噪声与振动控制

噪声与振动控制 ›› 2012, Vol. 32 ›› Issue (4): 153-157.DOI: 10.3969/j.issn.1006-1355.2012.04.034

• 6.信号处理与故障诊断 • 上一篇    下一篇

大型变压器故障诊断识别方法

何洪军1, 饶柱石1, 邵宇鹰 2, 荆建平1   

  1. 1. 上海交通大学 机械系统与振动国家重点实验室，上海 200240 2. 上海电力公司, 200203 上海 )
  • 收稿日期:2011-07-04 修回日期:2011-10-12 出版日期:2012-08-18 发布日期:2012-08-18
  • 通讯作者: 何洪军

Large Transformer Fault Diagnosis Identification Method

HE Hong-jun 1, RAO Zhu-shi 1, SHAO Yu-ying 2 , JIN Gjian-ping 1   

  1. （ 1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiaotong University, Shanghai 200240， China;2. Shanghai Municipal Electric Power Company, Shanghai 200203, China ）
  • Received:2011-07-04 Revised:2011-10-12 Online:2012-08-18 Published:2012-08-18

摘要： (大型电力变压器传统的电测法故障诊断不仅过程复杂而且还不能有效地识别故障原因。由此，基于隐马尔科夫模型（HMM）和模糊集诊断识别原理的基础上，提出了对变压器绕组故障识别更有效的方法，即双规识别法。通过理论仿真并结合实验验证，这种方法可以对变压器的状态类型作出准确的识别。

关键词: 振动与波, 故障诊断, 马尔科夫模型, 变压器, 绕组

Abstract: arge power transformer traditional electrical measurement fault diagnosis method not only process is complicated and still can't effectively identify the cause of the problem. Thus, based on a hidden Markofv model (HMM) and fuzzy set diagnosis, this paper puts forward more effective method for the fault recognition of transformer winding , namely detained recognition method. Through simulation and experimental validation, this method can make accurate state of transformer type of recognition.

Key words: Lvibration and wave, fault diagnosis, hidden Markov model, transformer, winding

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