Novel Leakage Detection and Localization Method Based on Line Spectrum Pair and Cubic Interpolation Search
Leakage detection in water distribution systems (WDS) is critical to ensuring the security of urban water supplies. Acoustic detection methods have been used for leakage detection in water utilities, but ambient noise in real cases interferes with their detection accuracy, and the localization proce...
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| Published in | Water resources management Vol. 34; no. 12; pp. 3895 - 3911 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.09.2020
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0920-4741 1573-1650 |
| DOI | 10.1007/s11269-020-02651-z |
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| Abstract | Leakage detection in water distribution systems (WDS) is critical to ensuring the security of urban water supplies. Acoustic detection methods have been used for leakage detection in water utilities, but ambient noise in real cases interferes with their detection accuracy, and the localization process in meshed or looped pipe networks requires significant computational costs. To increase the effectiveness of acoustic detection methods in practical applications, the current work proposes a novel leakage detection and localization method. This method extracts line spectrum pairs (LSP) of leakage signals and uses a random forest (RF) model to detect leaks; then, a cubic interpolation search (CIS) algorithm is developed to locate leaks. The LSP-based leakage detection method shows a clear advantage over the detection methods based on linear prediction coefficients (LPC) and time or frequency domain features. The proposed leakage detection method achieves 99.45% accuracy. In the case of −5 dB, the detection accuracy reaches 93.89%. The CIS algorithm is found to be more stable and shows a faster convergence speed than a commonly used graph-based search algorithm. The localization error is low (i.e., 2.22 m to 9.99 m). The LSP-CIS combined algorithm provides a more effective solution for leakage detection and localization. |
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| AbstractList | Leakage detection in water distribution systems (WDS) is critical to ensuring the security of urban water supplies. Acoustic detection methods have been used for leakage detection in water utilities, but ambient noise in real cases interferes with their detection accuracy, and the localization process in meshed or looped pipe networks requires significant computational costs. To increase the effectiveness of acoustic detection methods in practical applications, the current work proposes a novel leakage detection and localization method. This method extracts line spectrum pairs (LSP) of leakage signals and uses a random forest (RF) model to detect leaks; then, a cubic interpolation search (CIS) algorithm is developed to locate leaks. The LSP-based leakage detection method shows a clear advantage over the detection methods based on linear prediction coefficients (LPC) and time or frequency domain features. The proposed leakage detection method achieves 99.45% accuracy. In the case of −5 dB, the detection accuracy reaches 93.89%. The CIS algorithm is found to be more stable and shows a faster convergence speed than a commonly used graph-based search algorithm. The localization error is low (i.e., 2.22 m to 9.99 m). The LSP-CIS combined algorithm provides a more effective solution for leakage detection and localization. Leakage detection in water distribution systems (WDS) is critical to ensuring the security of urban water supplies. Acoustic detection methods have been used for leakage detection in water utilities, but ambient noise in real cases interferes with their detection accuracy, and the localization process in meshed or looped pipe networks requires significant computational costs. To increase the effectiveness of acoustic detection methods in practical applications, the current work proposes a novel leakage detection and localization method. This method extracts line spectrum pairs (LSP) of leakage signals and uses a random forest (RF) model to detect leaks; then, a cubic interpolation search (CIS) algorithm is developed to locate leaks. The LSP-based leakage detection method shows a clear advantage over the detection methods based on linear prediction coefficients (LPC) and time or frequency domain features. The proposed leakage detection method achieves 99.45% accuracy. In the case of −5 dB, the detection accuracy reaches 93.89%. The CIS algorithm is found to be more stable and shows a faster convergence speed than a commonly used graph-based search algorithm. The localization error is low (i.e., 2.22 m to 9.99 m). The LSP-CIS combined algorithm provides a more effective solution for leakage detection and localization. |
| Author | Xu, Xiyan Smith, Kate Ma, Ziqing Guo, Guancheng Liu, Shuming Wang, Xiaoting Huang, Yujun Yu, Xipeng |
| Author_xml | – sequence: 1 givenname: Guancheng surname: Guo fullname: Guo, Guancheng organization: School of Environment, Tsinghua University – sequence: 2 givenname: Xipeng surname: Yu fullname: Yu, Xipeng organization: School of Environment, Tsinghua University – sequence: 3 givenname: Shuming orcidid: 0000-0002-4949-4318 surname: Liu fullname: Liu, Shuming email: shumingliu@tsinghua.edu.cn organization: School of Environment, Tsinghua University – sequence: 4 givenname: Xiyan surname: Xu fullname: Xu, Xiyan organization: School of Environment, Tsinghua University – sequence: 5 givenname: Ziqing surname: Ma fullname: Ma, Ziqing organization: School of Environment, Tsinghua University – sequence: 6 givenname: Xiaoting surname: Wang fullname: Wang, Xiaoting organization: School of Environment, Tsinghua University – sequence: 7 givenname: Yujun surname: Huang fullname: Huang, Yujun organization: School of Environment, Tsinghua University – sequence: 8 givenname: Kate surname: Smith fullname: Smith, Kate organization: School of Environment, Tsinghua University |
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| CitedBy_id | crossref_primary_10_1016_j_measurement_2025_116857 crossref_primary_10_2166_aqua_2021_021 crossref_primary_10_1061_JWRMD5_WRENG_6122 crossref_primary_10_2166_ws_2021_101 crossref_primary_10_1016_j_scitotenv_2022_153530 crossref_primary_10_1080_09593330_2022_2074320 crossref_primary_10_1080_15732479_2022_2127792 crossref_primary_10_1016_j_wroa_2025_100333 crossref_primary_10_1016_j_watres_2024_121999 crossref_primary_10_1139_er_2021_0046 crossref_primary_10_1007_s41101_024_00248_w crossref_primary_10_1016_j_ymssp_2022_109810 crossref_primary_10_1016_j_measurement_2021_110611 crossref_primary_10_1016_j_watres_2024_122471 crossref_primary_10_1016_j_iot_2022_100504 crossref_primary_10_1016_j_psep_2023_08_011 |
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| Keywords | Leakage detection Water distribution system Line spectrum pair Graph-based localization Cubic interpolation search |
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| SubjectTerms | Accuracy Acoustic noise acoustics administrative management Algorithms Ambient noise Atmospheric Sciences Civil Engineering Coefficients Computer applications Earth and Environmental Science Earth Sciences Environment Geotechnical Engineering & Applied Earth Sciences Hydrogeology Hydrology/Water Resources Interpolation Leak detection Leakage Leaks Linear prediction Localization Localization method Methods prediction Search algorithms Security Sewage disposal Sonar detection Sound detecting and ranging water Water distribution Water distribution systems Water engineering Water supply Water utilities |
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| Title | Novel Leakage Detection and Localization Method Based on Line Spectrum Pair and Cubic Interpolation Search |
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