In this paper, a study is made on the distribution of noise spectrum characteristics of a 500 kV transformer operating at 80% and 100% of the rated current and 80% and 100% of the rated voltage. To improve the ability of identifying transformer noise in different factory conditions, the short-time strong correlation of line spectrum of transformer vibration noise is used to obtain high-quality reconstruction signal, the line spectrum SNR over detection threshold is extracted through CFAR processing, and 100 Hz and frequency doubling are identified. The test results show that the reconstruction signal is improved by 3–5 dB compared with the detected SNR of original line spectrum, and more vibration line spectrum can be extracted, thus providing more information about the line spectrum for diagnosis, monitoring and identification of transformer factory noise fault.
KEYWORDS: Transformers, Sensors, Acoustics, Fluctuations and noise, Velocity measurements, Signal processing, Data acquisition, Testing and analysis, Standards development
The main source of noise in the substation is the power transformer. The radiated sound intensity of transformer noise is an important factor affecting boundary noise of substation. It is also an important parameter of equipment factory control. In this paper, the noise intensity of variable voltage under no-load voltage and load current is tested. The transformer noise testing datum is designed. The factory noise intensity characteristics of 220kV power transformer are obtained. The project provides accurate test data for transformer factory noise evaluation.
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