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对齿轮故障诊断的特点进行了阐述 ,指出由于环境噪声的干扰 ,在齿轮故障诊断中往往不能获得理想的诊断结果。为此在对齿轮运行状况进行有效特征提取的基础上 ,采用支持向量机的方法对齿轮进行故障诊断。研究结果表明采用该方法可以获得比神经网络和线性判别方法等更准确的诊断结果
The characteristics of gear fault diagnosis are described. It is pointed out that due to the interference of environmental noise, the ideal diagnosis result can not always be obtained in gear fault diagnosis. Therefore, on the basis of extracting the effective features of the running condition of gear, the fault diagnosis of gears is carried out by the method of support vector machine. The results show that this method can get more accurate diagnostic results than neural networks and linear discriminant methods