Fault diagnosis of diesel engine cylinder wall based on Matlab probabilistic neural network

The diesel engine surface vibration signals contain a wealth of work status information and fault information. According to the time-domain characteristic parameters extracted from these signals can effectively identify the engine working status. Establishing diesel engine cylinder wall fault diagnosis probabilistic neural network (PNN) model based on the vibration signals collected by experiment, training and simulating the generated PNN model by using Matlab neural network toolbox, we obtained the predicted classification results of diesel engine cylinder wall fault, and then verified the reliability of this method.