Hi-Leak: Innovative monitoring system for early leak detection in water distribution systems
In Malaysia, current government initiatives are aimed at raising the financial and environmental sustainability of the water services industry by reaching 99% of coverage of clean and treated water and reduce NRW to 25% by 2020. Pipe failures for Malaysia’s non-revenue water are currently 39%, of which ~26% is lost through damaged water pipes and ~6% through inaccurate meter reading. The Ministry of Works estimates about RM25bn for water pipeline rehabilitation over the next 50 years including the replacement of over 44,000km of old asbestos-cement pipes with polyethylene pipes. It is intended that all the leaks detected are repaired by completely replacing the old pipes with new PE ones. Asbestos cement construction represents a significant percentage of the pipes installed in the Malaysian water distribution network, a network of 88,786 km of pipelines that supplies about 11bn m3 of water per year (expected to increase by 63% in 2050) to a total population of about 26 million. Current methods to identify leaks in this network include establishing district metered areas, visual inspections, insertion surveys (inserting microphones into water pipes) and correlation surveys (based on signal correlation techniques) which are all labour intensive and which efficiency largely depends on operator skills. In addition, leaks in non-ferrous mains often have relatively low noise frequencies that are almost impossible to detect with typical leak noise correlators. Considering the limitation of current methods and the lack of experienced manpower for inspection, the industry is looking at new technologies to monitor leaks without human intervention.
The objective of this project is to optimise the detection of water leaks occurring in PE water pipes using distributed guided waves ultrasonic sensors with AE capabilities. HiLeak will be installed along pipes to autonomously detect and report leaks. In order to keep costs as low as possible, the system should rely on relatively simple hardware components and, consequently, the project will take into account only basic signal processing techniques.
The HiLeak project will allow Brunel to advance the knowledge in the applicability of UGW for water filled polyethylene pipes monitoring, pushing further the monitoring range in non-metallic materials to notify in advance of pending failures via bespoke signal processing.
Brunel Innovation Centre's Roie
- Optimisation of data analysis with development and use of novel models for data interpretation related to ultrasonic guided wave behaviour in polyethylene pipes. Brunel will develop a user friendly interface to allow communication and visualisation of the information.
- Development and testing of the ultrasonic guided wave system pulser receiver and transducers. The pulser receiver will be controlled by a specially developed software application that provides high versatility for the waveform generation and several signal analysis tools.
Meet the Principal Investigator(s) for the project
Professor Tat-Hean Gan - Professional Qualifications CEng. IntPE (UK), Eur Ing BEng (Hons) Electrical and Electronics Engg (Uni of Nottingham) MSc in Advanced Mechanical Engineering (University of Warwick) MBA in International Business (University of Birmingham) PhD in Engineering (University of Warwick) Languages English, Malaysian, Mandarin, Cantonese Professional Bodies Fellow of the British Institute of NDT Fellow of the Institute of Engineering and Technology Tat-Hean Gan has 10 years of experience in Non-Destructive Testing (NDT), Structural Health Monitoring (SHM) and Condition Monitoring of rotating machineries in various industries namely nuclear, renewable energy (eg Wind, Wave ad Tidal), Oil and Gas, Petrochemical, Construction and Infrastructure, Aerospace and Automotive. He is the Director of BIC, leading activities varying from Research and development to commercialisation in the areas of novel technique development, sensor applications, signal and image processing, numerical modelling and electronics hardware. His experience is also in Collaborative funding (EC FP7 and UK TSB), project management and technology commercialisation.
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Project last modified 18/03/2021