Design of condition monitoring system for power transformer based on vibration signal

The vibration signal of transformer body contains abundant fault information. Extracting the effective characteristic parameters from the vibration signal can be used as an important basis for transformer fault diagnosis, which is the main method for non-intrusive monitoring of transformer faults at present. According to the vibration generation and transmission mechanism of transformer noumenon, this paper uses piezoelectric sensors, signal conditioning modules, high-speed data acquisition card and computer set up the transformer vibration monitoring system, and takes graphical language LabVIEW as the system software development platform. Wavelet packet-energy spectrum analysis method is used to analyze the vibration signal on the surface of transformer oil tank in time domain and frequency domain, quantifying the energy distribution of vibration signal in different frequency bands, and taking the percentage of each frequency band energy in the total energy as the characteristic parameter to monitor and diagnose the operation status of transformer. Field test results show that there is a significant difference in the energy distribution of the vibration signals before and after the transformer failure. This method can effectively extract the characteristics of the vibration signal in different states and obtain the percentage of energy distribution of the vibration signal in each frequency band, which can be used as the basis for transformer fault diagnosis.