M-FSVM在可靠性寿命分布模式识别中的应用  

Identification of Reliability Life Distribution with Multi-class Fuzzy Support Vector Machine

作　　者：景涛[1] 曹克强[1] 胡良谋[1] 高斌[1] 

机构地区：[1]空军工程大学航空航天工程学院,西安710038

出　　处：《宇航计测技术》2015年第4期58-63,共6页Journal of Astronautic Metrology and Measurement

摘　　要：在产品的可靠性研究中,准确、有效地识别产品所属的寿命分布,是可靠性建模成败的关键。针对传统支持向量机(SVM)在解决多分类问题时存在不可分区域等缺陷,提出了一种基于多分类模糊支持向量机(M-FSVM)的可靠性寿命分布模式识别方法,建立了包括指数分布、正态分布、对数正态分布和威布尔分布四种常用寿命分布模式识别的模糊支持向量机模型,并进行了仿真试验研究。仿真试验结果表明,该模型能够克服传统支持向量机中存在的不足,能够对常用的寿命分布模式进行智能识别,识别率高,便于工程应用。In the field of product reliability study, identifying the reliability life distribution of a product accurately and efficiently is a key to the result of reliability modeling. The traditional Support Vector Machine （SVM） has some defects, such as unclassifiable region in multiclass classification. Ai- ming at those defects, a method of identifying the reliability life distribution with Multi-class Fuzzy Sup- port Vector Machine （M-FSVM） is proposed, establishing four common models of reliability life distribution including exponential distribution, normal distribution, lognormal distribution and Weibull distribu- tion, and is confirmed by simulation. The results show that, this method can overcome the shortcomings of traditional SVM, identify common life distribution intelligently with high recognition rate, and is con- venient for the engineering application.

关 键 词：多分类模糊支持向量机 寿命分布 可靠性 模式识别 

分 类 号：TP202.1[自动化与计算机技术—检测技术与自动化装置]