因OLTC切换时振动信号具有随机性及低频混沌特性，文献[8，9]对OL

Due to the randomness and low-frequency chaotic characteristics of the vibration signal during OLTC switching, the literature [8, 9] reconstructed the phase space of the OLTC vibration signal, identified the operating conditions of the OLTC by defining the phase space coefficients, and proposed the power OLTC fault diagnosis model based on spectrum and invisible Marco chain. However, due to the limitations of the phase space reconstruction algorithm itself, the chaotic information of the signal cannot be fully reflected. Literature [10] introduced the narrow-band noise-assisted multivariate EMD algorithm into the mechanical fault monitoring of the converter OTLC. It mainly suppressed the modal aliasing phenomenon in the EMD algorithm by adding narrow-band noise signals to overcome some of the defects of the traditional methods, and Higher diagnostic efficiency. However, the method of judging the feature matrix used in this method is slightly simpler and still needs further study.

Because the vibration signal has the characteristics of randomness and low frequency chaos when OLTC is switched, the paper, 8,9, reconstructs the OLTC vibration signal, identifies the operating condition of OLTC by defining the phase spatial coefficient, and puts forward the OLTC fault diagnosis model based on the vibration signal power spectrum and the invisible marco chain. However, due to the limitations of phase space reconstruction algorithm itself, signal chaos information can not be fully reflected. In the literature, the narrow band noise-assisted EMD algorithm is introduced into the mechanical fault monitoring of the changer OTLC, and the main content is to suppress some defects of the traditional method by adding narrowband noise signal to suppress the modal aliasing phenomenon in the EMD algorithm, and has high diagnostic efficiency. However, the method used in this method is simple to judge the characteristic matrix, and further research is needed.

Due to the randomness and low-frequency chaos of the vibration signal during OLTC switching, the paper [8,9] reconstructs the phase space of the OLTC vibration signal, identifies the working condition of OLTC by defining the phase space coefficient, and proposes the OLTC fault diagnosis model based on the power spectrum of the vibration signal and the hidden Markov chain. However, due to the limitations of the phase space reconstruction algorithm, the chaotic information of the signal can not be fully reflected. In reference [10], the narrow-band noise assisted multivariate EMD algorithm is introduced into the mechanical fault monitoring of the converter OTLC, which mainly uses the narrow-band noise signal to suppress the modal aliasing phenomenon in the EMD algorithm, overcomes some defects of the traditional method, and has high diagnosis efficiency. However, the judgment method of the characteristic matrix used in this method is a little simple and needs further study.<br>