E3S Web Conf.
Volume 345, 2022XXV Biennial Symposium on Measuring Techniques in Turbomachinery (MTT 2020)
|Number of page(s)||7|
|Published online||29 March 2022|
Non-invasive leakage detection & localisation technique in noisy industrial environment
1 AUTh, Department of Mechanical Engineering, Laboratory of Fluid Mechanics and Turbomachinery, 54624 Thessaloniki, Greece
2 AUTh, Faculty of Sciences, School of Physics, Department of Electronics and Computers, 54124 Thessaloniki, Greece
An innovative non-invasive method for pipe leak detection and localization in noisy environment is presented in this paper. Nowadays, it is well known that complex pipeline networks are used for operational purposes and fluid transportation in every high-end-technology heavy industry such as refineries, combined heat and power cycles, cement and steel industries, etc. In all these cases, safety is the key parameter in order to ensure the efficient plant operation and to avoid any possible accident with devastating consequences that may lead to a turn down of the production process. For this reason, it is mandatory to develop reliable enough methods for detection of fluid leakages which represent the most common threaten in pipeline networks. Towards to this direction an integrated experimental setup was built in order to validate the results of the algorithm which was also developed for the purposes of the present study and aims to detect and locate the artificial leakages through the attenuation of the acoustic signal propagating in a pipeline. This experimental setup consists of pipelines that installed into an anechoic chamber and uses pure water as working medium. Apart from the high-efficient accuracy of the developed algorithm in the leakage detection and localization, the proposed method was designed with extra focus on the reduced CAPEX and OPEX costs. Finally, according to the results the proposed system gives sufficiently low false alarm regarding the leakage detection, while the mean percentage error of the leakage localization is around 6% which is considered as an acceptable value.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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