基于监控数据挖掘的运行图参数查定与修正方法

Method for the Measurement and Correction of Train Diagram Parameters Based on Monitoring Data Mining

采用基于统计的异常数据处理方法对列车运行监控装置记录的海量列车运行实测数据进行处理,剔出其中的异常数据,设计数据补齐算法补齐缺失的数据;应用统计分析方法,在分析实测数据的集中趋势、离散程度、分布形态等规律和按照列车种类对数据进行时距分组的基础上,建立能够合理反映数据变化趋势的拟合曲线回归模型,用于参数的修正。运用给出的数据处理方法和拟合曲线回归模型开发出基于实测数据的运行图参数查定与修正系统。以大同—准格尔铁路为例进行验证,结果表明该方法及系统提高了参数的计算精度和查定效率,并且简便易行,可操作性强。

A statistics-based method of abnormal data processing was used to process the abundant measured data recorded by the train monitoring and recording devices.The abnormal data were wiped off.A data complement algorithm was designed to fill up the missing data.Using the statistical analysis method,the author analyzed the central tendency,dispersion degree and distributional pattern of the measured data.The data were divided into several groups by time and distance according to different kinds of trains.Based on this,the curve fitting regression model that could reflect the trend of data change was established to modify the parameters.The given method of data processing and the curve fitting regression model were used together to develop the measurement and correction system of train diagram parameters based on measured data.Datong-Jungar Railway was taken for example to carry out the verification.Results show that this method and system have improved parameter calculation accuracy and measurement efficiency.At the same time,they are simple,feasible and with high operability.