Electrical engineering

Physics

Pattern recognition (psychology)

Chip

Mathematics

Algorithm

Statistics

Filter (signal processing)

Mean squared error

Machine learning

Engineering

Voltage

Artificial intelligence

Vibration

Acoustics

Hilbert–Huang transform

STM32

Correlation coefficient

Computer science

Computer vision

Transformer

Telecommunications

Journal of Intelligent Systems

This paper presents a method for the study of the influence of stability of a power transformer on the power system based on the vibration principle. Traditionally, the EMD and EEMD algorithms are employed to test the box vibration signal data of the power transformer under three working conditions. The proposed method utilizes a partial EMD screening along with MPEEMD method for the online monitoring of power transformer. A complete online monitoring system is designed by using the STM32 processor and LabVIEW system. The proposed system is compared with EMD and EEMD algorithms in terms of the number of IMFs obtained by decomposition, maximum correlation coefficient, and mean square error. The inherent mode correlation, when compared with the mean square error of the reconstructed signal, shows that the reconstruction error of MPEEMD algorithm is 4.762×10 −15 which is better than the traditional EMD algorithm. It is observed from the results that the proposed method outperforms both EMD and EEMD algorithms.

Online Monitoring Technology of Power Transformer based on Vibration Analysis