多传感器测量数据预处理

传统传感器测量数据处理方法只采用算术平均值的数字滤波法,虽然这种方法具有一定的抗干扰性,但从统计理论和实际应用情况分析来看,这种方法处理的数据不是测量结果的最好表示,尤其对于多传感器测量情况甚至更糟糕.针对这种情况提出了通过2次利用偏度分析建立动态检测门限判别并剔除粗差,再进行数据融合的分批估计方法.数据分析结果表明,这样处理后的数据测量误差和方差均更小,测量结果更接近测量真值.     

Skewness correction X̄ and R charts for skewed distributions

This paper proposes a skewness correction (SC) method for constructing the and R control charts for skewed process distributions. Their asymmetric control limits (about the central line) are based on the degree of skewness estimated from the subgroups, and no parameter assumptions are made on the form of process distribution. These charts are simply adjustments of the conventional Shewhart control charts. Moreover, the chart is almost the same as the Shewhart chart if the process distribution is known to be symmetrical. The new charts are compared with the Shewhart charts and weighted variance (WV) control charts. When the process distribution is in some neighborhood of Weibull, lognormal, Burr or binomial family, simulation shows that the SC control charts have Type I risk (i.e., probability of a false alarm) closer to 0.27% of the normal case. Even in the case where the process distribution is exponential with known mean, not only the control limits and Type I risk, but also the Type II risk of the SC charts are closer to those of the exact and R charts than those of the WV and Shewhart charts. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 555–573, 2003     

基于前四阶矩的非高斯响应概率密度函数逼近方法研究

基于响应前四阶统计矩研究了在偏态系数和峰度系数取值范围不同时Gram-Charlier渐进展式、Edgeworth渐进展式和Fleishman多项式3种非高斯概率密度函数,指出3种方法的适用条件。结果表明与Gram-Charlier和Edgeworth渐进展式相比,Fleishman多项式对峰度系数的变化不敏感,该方法只有在峰度系数与高斯分布一致时拟合的结果才有可能是合理的;Gram-Charlier和Edgeworth渐进展式在中、高度偏态情况下易出现负的概率,二者在低等偏态情况下拟合的结果是比较合理的。两算例表明在高等偏态、尖峰和对称、扁平分布情况下,Gram-Charlier和Edgeworth渐进展式拟合结果优于Fleishman多项式,但Gram-Charlier渐进展式易于出现负的概率,在应用时应引起注意。