【摘要】 针对因缺少大量故障数据样本而制约机械故障智能诊断的问题 ,本文改进了支持向量机多故障分类算法 ,依据此算法建立了多故障分类器 ,并应用于汽轮发电机组的故障诊断。应用结果表明 ,不必进行信号预处理以提取特征量 ,只需要用少量的时域故障数据样本建立故障分类器。该故障分类器可实现多故障的识别和诊断 ,并且具有算法简单、可对故障在线分类和故障分类能力强的优点更多还原

【Abstract】 This paper improves a multi-classification algorithm of support vector machine, and a multi-fault classifier based on the algorithm is constructed. Training the multi-fault classifier only needs a small quantity of fault data samples in time domain, and does not need signal preprocessing for extracting signal features. The multi-fault classifier was applied to fault diagnosis of steam turbine generator, and the results show that it has such advantages as simple algorithm, online fault classification and excellent capability of fault classification.更多还原