重复动态测量数据不确定度的灰色加权评定方法研究

Research on the Gray Weight Method for Evaluating the Uncertainty of Repetitive Dynamic Measurement Data

为提高动态测量不确定度评定的准确度,基于灰色关联分析理论,提出了一种动态测量不确定度的灰色加权评定新方法。此方法通过灰色加权序列体现动态测量序列不同采样点的分散性,采用最大残差区间来表征数据的最大分散区间,再利用灰色加权序列对最大残差区间进行概率加权,将加权结果作为标准动态测量不确定度。经试验分析,灰色加权评定方法可较好地评定动态测量数据的不确定度,且计算量小、评定准确度高,适合处理小样本动态测量数据不确定度评定问题,具有较高的实用价值。

In order to boost the precision of uncertainty evaluation of dynamic measurement,based on gray relation analysis theory,the new method of gray weighting for dynamic measuring uncertainty is proposed.With this method,through gray weighting alignment to show the distribution of different sampling points in dynamic measurement alignment,and use maximum residual error interval to show the maximum data distributed interval;then through gray weighting alignment again,to weight the maximum residual error interval,and the result is used as standard dynamic measurement uncertainty.The experimental analysis indicates that this gray weighting evaluation method better evaluates the uncertainty of the dynamic measurement data,and the calculation labor is less,while the evaluation accuracy is high,it is suitable for uncertainty evaluation for processing small sample dynamic measurement data,and offers higher applicable value.