Fault Diagnosis of Hydraulic Drilling Rig Based on Particle Swarm Optimization RBF Neural Network
Mingzhe Zhang · Coal Mine Machinery · 2012
A fault diagnosis method based on particle swarm optimization radial basis function neural network is proposed that can be used for hydraulic drilling rig.Virtual instrument and LabVIEW are used to acquisition the characteristic signal of hydraulic drilling rig.The central value,directional width and weights of radial basis function neural network are optimized by particle swarm optimization algorithm.Therefore fault diagnosis of hydraulic drilling rig can be implemented.The performance demonstrates that this fault diagnosis method is high accuracy and practicability in case of small samples.