Paper Title:
Engine Fault Diagnosis Based on PSO-BP Network
  Abstract

BP network could deal with some nonlinear problems such as fault diagnosis, but the gradient-based method tends to get stuck in local optima or premature convergence. As a population-based heuristic optimization algorithm, PSO method could increase training accuracy of BP network so as to improve discriminant precision of fault diagnosis of equipment such as engine. Ladder diminishing inertia weights tend to improve network’s convergence precision and efficiency during the late stage of PSO iterations, in addition, LPSO or RegPSO contributes to confining premature convergence. The PSO-BP fault diagnosis model of 190A diesel engine has verified the above opinions.

  Info
Periodical
Advanced Materials Research (Volumes 299-300)
Edited by
Jianzhong Wang and Jingang Qi
Pages
1307-1311
DOI
10.4028/www.scientific.net/AMR.299-300.1307
Citation
L. X. Nie, T. X. Zhang, S. J. Wang, L. P. Zhang, "Engine Fault Diagnosis Based on PSO-BP Network", Advanced Materials Research, Vols. 299-300, pp. 1307-1311, 2011
Online since
July 2011
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Price
$32.00
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