Fault Diagnosis of Reciprocating Compressors Based on Thermal Imaging and Support Vector Machines

Rongfeng Deng, Yubin Lin, Weijie Tang, Fengshou Gu, Andrew D. Ball

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

Abstract

Reciprocating compressor (RC) is widely used in industry because of its wide application pressure range, high thermal efficiency and strong adaptability. In order to avoid the possible casualties or property losses caused by the fault of a RC, it is of great significance to carry out efficient fault diagnosis for RC. The common fault types of RC usually lead to the variation of pressure range and the amount of air intake, so different faults will lead to the changes in the distribution of the whole temperature field, which provides the possibility to distinguish the fault types of RC by using infrared thermal imaging. In this paper, three kinds of faults were simulated in an uncontrolled temperature environment. The temperature distribution of a RC was captured by a infrared camera remotely. During the experiment, the average grayscale values of six main components were calculated in real time to form a 6-dimension vector which represent the temperature distribution. Support Vector Machines (SVM) was then used for classifying the differences of the temperature distributions, and the results demonstrated that variation of the average temperatures of six main components aided by SVM has great potential for fault diagnosis of RCs under various operating conditions and ambient temperature.

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
Pages206-216
Number of pages11
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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