密闭空间爆炸温度动态不确定度评估方法研究

融合了灰色模型GM(1,1)、Bootstrap方法以及不确定度评定理论,建立了密闭空间内爆炸温度动态测量不确定度的灰自助评估模型GBM(1,1),选取某次爆炸试验300s的温度数据作为分析数据,运用估计真值、估计区间和平均不确定度等参数表征其估计结果。实验结果表明,GBM(1,1)模型融合了灰色模型GM(1,1)和Bootstrap方法的优势,可以准确模拟动态测量数据的概率分布,并实时跟踪被测量瞬时值的变化趋势。相比于灰色模型GM(1,1)和Bootstrap方法,灰自助模型GBM(1,1)具有更高的真值估计准确度和区间估计可靠度,其估计误差分布区间为［-12.62, 13.58］,标准差为8.69℃,最大相对误差为1.2%,区间估计可靠度高于90%,估计区间能够较完整地包络被测量的动态波动范围。由此证明GBM(1,1)模型能够对密闭空间内爆炸温度的动态测量不确定度做出准确评估。

Study on Evaluation Method for Dynamic Uncertainty ofExplosion Temperature in Confined Space

Combining the grey model GM (1,1) with the bootstrap method and the uncertainty evaluation theory, a grey bootstrap evaluation model GBM (1,1) for dynamic measurement uncertainty of the explosion temperature in confined space was constructed by. A 300s temperature data in an explosion test were selected as the analysis data. Parameters such as the estimated true value, the estimated interval, and the mean uncertainty were used to characterize the estimation results. The results of this study indicate that the GBM (1,1) model, which combines the strengths of the GM (1,1) grey model and bootstrap method, can accurately model the probability distribution of the dynamic measurement data and track the variation trends of the measured instantaneous values in real time. Compared with the grey model GM (1,1) and bootstrap method, the grey bootstrap model has higher truth estimation accuracy and interval estimation reliability. The estimated error distribution range is ［-12.62, 13.58］, the standard deviation is 8.69℃, and the maximum relative error is 1.2%. Its interval estimation reliability exceeded 90%, and the estimated intervals fully enveloped the dynamic fluctuation range of the measured quantity. It proves that the GBM (1,1) model can evaluate the dynamic measurement uncertainty of the explosion temperature in confined space.