样本量对滚动轴承振动性能变异过程评估的影响

以轴承全寿命周期内的振动时间序列为研究对象,构建最大熵泊松评估模型以研究滚动轴承振动性能的演变历程。将振动时间序列分为不同的段数,基于最大熵原理和泊松过程,计算各个振动时间序列相对本征时间序列的变异概率、性能保持可靠度及其变异速度和变异加速度等指标；分析各个性能变异指标与样本量的关系,从而选取合适的样本量；用动态平均不确定度分析性能保持可靠性评估结果的不确定性。结果表明:针对案例1和案例2,将样本量分别选取为800~1000和500~900,既可以使本征序列数据样本蕴含足够的振动信息；又可以对轴承振动性能的具体变异过程进行有效地评估。 

Effect of sample size on evaluation of variation process of rolling bearing vibration performance

Based on the vibration time series during the life cycle of rolling bearings, a maximum entropy Poisson evaluation model was constructed to study the evolution process of rolling bearing vibration performance. The vibration time series were divided into different segments, and then the variation probability, vibration performance maintaining reliability and their variation speed and acceleration were calculated based on maximum entropy principle and Poisson process for each vibration time series in relation to the intrinsic series. The relationships between performance variation indexes and sample size were analyzed to select the appropriate sample size. Dynamic average uncertainty was used to analyze the uncertainty of evaluation results of performance maintaining reliability. Result showed that the sample sizes of 800-1000 and 500-900 were selected respectively, for case 1 and case 2, which can make the intrinsic series data sample contain enough vibration information, but also effectively evaluate the specific variation process of bearing vibration performance.