Research Review and Prospect of Data Cleaning for Multi-parameter Monitoring Data of Power Equipment
The situation awareness of power equipment based on multi-parameter monitoring data is one of the important approaches to enhance equipment maintenance efficiency,eliminate hidden faults,and ensure the safe and stable opera-tion of the power system.However,various interferences during the data collection,transmission,and storage processes lead to significant deviations and missing data in the original monitoring data,which in turn affects the accuracy of situa-tional awareness.Therefore,it is urgent to perform data cleansing to enhance data quality.On the basis of comprehensively analyzing the literature in the field of multi-parameter monitoring data cleaning of power equipment,we analyzed the influencing factors of data quality for power equipment multi-parameter monitoring,and we summarized the general framework for data cleaning of multi-parameter monitoring data,including multi-parameter correlation analysis,abnormal data detection,abnormal data classification,and"dirty"data repair.Moreover,the common methods of each part are compared and analyzed,and the data cleaning methods under special scenarios are introduced.Additionally,two approaches to improve the efficiency of data cleaning are explored.Finally,we identify the main challenges of data cleansing field for multi-parameter monitoring data of power equipment and provide an outlook on future development trends.
power equipmentmonitoring datadata cleaningsmooth reconstructionefficiency of data cleaning
万方数据
维普
