摘要
针对现有柴油机磨损模式判别方法中存在的不足,将支持向量机算法应用到柴油机磨损模式的识别中,建立了基于支持向量机的柴油机磨损模式判断模型,并对部分实验柴油机油液样本进行了评估,并与广义贴近算法、模糊聚类算法和专家评判结果进行了比较,证明了支持向量机能够准确、有效地识别柴油机磨损模式。
In view of the existing shortcomings on the course of wear mode identifying method on diesel en- gines, the support vector machine （SVM） algorithm was applied to the wear mode identifying. The recog- nition mode for the wear of diesel engine which was based on the SVM algorithm was established, and sev- eral oil samples of experimental diesel engines were estimated. The result was compared with results of generalized closeness degree algorithm, fuzzy clustering algorithm and expert assessment, and we proved that the wear mode of diesel engine can be effectively and accurately recognized by the SVM method.
出处
《四川兵工学报》
CAS
2015年第8期96-99,共4页
Journal of Sichuan Ordnance
