摘要
在经济发展日新月异的今天,环境治污已成为确保社会经济健康有序发展的关键。为实现对污水站点的有效管控,需对其运行状态进行实时监测,为此,文章提出一种负荷功率曲线自动化异常检测的方法。对智能电表采集的负荷数据进行离群点分析并提取典型日负荷曲线,采用一种改进的皮尔逊相关系数分析方法,对每个站点的负荷曲线进行异常检测,判断污水站点的运行情况,提高异常检测准确率并减少人为误差和投入,具有较好的实际应用价值。
With the rapid development of economy,environmental pollution control has become the key to ensure the healthy and orderly development of social economy.In order to realize the effective management and control of sewage stations,it is necessary to monitor their operation status in real time.Therefore,this paper proposes an automatic anomaly detection method of load power curve,analyzes the outliers of the load data collected by the smart meter,extracts the typical daily load curve,and uses an improved Pearson correlation coefficient analysis method to detect the anomaly of the load curve of each station,in this way,we can judge the operation situation of the sewage station,improve the accuracy of anomaly detection and reduce human error and investment.It has good practical application value.
作者
黄彦斌
骆德汉
蔡高琰
Huang Yanbin;LUO Dehan;CAI Gaoyan(School of Information Engineering,Guangdong University of Technology,Guangzhou 510006,China;Guangdong Haodi Innovation Technology Co.,Ltd.,Foshan 528200,China)
出处
《现代信息科技》
2021年第21期121-125,共5页
Modern Information Technology
