HUShi-yuan,GAOJin-liang,ZHONGDan,et al.Comparison of Methods for Flow Monitoring Data Outlier Detection in Water Distribution Network[J].China Water & Wastewater,2024,40(3):53-59.
Comparison of Methods for Flow Monitoring Data Outlier Detection in Water Distribution Network
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第40卷
Number:
第3期
Page:
53-59
Column:
Date of publication:
2024-02-01
- Keywords:
- flow monitoring data; outlier detection; Boxplot; LOF; Prophet
- Abstract:
- With the development of information technology, water enterprises are undergoing intelligent transformation and upgrading. Data collection and preprocessing is an important pre-step for water enterprises to realize intelligent management, and provides a foundation for subsequent data mining, operation management and scheduling decision. Due to the reasons such as environmental factors, random disturbance in the pipe network and pipe network accident, monitoring data quality issues exist widely, making it is very important to find an effective method for flow monitoring data outlier detection in water distribution network. The common anomalies were firstly classified into three categories according to the basic characteristics and temporal correlation of flow monitoring data in water distribution network. Then, the performance of Boxplot, LOF and Prophet outlier detection models based on statistics, density and prediction in the detection of different types of real flow monitoring data outliers was explored in a southeast coastal city of China. Boxplot and LOF models identified outliers more accurately. However, Boxplot had broad criteria for outlier identification, and it was easy to identify some non-abnormal data as outliers. Prophet had limited effectiveness in identifying unstable flow data.
Last Update:
2024-02-01