摘要：基于统计学理论的支持向量机因其具有良好的学习性能和泛化能力，而被国内外学者广泛地应用于电机故障诊断领域。对现有应用于电机故障诊断的各种支持向量机模型的特点进行了系统的分析，包括标准型支持向量机、最小二乘支持向量机以及和其相关的混合模型，并对未来电机故障诊断方法的研究发展方向进行了总结和探讨。
关键词：电机故障诊断；标准支持向量机；最小二乘支持向量机

Abstract: Support vector machines (SVMs) based on statistical learning theory are widely used in the field of motor fault diagnosis because of their good learning performance and generalization ability. The characteristics of various support vector machine models used in motor fault diagnosis were analyzed systematically, including the standard support vector machine, the least squares support vector machine and the related hybrid model. The development direction of the future motor fault diagnosis method was summarized and discussed.
Key words: motor fault diagnosis; standard SVMs; least squares SVMs