关键词: 最小二乘支持向量机, 二进制微分进化, 故障诊断, 小波变换

Abstract: Aiming at problem of few samples and non-linear characteristics in diesel engine fault diagnosis, Least Squares Support Vector Machine（LSSVM） can be better to diagnostic studies, but the results of diagnosis are greatly influenced by the penalty factor and the selection of kernel parameters, it is necessary to optimize its parameters, LSSVM algorithm based on Binary Differential Evolution（BDE） is proposed. For the data of diesel engine valve vibration signal used as the characteristics values of model, and wavelet transformed, the fault diagnosis model based on BDE-LSSVM is established. Compared with LSSVM model based on the particle swarm algorithm and genetic algorithm, the results show that LSSVM with BDE has better fitness value and stability, as well as more perfect accuracy and speed in the diagnosis classification.

Key words: Least Squares Support Vector Machines（LSSVM）, Binary Differential Evolution（BDE）, fault diagnosis, wavelet transform