| Summary: | Water is significantly lost within water networks in most countries with an estimates of 30% would be lost due to leaks in water pipelines. Water leaks are one of the major factors facing the world, from waste water for no appropriate reason other than a lack of sustainable management programmes. This research work will investigates several sensor techniques and image/signal processing methods to detect water leaks within buried pipeline system. A sensor fusion method for the detection of water leakage in pipes, which consists of two or more sensory systems, is proposed in this research work. The suggested sensor fusion system will investigate a combination of transient signals of several direct types, such as flow and pressure, and non-direct types such as acoustic signals and infrared images. The sensors will identify signals inside the pipeline system and will detect any acoustic or transient signals. This might happen as a result of a leakage while the thermal imager will look outside the pipeline system for any leakage signs. This is by way of detecting the contrast in temperature and humidity of the soil surrounding the leakage point. The data has been collected using software that can read and store the required signal data with the infrared image data as required. The collected data is subjected to processing using the Matlab software and based on the results a computer algorithm which has been developed to be used in detection, locating and identifying the leaks using artificial intelligence techniques. The methodology of this research work includes constructing a test rig of a pipeline equipped with necessary instrumentations for data acquiring purposes. As such, data acquisition device, pressure sensors, acoustic sensors, temperature sensors, infrared camera, normal visual camera and any other necessary equipment for water flow control. A series of experiments have been conducted with the test rig in the laboratory and a field experimental work has been conducted in Libya with the results having been highlighted within this report. The expected contribution to knowledge would include significant technical and theoretical aspects of the experimental work and analysis. The contribution includes the comparison between the high and low-resolution infrared cameras. Additionally, an application of a novel approach to using a combination of infrared technology and visual images with a sensory fusion system of acoustic emission and transient signal to detect water leaks in pipeline systems. The work requires building a test rig to develop the experimental work as well as carrying out field works. The contribution to knowledge also includes the developing of an artificial intelligence algorithm for detecting water leakage in pipelines, which would determine the best times of detection when estimating and quantifying the leakage amount.
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