Finding
Comparison of the diagnostic results between the PSO-based algorithm and the BP-based algorithm indicates that the network system based on PSO algorithm is of better training performance, and of less overall output error compared with those of the BP algorithm.
Paper
Application of PSO Algorithm to Gearbox Fault Diagnosis
Abstract
After an introduction of the principle of particle swarm optimization (PSO) algorithm based on swarm intelligence, and of the modified version of the PSO algorithm, a neural network system for gearbox fault diagnosis has been established. After being trained by PSO algorithm, the neural network system is applied to fault diagnosis. Comparison of the diagnostic results between the PSO-based algorithm and the BP-based algorithm indicates that the network system based on PSO algorithm is of better training performance, and of less overall output error compared with those of the BP algorithm. It has been proved that the neural network system for fault diagnosis based on PSO algorithm is of higher probability of identifying multi-fault symptoms, and of rapid convergence and higher diagnosis accuracy, and that the neural network system for fault diagnosis expects a wide application in the field of mechanic fault diagnosis because of its higher searching efficiency.
Authors
Hongxia Pan
Journal
Journal name not available for this finding