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作 者:李兴[1] 李艳玲[1] 张鹏 杨哲 LI Xing;LI Yan-ling;ZHANG Peng;YANG Zhe(State Key Laboratory of Hydraulics and Mountain River Engineering,College of Water resource and Hydropower,Sichuan University,Chengdu 610065,China;No.1 Design and Research Sub-institute,Southwest Municipal Engineering Design and Research Institute of China,Chengdu 610081,China)
机构地区:[1]四川大学水力学与山区河流开发保护国家重点实验室水利水电学院,成都610065 [2]中国市政工程西南设计研究总院有限公司第一设计研究院,成都610081
出 处:《中国农村水利水电》2019年第8期133-136,共4页China Rural Water and Hydropower
摘 要:监测数据是反映大坝安全的直观手段,数据序列的精度对安全评价、隐患预警影响较大。传统的监测数据粗差识别常采用的Pauta准则仅对具有特定分布规律(正态或近似正态分布)的数据序列精度较高,而对于含较多离群点的序列则容易出现异常值漏判的问题。提出了基于M估计的改进Pauta准则,以位置M估计量和基于位置M估计量的尺度估计量代替均值和标准差构造控制函数,克服了传统识别方法的精度易受离群点影响的问题,有效解决了异常值漏判的问题。将改进Pauta准则应用于耿达水电站不同类型的监测序列,应用结果表明基于M估计改进的Pauta准则粗差识别精度和适用性较传统Pauta准则提升明显。Monitoring data is an intuitive means to reflect the safety of the dam,and the accuracy of data sequence has a great impact on the safety evaluation and early warning.The traditional Pauta criterion for monitoring data gross error identification is only accurate for data sequences with specific distribution(normal or approximate normal distribution),while it is prone to miss out for sequences with more outliers.Accordingly,an improved Pauta criterion based on M-estimation is proposed.The control function is constructed by replacing the mean and standard deviation with the location M-estimator and the scale estimator based on location M-estimation,which effectively overcomes the problems that the accuracy of the traditional identification method is susceptible to the outliers and missing judgement of outliers.The improved Pauta criterion is applied to different types of monitoring sequences of the Gengda Hydropower Station.The application results show that the improved accuracy and applicability of the Pauta criterion based on the M-estimation is significantly improved compared with the traditional Pauta criterion.
关 键 词:安全监测数据 Pauta准则 位置M估计量 尺度估计量
分 类 号:TV698.1[水利工程—水利水电工程]
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