Search:
Computing and Library Services - delivering an inspiring information environment

The Diagnosis of a Gearbox Transmission System Using Electrical Control Parameters

Benghozzi, A., Shao, Y., Shi, Z., Gu, Fengshou and Ball, Andrew (2012) The Diagnosis of a Gearbox Transmission System Using Electrical Control Parameters. In: Proceedings of the 18th International Conference on Automation and Computing (ICAC) 2012: Integration of Design and Engineering. IEEE, Loughborough, UK, pp. 1-6. ISBN 9781908549006 / 9781467317221

[img]
Preview
PDF - Accepted Version
Download (412kB) | Preview

    Abstract

    Most of the techniques used to monitor and diagnose faults from machines are usually based on additional measurements which require high setup costs and installation difficulties. This paper focuses on developing a new sensorless method to monitor and diagnose different faults of a gearbox transmission system based on the parameters acquired from control systems. The control data, which are available in most of machines, including armature current, load set point, speed demand, motor current, torque feedback and speed feedback have been explored based on a gearbox test system. A non linear regression model is adopted to correlate the datasets to obtain residuals from the observed and the predicted control parameters. Subsequently a model based method is implemented to detect common faults such as lower oil levels and shaft misalignment in the gearbox system. The results confirm that it is possible to use existing control parameters for monitoring such faults.

    Item Type: Book Chapter
    Subjects: T Technology > T Technology (General)
    T Technology > TA Engineering (General). Civil engineering (General)
    T Technology > TK Electrical engineering. Electronics Nuclear engineering
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Automotive Engineering Research Group
    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 > Informatics Research Group > XML, Database and Information Retrieval Research Group
    Related URLs:
    Depositing User: Sara Taylor
    Date Deposited: 20 Sep 2012 14:47
    Last Modified: 05 Jun 2013 12:43
    URI: http://eprints.hud.ac.uk/id/eprint/15005

    Document Downloads

    Downloader Countries

    More statistics for this item...

    Item control for Repository Staff only:

    View Item

    University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©