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Diagnostics of Mechanical Faults of Loudspeakers Using Principal Component Analysis and Fisher’s Discriminant Analysis

[+] Author Affiliations
Jaewon Choi, Michael D. Bryant

The University of Texas at Austin, Austin, TX

Paper No. DSCC2011-6198, pp. 433-440; 8 pages
doi:10.1115/DSCC2011-6198
From:
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Volume 1
  • Arlington, Virginia, USA, October 31–November 2, 2011
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5475-4
  • Copyright © 2011 by ASME

abstract

This study illustrates a novel model based FDI method for the common mechanical faults arising during the manufacture of loudspeakers. To overcome the drawbacks of the conventional signal based approaches, the Bayesian classification of impulse responses based on a model based fault symptom database is proposed. The loudspeaker model is estimated via IRES and ARMA techniques. The fault symptom database is constructed with a novel nonlinear loudspeaker model. The performances of Principal Component Analysis (PCA) and Fisher’s Discriminant Analysis (FDA) are compared. The results show the effectiveness of the proposed method. It is also shown that the FDA based classifier performs better than PCA in terms of the accuracy and consistency of the healthy baseline estimation. However, the fault isolation is difficult due to the similarities of fault signatures.

Copyright © 2011 by ASME

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