Fault Diagnosis of Cultivator Gear Box Based on IPSO Optimization PNN Method
Analyzing the vibration signal of the gear box of the tiller is helpful to judge the fault diagnosis re-sult.Probabilistic neural network(PNN)has the ability of adaptive learning,nonlinear analysis and excellent fault signal recognition,which can make up for the defects of neural network algorithm.An IPSO optimization PNN method is designed and applied in the field of vibration signal detection of gear box to realize the accurate judgment of vibration parameters.The results show that the proposed algorithm can also eliminate the redundant operations in the repeated iterative calculation process and greatly shorten the time required for vibration classification process.This research is helpful to improve the operation efficiency of agricultural machinery and equipment,which can be extended to other mechanical transmission fields and has a wide range of application markets.
NETL
NSTL
万方数据
维普
