连续压实检测指标概率分布模型研究

Study on Probability Distribution Models of Continuous Compaction Indicators

基于某路基的现场压实试验数据,以连续压实指标CMV为分析变量,考虑CMV影响因素的基础上对数据进行筛选,利用常用概率模型进行统计分析,初步得到数据所符合的概率分布模型后,引入离散概率,利用散点图来进行概率择优.结果表明CMV指标最符合对数正态分布,在该模型的基础上确定了最优的碾压遍数,为该路基段连续压实质量检测提供了参考依据.

CMV is an indicator of continuous compaction control （CCC）.The major purpose of the paper is to investigate the probability models of CMV and find the optimal rolled times based on the data of a subgrade site.Several methods were used to filter the CMV data and the discrete probability was used to find the most accurate probability model.After analyzing the final CMV data,the results shows that the lognormal distribution is the most accurate distribution.Based on the model,the result of optimal rolled times was found as six times.The result of the paper provide a reference for the subgrade continuous compaction.