“…To address this, an online monitoring and fault diagnosis technology for OLTCs has emerged, significantly reducing costs and improving maintenance efficiency. Various signal processing and fault diagnosis methods have been proposed by scholars, including hidden Markov chain [3], short-time Fourier transform (STFT) [4], wavelet transform (WT) [5,6], empirical mode decomposition (EMD) [7,8], Hilbert transform (HT) [9,10], K-means cluster analysis [11,12], fuzzy C-means clustering (FCM) analysis [13,14], and others. These methods primarily rely on mechanical vibration signals for fault diagnosis of OLTC, but they have not yielded satisfactory results.…”