地处理预测数据的非线性。确定优化因子τ{sup} *以使预测数据最接近原始数据。以某油泵滚动轴承为例，预测其故障特征参数，并与GM（1,1）进行比较，实验结果表明，该方法取得了理想的精度检验效果，证明了该方法的可行性和实用性。 。

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