基于小波与倒频谱技术的烟气轮机轴承故障诊断  

Malfunction Diagnosis of Bearing of Flue Gas Turbine Based on Wavelet and Scrambled Technology

作　　者：于晓红[1] 张来斌[1] 王朝晖[1] 

机构地区：[1]中国石油大学(北京)机电工程学院,北京102249

出　　处：《科学技术与工程》2006年第23期4679-4681,共3页Science Technology and Engineering

基　　金：国家自然科学基金(50105015;50375103);教育部新世纪优秀人才支持计划;北京市科技新星计划(2003B33);北京市教育委员会共建项目建设计划(XK114140478);教育部霍英东青年教师教育基金(91051)共同资助

摘　　要：烟气轮机是石油炼厂催化裂化装置能量回收系统的关键设备,并且长期在高速、高温环境下运行,机组振动较大。轴承是烟气轮机中应用非常广的一种通用机械部件,轴承的运行情况直接影响到整个机组的安全运行,因此,对其状态监测和故障诊断意义重大。分析了轴承的振动特点和故障类型,分别介绍了小波降噪技术和倒频谱分析技术的原理、特点以及在轴承诊断中的优点,并将二者结合起来对烟气轮机的轴承振动进行故障诊断,最后验证了此种方法的有效性。Flue gas turbine, as a typical example of refineries catalysis cracking device, is a key oil refineries energy recovery equipment, it works under high-speed and high-temperature operating environment in a very long time, and the vibration of the working set is biggish. Bearing is a type of universally used machinery unit which is widely used in flue gas turbine, the whole set＇s safe running is directly affected by the bearing＇s running status, thus the monitoring and malfunction diagnosis of the bearing are significant. The vibration specialty and the type of malfunction of bearing and introduced the principle and specialty of wavelet technology and cepstrum analysis technology respectively are analyzed, also the merits of bearing diagnosis is introduced, and at last the effectiveness of this method by combining these two items to make malfunction diagnosis to the bearing vibration of flue gas turbine is validated.

关 键 词：烟气轮机 小波分析 轴承 倒频谱分析 故障诊断 

分 类 号：TH133.3[机械工程—机械制造及自动化]