为对地铁监测数据进行科学分析,在传统“双控”指标分析方法的基础上,引入并改进统计过程控制(statistics process control,SPC)技术,建立新的分析方法。参考基础性国标GB 50068—2018《建筑结构可靠性设计统一标准》中的相关规定,明确...为对地铁监测数据进行科学分析,在传统“双控”指标分析方法的基础上,引入并改进统计过程控制(statistics process control,SPC)技术,建立新的分析方法。参考基础性国标GB 50068—2018《建筑结构可靠性设计统一标准》中的相关规定,明确SPC技术的理论依据3σ准则对应的假设检验显著性水平α=0.27%明显偏小。提出应该以α=5%建立适用于土木工程领域的分析准则,即2σ非连续准则;并将新准则与SPC结合,形成适用于地铁工程建设的监测数据分析方法。最后,基于工程实例验证了新方法的可行性。经研究可以明确:1)引入SPC可以充分利用监测数据,分析出传统分析方法不易识别出的数据变化特征;2)改进SPC技术更加满足地铁工程建设领域的基本要求,对数据的分析判定也更加严格。展开更多
The separation of anomalies from geochemical background is an important part of data analysis because lack of such identifications might have profound influence on or even distort the final analysis results. In this a...The separation of anomalies from geochemical background is an important part of data analysis because lack of such identifications might have profound influence on or even distort the final analysis results. In this article, 1 672 geochemical analytical data of 11 elements, including Cu, Mo, Ag, Sn, and others, from a region within Tibet, South China, are used as one example. Together with the traditional anomaly recognition method of using the iterative mean ±2σ local multifractality theory has been utilized to delineate the ranges of geochemical anomalies of the elements. To different degrees, on the basis of original data mapping, C-A fractal analysis and singularity exponents, Sn differs from the other 10 elements. Moreover, geochemical mapping results based on values of the multifractal asymmetry index for all elements delineate the highly anomalous area. Similar to other 10 elements, the anomalous areas of Sn delineated by the asymmetry index distribute along the main structure orientations. According to the asymmetry indexes, the 11 elements could be classified into 3 groups： （1） Ag and Au, （2） As-Sb-Cu-Pb-Zn-Mo, and （3） Sn-Bi-W. This parageneflc association of elements can be used to interpret possible origins of mineralization, which is in agreement with petrological analysis and field survey results.展开更多
文摘为对地铁监测数据进行科学分析,在传统“双控”指标分析方法的基础上,引入并改进统计过程控制(statistics process control,SPC)技术,建立新的分析方法。参考基础性国标GB 50068—2018《建筑结构可靠性设计统一标准》中的相关规定,明确SPC技术的理论依据3σ准则对应的假设检验显著性水平α=0.27%明显偏小。提出应该以α=5%建立适用于土木工程领域的分析准则,即2σ非连续准则;并将新准则与SPC结合,形成适用于地铁工程建设的监测数据分析方法。最后,基于工程实例验证了新方法的可行性。经研究可以明确:1)引入SPC可以充分利用监测数据,分析出传统分析方法不易识别出的数据变化特征;2)改进SPC技术更加满足地铁工程建设领域的基本要求,对数据的分析判定也更加严格。
基金jointly supported by the National Natural Science Foundation of China (Nos. 40525009, 40638041, 40502029, and 40373003)
文摘The separation of anomalies from geochemical background is an important part of data analysis because lack of such identifications might have profound influence on or even distort the final analysis results. In this article, 1 672 geochemical analytical data of 11 elements, including Cu, Mo, Ag, Sn, and others, from a region within Tibet, South China, are used as one example. Together with the traditional anomaly recognition method of using the iterative mean ±2σ local multifractality theory has been utilized to delineate the ranges of geochemical anomalies of the elements. To different degrees, on the basis of original data mapping, C-A fractal analysis and singularity exponents, Sn differs from the other 10 elements. Moreover, geochemical mapping results based on values of the multifractal asymmetry index for all elements delineate the highly anomalous area. Similar to other 10 elements, the anomalous areas of Sn delineated by the asymmetry index distribute along the main structure orientations. According to the asymmetry indexes, the 11 elements could be classified into 3 groups： （1） Ag and Au, （2） As-Sb-Cu-Pb-Zn-Mo, and （3） Sn-Bi-W. This parageneflc association of elements can be used to interpret possible origins of mineralization, which is in agreement with petrological analysis and field survey results.
