Bibliographic Details
| Title: |
Identifying periods impacted by sewer inflow and infiltration using time series anomaly detection |
| Authors: |
Jingyu Ge, Jiuling Li, Ruihong Qiu, Tao Shi, Zi Huang, Yanchen Liu, Zhiguo Yuan |
| Source: |
Water Research X, Vol 25, Iss , Pp 100278- (2024) |
| Publisher Information: |
Elsevier, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Environmental technology. Sanitary engineering |
| Subject Terms: |
Inflow and infiltration, Dry/ wet weather, Data, Time series, Anomaly detection, Environmental technology. Sanitary engineering, TD1-1066 |
| More Details: |
Accurate diagnosis of sewer inflow and infiltration (I/I) is crucial for ensuring the safe transportation of sewage and the stability of wastewater treatment processes. Identifying periods impacted by I/I is essential for I/I diagnosis, but current methods lack a standard criterion and require adaptation to specific conditions, resulting in low accuracy, complexity, and limited generalizability. This paper proposes a novel approach to distinguish I/I periods from time series of sewer measurements based on anomaly detection theory through an iterative use of a time-series reconstruction model. This method eliminates the need for external data such as rainfalls and avoids intensive manual data analysis. Operating directly on in-sewer data, it enhances accuracy compared to existing approaches and is applicable to various external factors such as rainfall, snowmelt, and seawater intrusion. The method can be applicable to a broad range of monitoring data, including flow rate, temperature, and conductivity. Validated through simulation studies and demonstrated via real-life applications, this method offers an efficient solution for I/I detection, facilitating further I/I diagnosis, including I/I quantification and location identification. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2589-9147 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2589914724000689; https://doaj.org/toc/2589-9147 |
| DOI: |
10.1016/j.wroa.2024.100278 |
| Access URL: |
https://doaj.org/article/927e06cf9add41359f3c84550fe83170 |
| Accession Number: |
edsdoj.927e06cf9add41359f3c84550fe83170 |
| Database: |
Directory of Open Access Journals |
