In this paper,focusing on the on-board cylinder damage diagnosis,the cylinder damage diagnosis method is studied,and a cylinder damage diagnosis method based on least square support vector regression(LSSVR)and particle swarm optimization algorithm(PSO)is proposed.The LSSVR parameters are optimized by PSO,and the optimized LSSVR model is obtained.The finite element method of random vibration is used to simulate the situation of multiple groups of damaged cylinders during transportation,and the vertical acceleration and equivalent stress of the damaged location are collected as the inputs to the model to obtain the diagnosis results of cylinder damage.Taking the root mean square error between the diagnostic value and the actual value as the criterion,PSO is adopted to optimize the model parameters,and the diagnostic error is stabilized within 1%,and a more appropriate optimization model is obtained.Compared with BP neural network,support vector regression(SVR)algorithm and unoptimized LSSVR algorithm,the results show that this model exhibits higher accuracy and stability in identification.
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