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异常振动分析识别汽轮发电机组转子裂纹故障
引用本文:张学延,李德勇,牟芳信,汪广慧,卢一兵.异常振动分析识别汽轮发电机组转子裂纹故障[J].中国电力,2013,46(1):40-45.
作者姓名:张学延  李德勇  牟芳信  汪广慧  卢一兵
作者单位:1. 西安热工研究院有限公司,陕西 西安 710032; 2. 华能伊敏煤电有限责任公司发电厂,内蒙古 呼伦贝尔 021134; 3. 华电新乡发电有限公司,河南 新乡 453635; 4. 河南电力试验研究院,河南 郑州 450052
摘    要:转子裂纹可能导致汽轮发电机组发生断轴毁机事故并造成重大损失,在机组运行中及时发现转子裂纹对于保障机组的安全稳定运行具有重要现实意义。在归纳总结裂纹转子振动特性研究结果的基础上,结合现场振动故障诊断经验,提出较为实用的异常振动分析识别裂纹转子的方法,并且通过对2台600 MW等级机组异常振动的分析和诊断,介绍了发电机转子和低压转子裂纹的发现过程。由于判断准确,及时停机检查,发现了裂纹,从而避免了机组继续运行可能发生的灾难性事故。

关 键 词:汽轮发电机组  转子裂纹  异常振动  故障识别  
收稿时间:2012-08-24

Turbo-Generator Rotor Crack Identification by Abnormal Vibration Analysis
ZHANG Xue-yan , LI De-yong , MU Fang-xin , WANG Guang-hui , LU Yi-bing.Turbo-Generator Rotor Crack Identification by Abnormal Vibration Analysis[J].Electric Power,2013,46(1):40-45.
Authors:ZHANG Xue-yan  LI De-yong  MU Fang-xin  WANG Guang-hui  LU Yi-bing
Affiliation:1. Xi’an Thermal Power Research Institute Co. Ltd., Xi’an 710032, China; 2. Huaneng Yimin Coal & Electricity Co., Ltd. Power Plant, Hulunbeier 021134, China; 3. Huadian Xinxiang Power Generation Co., Ltd., Xinxiang 453635, China; 4. Henan Electric Power Test Research Institute, Zhengzhou 450052, China
Abstract:Rotor cracks may lead to turbine-generator shaft broken accident, causing the unit to be destroyed and producing great losses. Therefore, how to timely detect rotor cracks to ensure the safe and stable operation of the unit is significantly and practically important. Based on the summarization of the research results of the vibration characteristics of cracked rotors and combined with the experience of field vibration fault diagnoses, a practical method of identifying cracked rotors with abnormal vibration analysis is proposed. Through analyzing the abnormal vibration of two 600-MW units, the process of detecting the rotor crack is introduced. Because the diagnosis is accurate, the unit is timely stopped for check, and the defect is identified, thus avoiding catastrophic accidents if the unit continues running.
Keywords:turbine-generator set  rotor crack  abnormal vibration  fault identification  
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