The stacker is the core component of the automatic intelligent storage system, and the data of the stacker is an important part of the large data of the power intelligent operation and maintenance warehouse. With the rapid intelligence of the warehouse equipment,the collection,processing and analysis of the stacker's state data are of great significance to the normal operation of the automatic intelligent storage system. In order to dig out the abnormal data from the stacker state data, warning of stacking in actual engineering machine,to prevent major failure of stacker. Firstly,using the mean to smooth the data smoothing,and a pre-processing model for smoothing data is constructed.Secondly,using box-plot method after pre-pro-cessing to dig out abnormal screening interval,and a interval automatic identification model is established. Finally,the algo-rithm is verified by using the the stacker operation data obtained from automatic intelligent storage system,and then the cor-rectness and effectiveness of the algorithm are proved.%堆垛机是自动化智能仓储系统的核心组成部分,堆垛机运行数据是电力智能运维大数据的重要组成部分.随着仓库设备迅速智能化,堆垛机状态数据的采集、处理、分析对自动化智能仓储系统正常运行有极其重要意义.为从堆垛机状态数据中挖掘出异常数据,进而对实际工作中堆垛机进行预警提示,防止堆垛机发生重大故障,首先利用均值平滑对数据进行平滑处理,建立数据平滑处理的预处理模型;其次,利用箱形图法对预处理后的数据进行异常区间筛选,建立异常区间自动识别模型.最后,利用电力行业自动化仓储系统中堆垛机运行数据对算法进行验证,证明其正确性及有效性.
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