基于统计诊断的大坝监测数据合理性检验

基于统计诊断的异常数据划分,并结合大坝监测数据的误差成因,将监测的异常数据划分为随机误差、粗差、系统误差等,并辨识强影响数据。继而基于均值漂移模型,研究不同异常数据的诊断方法,包括以模型扰动值为依据的粗差的t检验法和以模型扰动对拟合参数的影响为依据的强影响数据的Cook距离检验法。以大坝典型位移监测数据为例,采用上述统计诊断方法对原始监测数据进行合理性检验,结果表明可有效辨识误差数据和强影响数据,能提高数据进一步建模分析的准确性。

Rationality test of dam monitoring data based on statistical diagnosis

According to the abnormal data partitioning of the statistic diagnosis and the causes of the error data in dam monitoring, the abnormal data observed can be categorized into random error, gross error, system error. The influential data is distinguished and then the processing methods for different errors are studied using the mean shift model, including the t-test method for the gross error detection based on the model disturbed values and the Cook-distance-test method for the influential data based on the influence of the model disturbance on the model fitting parameters. Taking typical original monitoring data of dam displacement as an example, rationality test was performed using the proposed statistical diagnosis methods. The results indicate that these methods can effectively distinguish gross errors and influential data, with which the accuracy of further model analysis can be significantly improved.