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Time-Frequency Based Sensor Fusion in the Assessment and Monitoring of Machine Performance Degradation

[+] Author Affiliations
Dragan Djurdjanovic, Jun Ni

University of Michigan, Ann Arbor, MI

Jay Lee

University of Wisconsin at Milwaukee, Milwaukee, WI

Paper No. IMECE2002-32032, pp. 15-22; 8 pages
doi:10.1115/IMECE2002-32032
From:
  • ASME 2002 International Mechanical Engineering Congress and Exposition
  • Dynamic Systems and Control
  • New Orleans, Louisiana, USA, November 17–22, 2002
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 0-7918-3629-0 | eISBN: 0-7918-1691-5, 0-7918-1692-3, 0-7918-1693-1
  • Copyright © 2002 by ASME

abstract

Machines degrade as a result of aging and wear, which decreases their performance reliability and increases the potential for faults and failures. In contemporary manufacturing it becomes increasingly important to predict and prevent machine failures, rather than allowing the machine to fail and then fixing the failure. In this paper, methods of time-frequency signal analysis will be used to capture information from multiple machine sensors. This information could be used to assess machine performance degradation and subsequently take appropriate action. Signals emanating from three different sensors were collected when a sharp and a worn tool have been mounted on a CNC lathe machine. Several combinations of sensors and signal features have been tried in order to demonstrate the ability to use the information from multiple sensors and increase sensitivity to tool wear.

Copyright © 2002 by ASME

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