提出变异概率、变异速度和变异加速度等新概念，基于最大熵原理和泊松过程建立可靠性预测模型，对滚动轴承振动性能可靠性的变异过程进行预测。运用最大熵原理，计算本征序列中性能数据的概率密度函数；根据泊松过程，获得细分后时间序列中性能数据落在本征序列置信区间之外的变异个数和变异概率；对时间进行离散化处理，计算各个时间序列振动性能可靠性的变异速度和变异加速度。以滚动轴承(SKF6205)为例，进行滚动轴承振动加速度实验。试验结果表明：随着磨损直径的逐渐增大，可靠性变异概率呈非线性增长的趋势，总体上可分为初级磨合阶段、正常性能退化阶段和性能恶化阶段。而且，该可靠性预测模型可以分析乏信息条件下可靠性的变异过程，为现有的可靠性方法做出有益补充。
New concepts including variation probability,variation speed,and variation acceleration,were proposed and a reliability prediction model was established to predict the variation process of reliability of rolling bearing vibration performance based on the maximum entropy principle and Poisson process.The maximum entropy principle was applied to calculate the probability density function of sample data of the intrinsic sequence.According to Poisson process,variation number and variation frequency of performance data outside the confidence interval of intrinsic sequence were achieved for time series subdivided.Variation speed and variation acceleration of rolling bearing vibration performance were calculated by discrimination processing for time.The rolling bearing (type SKF6205) was used as an example to illustrate the applications of maximum entropy principle and Poisson process in analyzing variation process.Experimental investigation shows that the variation probability of reliability presents a nonlinear increase trend with the increase of wear diameter,which can be divided into initial running stage,normal performance degradation stage,and performance deterioration stage.Moreover,the reliability prediction model can be used to analyze variation process of reliability under the condition of poor information,which is proven to be a useful supplement to available reliability methods.
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