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Condition Monitoring of CI engine running on Biodiesel using Transient Process

Tesfa, Belachew, Mishra, Rakesh, Gu, Fengshou and Ball, Andrew (2009) Condition Monitoring of CI engine running on Biodiesel using Transient Process. Key Engineering Materials, 413-14. pp. 495-503. ISSN 1013-9826

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Abstract

Various research groups across the globe have developed models for engine condition monitoring and fault diagnosis based on the data from steady state performance measurements over the last two decade. However, these performance data are not amenable for easy collection in some situations and some of the data may show little performance deviation at the steady state conditions of operation. The aim of this study is to identify engine operating conditions and parameters that can be used to develop a diagnostic tool for internal combustion (CI) engine running on biodiesel blends fuel. Ricardo Wave Software was used to stimulate healthy and degraded engine. The degraded condition of operation was created by forcing one injector to work with 90%, 80% and 70% of the normal fuel flow efficiency. The measurable performance parameters such as brake power, brake torque and exhaust temperature and CO emission have been used to compare the deviations during steady and transient condition. From the comparison of the data obtained from transient and steady state simulation of the engine with and without injector fault, it can be concluded that the transient parameters show higher deviations and hence are better suited for condition monitoring and diagnostic modelling in engine working speed.

Item Type: Article
Additional Information: (c) Trans Tech Publications
Uncontrolled Keywords: Injector Fault; Transient Performance; Condition Monitoring; Accumulated Deviation
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Pedagogical Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:
Depositing User: Belachew Tesfa
Date Deposited: 27 May 2009 15:33
Last Modified: 24 Aug 2015 12:01
URI: http://eprints.hud.ac.uk/id/eprint/4381

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