【摘要】 支持向量机作为一种基于结构风险最小化原则的统计学习理论,目前已广泛地应用于模式识别[1]、函数逼近[2]等研究领域,尤其是在小样本情况下相比传统统计学习理论体现了更好的泛化性能。选择无量纲参数作为支持向量机的特征向量,将其应用于发动机参数采集器的故障诊断中,结果表明,它对发动机参数采集器的故障模式具有很好的分类能力。更多还原

【Abstract】 Support vector machine(SVM),which is based on structural risk minimization principle,is now widely used in pattern recognition,function approximation and other research fields.It shows better generalization ability than traditional statistical learning theory,especially,when used to small sample.Some dimensionless parameter is selected as the eigenvalue,and support vector machine is applied to fault diagnosis in engine parameter acquisition unit.Experimental result proves that it has good capability in fault pattern classification of engine parameter acquisition unit.更多还原