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