伊廷华, 郭庆, 李宏男. 基于控制图的GPS异常监测数据检验方法研究[J]. 工程力学, 2013, 30(8): 133-141. DOI: 10.6052/j.issn.1000-4750.2012.04.0280
引用本文: 伊廷华, 郭庆, 李宏男. 基于控制图的GPS异常监测数据检验方法研究[J]. 工程力学, 2013, 30(8): 133-141. DOI: 10.6052/j.issn.1000-4750.2012.04.0280
YI Ting-hua, GUO Qing, LI Hong-nan. THE RESEARCH ON DETECTION METHODS OF GPS ABNORMAL MONITORING DATA BASED ON CONTROL CHART[J]. Engineering Mechanics, 2013, 30(8): 133-141. DOI: 10.6052/j.issn.1000-4750.2012.04.0280
Citation: YI Ting-hua, GUO Qing, LI Hong-nan. THE RESEARCH ON DETECTION METHODS OF GPS ABNORMAL MONITORING DATA BASED ON CONTROL CHART[J]. Engineering Mechanics, 2013, 30(8): 133-141. DOI: 10.6052/j.issn.1000-4750.2012.04.0280

基于控制图的GPS异常监测数据检验方法研究

THE RESEARCH ON DETECTION METHODS OF GPS ABNORMAL MONITORING DATA BASED ON CONTROL CHART

  • 摘要: 为了有效地判别GPS异常监测数据,建立了GPS监测序列异常检验的数学模型,提出利用统计过程控制中的控制图对监测序列进行异常检验和预警的新方法;针对GPS监测数据不服从正态分布的问题,提出利用累积分布函数的核密度估计将其转换为Q统计量,并以此为基础构建基于Q统计量的控制图用于GPS异常波动数据的检验;该文文末利用仿真数据对比分析了休哈特控制图与累积和控制图对不同异常偏移值的检验效果,结果表明两种控制图各有利弊、相互补充,休哈特控制图对于3倍以上标准差的异常偏移能够给出有效的预警,但缺乏小偏移检测的能力,累积和控制图能够精确检测出最小达0.5倍标准差的连续小偏移,但是随着偏移值的增大其误警率会有所增加。

     

    Abstract: In order to effectively detect GPS abnormal monitoring data, a mathematical model for the GPS observations outlier detection is established. A new method for outlier detection and early-warning of observations by controlling a chart in the statistical process is proposed. Since the GPS monitoring data are not normally distributed, transferring them to Q statistic by Kernel density estimation of cumulative distribution functions is raised, and based on this, the control chart of Q statistic used for GPS abnormal data detection is constructed. Finally, the detection capacity of a Shewhart control chart and a cumulative sum control chart on different abnormal offsets are compared and analyzed based on the simulation data. The results show that the two control charts offer certain advantages and complement each other. The Shewhart control chart is able to provide effective early-warning for the abnormal offsets 3 times of the standard deviations, but it is lacking in the detection capacity of small offsets; while the cumulative sum control chart can accurately detect the continuous small offsets even smaller as 0.5 times of the standard deviations, but the false alarm rate may be bigger with the increase of the offsets.

     

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