Artificial Intelligence (AI) Contribution to GIS in Optimal Positioning of Hydrophone Sensors Using Genetic Algorithm (Case Study: Water Network, Casablanca, Morocco)

2023

WIREs Water

Effective water pipeline leak detection and localization can help water practitioners save water losses and reduce pipe rehabilitation budgets. Different sensing technologies can provide essential data aiding model development for predicting future leaks in the water distribution networks. Solutions for applying different sensing technologies to real water distribution networks are being developed for real‐time data collection, precise leak localization, reducing false alarms, and continuous pipeline monitoring. Experiments of different scales and specifications have been conducted to test the application and effectiveness of sensing technologies for leak diagnosis in water pipelines. Quality data collection is especially crucial for the successful implementation of these experiments. However, practitioners need help designing effective leak detection and localization experiments, wasting time, and resources. There needs to be a greater understanding of the design parameters for more accurate testing, such as sensor selection, sensor placement, ambient noise sources, and system operations. The current study, therefore, delineates design parameters for design leak diagnosis experiments for lab, testbed, and real networks. For application in real water networks, expert opinion is used to help identify the benefits and limitations and the implementation issues of available sensing technologies. An example experiment design using multi‐sensing technologies for smart leak diagnostics in Hong Kong is also presented. The study can guide water practitioners and researchers to design a multi‐sensing leak diagnostic experiments enabling a smart and sustainable utility management.This article is categorized under: Engineering Water > Methods Engineering Water > Sustainable Engineering of Water Science of Water > Water Extremes

Section: Real Wdnsmentioning

confidence: 99%

State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

2023

WIREs Water

“…Only 7% of real-life cases and theoretical studies could be found on the topic which implies a big gap in research. For example, Lechgar et al (2016) explored hydrophone implementation for leak detection in Casablanca. Overall, theoretical studies including a review of previous work on the current research area are also negligible.…”

Section: Types Of Research Studiesmentioning

confidence: 99%

“…Generic discussion on all methods, however, does not help practitioners gain a working insight of any hardware-based acoustic methods like hydrophones for practical implementation in the field. In this regard, some of the relevant empirical studies have revealed its merit to be used for real-time monitoring for leak detection (Lechgar et al 2016;Xu et al 2019). However, practical implementation requires the identification of constraints for its use for efficient leak detection, accurate localization, and long-term monitoring of real networks.…”

Section: Introductionmentioning

confidence: 99%

Review of Water Leak Detection and Localization Methods through Hydrophone Technology

J. Pipeline Syst. Eng. Pract.

2021

Acoustic technologies are popular for detection of leak detriments in water pipelines. However, problems of false alarms, detection of weak or difficult leaks, accurate leak pinpointing, and the high cost of long-term monitoring remain prevalent. These issues demand a more sophisticated testing approach suitable for real-world application. In particular, hydrophone technology has strong promise for long-range leak detection in high attenuation conditions. However, existing review studies only cover the methods of leak detection holistically with limited insight into the practical implementation of sensing technologies for water leak detection. In particular, the problem of detecting and localizing leaks using hydro-acoustic data has not been yet extensively studied. The current study, therefore, presents a state-of-the-art review of the extant literature on water leak detection and localization taking hydrophones as a good example of hydro-acoustic water leak detection. The study compares hydrophones with other popular sensing technologies like accelerometers and guides on its better application for detecting water leaks. Current research directions, gaps, and future work foci are also identified to enable further development of a hydrophone-based water leak detection system. Review shows that existing experiments are limited to controlled conditions where impacts of surrounding strata, ambient noise, and difficult pipe geometries cannot be studied. Future studies can apply the technology to real-life cases, developing faster analytical methods and hybrid solutions using a multi-sensing approach. This can help water leak experts enormously in cost-effective, efficient detection of leaks.

“…Such empirical studies show the viability of the hydrophone for detecting real unstimulated leaks in real water distribution networks (Lechgar et al, 2016;Xu et al, 2019). However, there are very few studies that have attempted to apply hydrophones to real water networks.…”

Section: Introductionmentioning

confidence: 99%

“…A recent review covers the previous research on hydrophones extensively (Bakhtawar & Zayed, 2021). Previous experimental studies demonstrate hydrophones produce similar or higher accuracy results as compared to accelerometers, pressure sensors, or ground microphones (Almeida et al, 2014;Gao et al, 2005;Guo et al, 2019;Lechgar et al, 2016;Xu et al, 2019). Particularly, Cody et al (2020b) suggest that acoustic methods deliver high-resolution data for the detection of even small leaks which are difficult to detect.…”

Section: Introductionmentioning

confidence: 99%

AI-based smart water leak detection using hydrophones

Fares

2022

Preprint

Acoustic technologies are popular for the detection of leak detriments in water pipelines. However, problems of false alarms, missed leaks, limited site information, and the high cost of long-term monitoring remain prevalent. These issues demand a more sophisticated testing approach suitable for real-world applications. Hydrophone technology has a strong promise for precision leak detection. However, acoustic leak detection is mostly focused on detection using controlled testbed experiments. The practical application of hydrophones for leak detection has not been well reported in the literature. The current study presents a smart real-time leak detection system that uses real-time acoustic data collection. AI-based data-driven models were developed to identify leaks based on limited site information. Different classification models were trained using various feature combinations to identify the most significant model and feature set. ensemble-based classifiers of Adaboost, and Random Forest demonstrated the most promising performance for the leak detection application. Results reveal hydrophones to be more effective as compared to other acoustic devices like accelerometers and noise loggers in detecting leaks.