The Design of Pipeline Leak Location Prediction System with Incremental Extreme Learning Machine (I-ELM)

Suyanto, Ali Masduqi, Syamsul Arifin, Mohammad Alfaris Fernanda, Gigih Yuli Asmara

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Water loss is a global concern faced by all nations. It stems from various factors, categorized into physical and non- physical losses. Physical loss, mainly attributed to pipe leaks, significantly contributes to total water loss, with 80% attributed to leaks. Thus, an Artificial Neural Network-based leak detection system using Incremental Extreme Learning Machine algorithm is designed. A District Metered Area (DMA) is selected for study. DMA specifications are used for modeling through EPANET software. After validating the DMA model, leak simulations employ emitter coefficients (0.5-1 LPS). Data from 17 junctions under different leak scenarios are collected. An I-ELM leak detection system is developed, using 17-feature pressure data and two target variables for training. Testing data, derived from the split training set, results in leak location predictions for pipeline sections with average deviations of 3.7577, 2.4310, and 0.5630. Leak size predictions have average deviations of 0.0807, 0.0585, and 0.0543. Overall, leak location prediction's RMSE is 0.0516, and leak size prediction's RMSE is 0.0696.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationICMERALDA 2023 - International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages214-219
Number of pages6
ISBN (Electronic)9798350369359
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023 - Virtual, Online, Indonesia
Duration: 24 Nov 202324 Nov 2023

Publication series

NameProceedings: ICMERALDA 2023 - International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications

Conference

Conference2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023
Country/TerritoryIndonesia
CityVirtual, Online
Period24/11/2324/11/23

Keywords

  • DMA
  • I-ELM
  • Leak Location
  • Pressure
  • RMSE

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