A Novel Design and Implementation of Pipeline Inspection System

Rajesh, R. M.; Rakesh, B.; Rohan, P.; Santosh, C. K.; Shirol, Suhas B.; Ramakrishna, S.

doi:10.1007/978-981-15-1632-0_1

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…Among them, pipeline robots 3 perform periodical inspections with non-destructive testing probes and are widely used for detecting defects inside of pipeline. Rajesh et al 4 proposed a design for a pipeline inspection robot that can detect various pipe cracks internally using infrared sensor at a very low cost. Park et al 5 designed a robot to work in the pressurized gas pipe up to maximum 5 MPa and to overcome adverse environment like steel dust, water, and mud.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of fiber Bragg grating hoop strain sensor–based method for sudden leakage monitoring of gas pipeline

Jiang

Ren

Wang

et al. 2020

Structural Health Monitoring

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Pipeline, serving as one of the most important gas transportation methods, can cause serious consequences in the event of leakage, so leakage monitoring is particularly important. In our previous study, a fiber Bragg grating hoop strain sensor was developed to detect pipeline leakage by measuring circumferential strain, and this sensor was utilized in a liquid pipeline leakage test to verify its performance. In this article, we established a full-scale gas pipeline model and investigated the performance of this fiber Bragg grating hoop strain sensor in leakage monitoring. On the basis of circumferential strain variation characteristic before and after negative pressure wave arrival at a fiber Bragg grating hoop strain sensor, a linear fitting algorithm combined with threshold detection was proposed to capture the knee point of circumferential strain. Test results illustrated that the proposed approach has good performance in knee point detection, and fiber Bragg grating hoop strain sensor is suitable for gas pipeline leakage monitoring.

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Section: Introductionmentioning

confidence: 99%