基于模糊c-均值的设备性能退化评估方法  

Fuzzy c-Means Based Equipment Performance Degradation Assessment

作　　者：潘玉娜[1] 陈进[1] 李兴林[2] 

机构地区：[1]上海交通大学机械与动力工程学院,上海200240 [2]杭州轴承试验研究中心,杭州310022

出　　处：《上海交通大学学报》2009年第11期1794-1797,共4页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金资助项目(50675140);国家高技术研究发展计划(863)项目(2006AA04Z175)

摘　　要：为了更好地实现基于状态的维护模式,提出了一种基于模糊c-均值聚类的性能退化评估方法.该方法以正常状态和失效时刻的数据为基础,建立智能评估模型,以待测数据隶属于正常状态的程度作为退化指标.以6307滚动轴承为研究对象,对其疲劳寿命加速试验中全寿命周期的性能退化进行评估,结果验证了该方法的可行性和有效性.Equipment performance degradation assessment is the complete development of existing fault diagnosis technique, it is more favorable for realizing condition based maintenance. This paper proposed a new method based on fuzzy c-means. It uses the normal state and failure data to build intelligent assessment model, the tested data＇s subjection to normal state as the degradation indicator. 6307 bearing＇s accelerated life test was performed using ABLT-1A, and the assessment result of applying the proposed method to its whole life time shows that this method is feasible and valid.

关 键 词：模糊C-均值聚类 性能退化评估 轴承 

分 类 号：TP206[自动化与计算机技术—检测技术与自动化装置] TP911[自动化与计算机技术—控制科学与工程]