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A programmable logic controller based remote pipeline monitoring system

Abstract Pipelines are vital method for long distance transportation and they need to satisfy levels of safety, unwavering quality and efficiency. Large amount of natural resources is wasted due to leakages in pipelines. In recent years, this issue has gained a lot of consideration in research community due to associated economic losses and environmental hazards. The precise effort of this research is to design a novel leak detection system with improved sensitivity, reduce false alarm rate and higher leak localization accuracy. The proposed test bed is established by using specific purpose sensors, A programmable logic controller (PLC) and supervisory control and data acquisition (SCADA). The well-known Volume Based Method (VBM) and Pressure Point Analysis (PPA)approach has been adapted to propose a Leak Detection System (LSD), with improved detection sensitivity and reliability. The algorithms are deployed in field on pipeline test bed and performance results are documented for different testing scenarios. Results show that the hybrid technique has leak detection sensitivity of 5 L/min in real time and ±8.5% leak localization accuracy.
- University of Alberta Canada
- COMSATS University Islamabad Pakistan
- COMSATS University Islamabad Pakistan
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).10 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
