湖南电力 ›› 2024, Vol. 44 ›› Issue (6): 141-146.doi: 10.3969/j.issn.1008-0198.2024.06.020

• 故障与分析 • 上一篇    

基于混沌理论的变压器绕组松动故障诊断方法

颜锦1, 王喻玺1, 马文博2, 龚星宇1, 颜子睿1, 马宏忠3   

  1. 1.国网湖南省电力有限公司衡阳供电公司,湖南 衡阳 421001;
    2.南京国电南自自动化有限公司质量管理部,江苏 南京 211153;
    3.河海大学能源与电气学院,江苏 南京 211100
  • 收稿日期:2024-09-11 修回日期:2024-10-17 出版日期:2024-12-25 发布日期:2024-12-25
  • 通信作者: 颜锦(1995),男,硕士,主要研究方向为电力设备状态监测与故障诊断。
  • 基金资助:
    国家自然科学基金(51577050)

Diagnosis Methods of Transformer Winding Loos‍ening Faults Based on Chaos Theory

YAN Jin1, WANG Yuxi1, MA Wenbo2, GONG Xingyu1, YAN Zirui1, MA Hongzhong3   

  1. 1. State Grid Hengyang Power Supply Company, Hengyang 421001, China;
    2. Nanjing SAC Power Grid Automation Company Limited, Nanjing 211153, China;
    3. College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
  • Received:2024-09-11 Revised:2024-10-17 Online:2024-12-25 Published:2024-12-25

摘要: 针对变压器空载合闸振动信号具有非线性、非平稳性及瞬变性,导致故障特征提取困难问题,提出一种基于混沌理论的变压器绕组松动故障诊断方法。首先,采用互信息值法确定最佳延迟时间。其次,使用伪邻近点法选择嵌入维数,对绕组正常和松动故障状态下的空载合闸振动信号进行相空间重构,详细分析变压器绕组在不同压紧状态下振动信号混沌吸引子的变化规律。最后,从混沌吸引子中提取相关混沌特征参数,即最大李雅普诺夫指数和关联维数,研究其与变压器绕组压紧状态之间的关系。研究结果表明,变压器空载合闸振动信号的混沌特征能够有效反映变压器绕组松动故障,为变压器绕组松动故障诊断提供新的方法。

关键词: 变压器, 绕组松动, 混沌理论, 振动信号, 故障诊断

Abstract: Aiming at the problem that the transformer no-load closing vibration signals is nonlinear,non-stationary and transient, which leads to the difficulty of fault feature extraction, a method of transformer winding loosening fault diagnosis based on chaos theory is proposed. Firstly, the mutual information value method is used to determine the optimal delay time. Secondly, the pseudo-neighbour method is used to select the embedding dimension,and the phase space reconstruction of transformer no-load closing vibration signals under the normal and loose fault states of the winding is performed. The change rules in chaotic attractor of transformer winding vibration signals under different compression stateis are analyzed in detail. Finally, the relevant chaotic feature parameters, namely,the maximum Lyapunov exponent and correlation dimension,are extracted from the chaotic attractor,and the relationship between them and the compression state of transformer winding is studied. The research results show that the chaotic features of transformer no-load closing vibration signals can effectively reflect the transformer winding loosening fault and provide a new method for transformer winding loosening fault diagnosis.

Key words: transformer, winding loosening, chaos theory, vibration signals, fault diagnosis

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