滚动轴承噪声的灰自助动态评估

Dynamic Assessment for Noise of Rolling Bearing Using Grey Bootstrap

以灰预报和自助再抽样方法为基础,提出灰自助动态评估模型,用于评估滚动轴承的噪声。该模型用动态不确定度、估计区间、估计真值、平均不确定度、平均真值和趋势项测度6个参数,全面描述滚动轴承噪声的基本特征。计算机仿真和工程试验表明,该模型对随机变量的概率分布与趋势项的类型没有任何要求,在平均不确定度为最小的条件下,可有效地分离出趋势项,评估的可信度达到100%。

Based on grey prediction and bootstrap resampling, a model of dynamic assessment was proposed to evaluate noise of rolling bearings. The model characterized completely noise of rolling bearings by developing six parameters viz. dynamic uncertainty, estimated interval, estimated truevalue, mean uncertainty, mean true value, and trend measure. Computer simulation and engineering experiments show that the model can effectively separate trends with a minimum of the mean uncertainty, without any requirements for both the probability distribution of random variables and the type of trends. Reliability of assessment is proved to be 100%.