现代电力2012，Vol.29Issue(6)：68-73,6.
基于支持向量机与知识的汽轮发电机组智能故障诊断研究
Study of Intelligent Fault Diagnosis Method for Turbo-generator Unit Based on Support Vector Machine and Knowledge
摘要
Abstract
For the low efficiency and poor accuracy of turbogenerator unit's fault diagnosis, this paper divides the common 18 kinds of vibration fault into four categories, and takes advantage of support vector, machine to distinguish the fault cluster for early fault diagnosis according to the characteristics of vibration signal spectrum. For different fault cluster, different fault pattern recognition model is established. With the use of certain symptom group, this article engages in knowledge reasoning to obtain the specific fault recognition mode by using weighted fuzzy logic. Besides, the searching methods of fault cause, fault influence and troubleshooting measures in the knowledge base are proposed, which make the diagnosis process more meticulous and comprehensive. Case analysis shows that it is feasible to use this method to develop a system for intelligent fault diagnosis of turbo-generator unit, which is valuable for further study in more depth.关键词
支持向量机/知识推理/加权模糊逻辑/故障诊断/汽轮发电机组Key words
support vector machine/ knowledge reasoning/ weighted fuzzy logic/ fault diagnosis/ turbo- generator unit分类
信息技术与安全科学引用本文复制引用
黄乃成,顾煜炯,谢骐宇,张国坤..基于支持向量机与知识的汽轮发电机组智能故障诊断研究[J].现代电力,2012,29(6):68-73,6.基金项目
中央高校基本科研业务费专项资金项目(12QX06) （12QX06）
华能集团科技创新项目(HNKJ11-H27) （HNKJ11-H27）
