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在工程应用中的振动信号大多为非线性非平稳信号,为了能充分利用工程中采集的振动信号中的信息,以kolmogorov-smirnov检验为基础,提出了以K-S距离作为机械设备各退化状态退化指标的方法.根据经验设定机械设备完全失效对应的退化指标的阈值,用退化指标序列训练灰色模型,然后用训练好的模型预测退化指标的变化趋势,从而估计退化指标到达设定阈值时的时间并以此作为机械设备的剩余使用寿命.最后通过轴承的全寿命周期振动信号对其验证,结果表明所提出的预测方法可以有效地预测轴承的剩余寿命.
Abstract：Most of practical signals are nonlinear and non-stationary.In order to make full use of information contained in vibration signal,a K-S distance was proposed as a degradation index.Corresponding threshold degradation index was set first according to experience,degradation index sequence was used to train gray model,and the model was used to predict the trend of degradation index so as to to predict the residual useful life.Finally,validated with the bearing entire life vibration signal,the results show that the proposed prediction method can effectively predict the remaining life of the bearing.
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基本信息:
中图分类号:TB533.1
引用信息:
[1]马海波,周东健,黄希,等.基于K-S距离的GM(1,1)的机械设备剩余寿命预测[J],2013,12(04):82-86.
基金信息:
江苏省自然科学基金资助项目(BK2011391);; 南通市应用研究计划项目(BK2012020,BK2013026)