Simulation analysis reveals noise impacts on sensitivity calibration of ultrasonic sensors in transformers, suggesting improved denoising techniques.
As a critical component in transformer partial discharge monitoring and localisation, the output signal of the contact ultrasonic sensor is significantly influenced by its sensitivity. Consequently, field sensitivity verification of ultrasonic sensors is essential. However, field calibration is often impacted by environmental noise, and the effects of various noise types on the sensitivity calibration results remain inadequately understood. To address this issue, this paper introduces a sensitivity field calibration process tailored for ultrasonic sensors used in oil‐immersed transformer. Transformer and ultrasonic sensor models are developed, and the sensor output signal is simulated using the finite element method. Noise signals of different types are superimposed to evaluate their effects on the sensitivity calibration results. The results indicate that under the interference of narrowband noise, white noise, and mixed noise, significant errors occur in both the root mean square fluctuation of the sensitivity curve and the peak sensitivity, whereas the error in mean sensitivity is comparatively smaller than that of the aforementioned indicators. These results provide a theoretical foundation for the development of targeted denoising techniques during field verification.
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Zhou et al. (2025) studied this question.
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