汽轮发电机组故障诊断的节约覆盖集概率模型  

Parsimonious Covering Probability Model for Turbogenerator Vibration Faulty Diagnosis

作　　者：张彼德[1] 孙才新[1] 欧健[1] 胡雪松[1] 

机构地区：[1]重庆大学高电压与电工新技术教育部重点实验室,重庆400044

出　　处：《重庆大学学报（自然科学版）》2002年第5期101-103,107,共4页Journal of Chongqing University

摘　　要：汽轮发电机组的振动故障具有多样性的特点 ,经常出现多种故障同时发生的情况。文中介绍了一种在节约覆盖集理论框架上集成概率推理的诊断模型 ,并在此基础上建立了汽轮发电机组振动多故障诊断的实用模型。以某汽轮发电机组的 2类振动多故障为例验证了该方法的有效性。该模型能有效地识别出汽轮发电机组的多故障 ,弥补了专家系统和神经网络等诊断方法不能正确诊断多故障的不足 。The turbogenerator vibration faults have the character of variety. Many faults often occur synchronously. This paper introduces a diagnosing model based on parsimonious covering theory and probability. A model for turtogenerator's fault diagnosis is proposed. The availability of this method is proved by two fault diagnosis examples of turbogenerator. The results show that the model proposed can be used for multi_fault diagnosis together. It may make up shortage for some of expert systems and neural networks in some aspect. From the practice,this model has higher reliability and practicability.

关 键 词：节约覆盖集理论 概率推理 汽轮发电机组 振动故障 

分 类 号：TM311[电气工程—电机]