大型烟气机组的全面在线诊断与预测技术研究  

Full-scale Online Diagnosis and Prediction Technology of Huge Stack Gas Turbine Set

作　　者：胡阳[1] 吴国新[1] 王吉芳[1] 

机构地区：[1]北京信息科技大学机电系统测控北京市重点实验室

出　　处：《电子技术（上海）》2008年第12期71-74,共4页Electronic Technology

基　　金：北京市自然基金(3062008);机电系统测控北京市重点实验室开发项目(KF20071123203)资助

摘　　要：通过对大型烟气发电机组发生故障时振动信号特点的分析及现场测试,利用无量纲振动信号分析技术,进行故障的长期在线诊断及预测预报技术研究,并提出了采用声发射技术结合振动分析的方法,实现了对烟机机组运行状态的全面在线监测诊断与预测。运用表明,这种混合型的分析方法诊断效果良好,能满足实际需求,为大型烟机组故障的在线诊断与预测提供了一种可行的新方法。Based on the feature analysis of vibration signal and the spot test of the huge stack gas turbine set when faults happen,non-dimension parameters diagnosis technology is used for long- period online diagnosis and prediction technology research of the faults.The method which combines acoustic emission technology and vibration analysis is put forward in this paper,and the full- scale online inspection diagnosis and prediction for the running state of the huge stack gas turbine set.The application shows that this combined analysis method has a good diagnosis effect. It can meet practical demands and provide a new available method for the online fault diagnosis and predication of the huge stack gas turbine set.

关 键 词：烟气轮机 振动信号分析 声发射 故障诊断 状态预测 

分 类 号：TH165.3[机械工程—机械制造及自动化]