Fuzzy Model-Based Condition Monitoring of a Dry Vacuum Pump via Time and Frequency Analysis of the Exhaust Pressure Signal

Twiddle, J.A. and Jones, N.B. and Spurgeon, S.K. (2008) Fuzzy Model-Based Condition Monitoring of a Dry Vacuum Pump via Time and Frequency Analysis of the Exhaust Pressure Signal. Proceedings of the Institution of Mechanical Engineers Part C - Journal of Mechanical Engineering Science, 222 (2). pp. 287-293. ISSN 0954-4062 . (The full text of this publication is not available from this repository)

The full text of this publication is not available from this repository. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1243/09544062JMES651

Abstract

A fuzzy model-based diagnostic scheme is designed to monitor dry vacuum pump performance and detect two fault conditions, mechanical inefficiency and exhaust system blockage. The diagnostic scheme is based on time and frequency analysis of the exhaust pressure signal. Power ratios of certain frequency components in the signal spectrum can be used to predict the gas load, motor current and hence mechanical efficiency. Changes in the periodic features of the signal, symptomatic of fault conditions can be detected using a fuzzy reference model. A fuzzy rule base is used to analyse outputs of the reference model and the load estimator and produce a diagnosis of the pump condition. Experimental results show that the motor current estimation had a root mean squared error of 0.11 A (similar to 5 per cent). Two fault symptoms, a 29 per cent obstruction of the exhaust silencer and an 8 per cent increase in current with respect to gas load, were simulated on the pump test bed and successfully diagnosed.

Item Type: Article
Uncontrolled keywords: dry vacuum pumps; condition monitoring; fault diagnosis; fuzzy logic
Subjects: T Technology > TJ Mechanical engineering and machinery > Control engineering
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: J. Harries
Date Deposited: 20 Apr 2009 14:07
Last Modified: 17 Jun 2009 13:52
Resource URI: http://kar.kent.ac.uk/id/eprint/17877 (The current URI for this page, for reference purposes)
  • Depositors only (login required):