Fault diagnosis for diesel cylinder liner wear based on fuzzy neural network

摘要

A multi-source and multi-dimension information fusion method based on the fuzzy neural network is discussed. The multi-source and multi-dimension wear fault information of diesel cylinder liner, which includes the cylinder block surface vibration and the lubricant iron spectrum analyses is acquired by imitated experiment, and then is preprocessed. Thus problems of the fuzzy neural network model, such as the fuzzy input method, the membership function of the output vectors, the choice of the train sample and network training are solved; the uncertainty of the fault diagnosis is decreased moderately; the accuracy of the fault diagnosis is increased greatly.