| Title | Comparison on Multiple Signal Analysis Method in Transformer Core Looseness Fault |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Yuan, Fuxiang, Shang, Yu, Yang, Dingge, Gao, Jian, Han, Yanhua, Wu, Jingfeng |
| Conference Name | 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) |
| Keywords | core looseness, Cyber-physical systems, Empirical mode decomposition, fault diagnosis, human factors, Metrics, multiple fault diagnosis, pubcrawl, Resiliency, Time-frequency Analysis, Transformer cores, vibration analysis, vibration signal, Vibrations, wavelet analysis, wavelet transforms |
| Abstract | The core looseness fault is an important part of transformer fault. The state of the core can be obtained by analyzing the vibration signal. Vibration analysis method has been used in transformer condition monitoring and fault diagnosis for many years, while different methods produce different results. In order to select the correct method in engineering application, five kinds of joint time-frequency analysis methods, such as short-time Fourier transform, Wigner-Ville distribution, S transform, wavelet transform and empirical mode decomposition are compared, and the advantages and disadvantages of these methods for dealing with the vibration signal of transformer core are analyzed in this paper. It indicates that wavelet transform and empirical mode decomposition have more advantages in the diagnosis of core looseness fault. The conclusions have referential significance for the diagnosis of transformer faults in engineering. |
| DOI | 10.1109/IPEC51340.2021.9421281 |
| Citation Key | yuan_comparison_2021 |
Comparison on Multiple Signal Analysis Method in Transformer Core Looseness Fault