关键词: 贯流风叶, 粘连, 支持向量机, 核函数, 数学模型, 诊断

Abstract:

A defects diagnosis method based on support vector machine is proposed for better accuracy and robustness of crossflow fan leaf blade adhesion defects diagnosis. The linear kernel is used as the inner product kernel function. The mathematical model of crossflow fan leaf blade adhesion defects diagnosis is established under the premise of pursuing maximum interval in classification. The simulation and actual test results show that the model reaches a higher accuracy of leaf blade adhesion defects diagnosis even with less training samples and has better performance than the traditional defects diagnosis methods.

Key words: cross flow fan, adhesion, support vector machine, kernel function, mathematical model, diagnosis