Grey Wolf Optimization based Sensor Placement for Leakage Detection in Water Distribution System
Rejeesh Rayaroth1, G. Sivaradje2
1Rejeesh Rayaroth, Department of Electronics and Communication Engineering, Pondicherry Engineering College, Pillaichavady, Puducherry India.
2G. Sivaradje, Department of Electronics and Communication Engineering, Pondicherry Engineering College, Pillaichavady, Puducherry India.
Manuscript received on 06 February 2019 | Revised Manuscript received on 19 February 2019 | Manuscript Published on 04 March 2019 | PP: 180-188 | Volume-7 Issue-5S2 January 2019 | Retrieval Number: ES2028017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Water Distribution System (WDS) are employed in everyday life either for domestic or for industrial purpose. WDS are large scale systems that need the design of better leak detection methods to avoid water waste. Recently, researchers concerned about WDS have focused their research on water leakage detection techniques. However, the different existing techniques failed to improve the performance of accuracy and time consumption during water leakage detection. In order to address the above mentioned issues, Bivariate Correlation and Sensitivity Analysis based Meta-Heuristic Grey Wolf Optimization (BCSA-MHGWO) Technique is introduced. The main aim of the BCSA-MHGWO technique is to detect the water leakage with a minimal number of sensor placed nodes. Initially, WDS is represented in graph model comprising a set of vertices (i.e., nodes) and set of edges (i.e., pipes). The sensitivity and entropy value is calculated for all nodes based on the pressure and flow rate. After calculating the sensitivity value, the correlation value of all nodes is measured by using bivariate correlation coefficient based on the pressure series. Finally, grey wolf optimization process is carried out in BCSA-MHGWO technique to select the optimal nodes for sensor placement based on the sensitivity, entropy and correlation value for water leakage detection. In this way, water leakage detection accuracy and time performance get improved using BCSA-MHGWO technique. The performance of BCSA-MHGWO Technique is measured in terms of water leakage detection accuracy, water leakage detection time, and false positive rate. The simulation results show that BCSA-MHGWO Technique improves the performance of water leakage detection accuracy and also reduces water leakage detection time when compared to state-of-the-art works.
Keywords: Water Distribution Systems, Leak Detection, Bivariate Correlation, Sensitivity, Entropy, Meta-Heuristic, Grey Wolf Optimization.
Scope of the Article: Smart Sensors and Internet of Things for Smart City