A Mobile Robot Based Monitoring Platform for Pipeline Leakage Diagnosis Based on Cross-correlation Analysis

Weijie Tang, Guocai Zhang, Fengshou Gu, Xiaoli Tang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, various pipelines are broadly used in the transportation of resources in the production process and life applications, such as natural gas, compressed air, water, oil and so on. Pipe leakages usually occur due to the improper manufacturing process, installation of valves or other devices, prolonged use, etc. Pipeline leakage will cause energy loss, pollution and other severe problems, which will lead to equipment damage and even casualties. Therefore, the detection of pipeline leakage is significantly important. Traditional pipeline leak detection requires visual inspection or many fixed detection sensors. This may cause missed inspection by human errors and also will greatly increase the cost on the expensive devices. Compared with visual inspection and specific testing devices, mobile robots have the advantages of portability, economic cost and wide application for effective and efficient pipeline leakage detection. Robots can be deployed on lines or near equipment prone to pipeline leaks which can be detected online according to the path set. This paper presents an effective pipeline leak detection method to monitor the leakage of a two-stage reciprocating compressor with a mobile robot. An android mobile phone is installed on the mobile robot platform. After the robot moves to the monitoring point, the microphone of the mobile phone starts to collect environmental sound. The cross-correlation analysis is then performed on the LABVIEW software platform to implement online detection of different leakage faults. The experimental results show that the extreme value of the correlation number is effective and efficient for real-time detection of the presence of leaks.

Original languageEnglish
Title of host publicationProceedings of IncoME-V & CEPE Net-2020
Subtitle of host publicationCondition Monitoring, Plant Maintenance and Reliability
EditorsDong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Pages477-489
Number of pages13
Volume105
Edition1st
ISBN (Electronic)9783030757939
ISBN (Print)9783030757922
DOIs
Publication statusPublished - 16 May 2021
Event5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China
Duration: 23 Oct 202025 Oct 2020
Conference number: 5
https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

NameMechanisms and Machine Science
Volume105
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

Conference5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated titleIncoME-V and CEPE Net-2020
CountryChina
CityZhuhai
Period23/10/2025/10/20
Internet address

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