A Denoising Method for Partial Discharge Ultrasonic Signals in GIS Based on Ultra-High Frequency Signal Synchronization

The insulation condition is the key to determining whether gas insulated switchgears (GISs) can operate stably and reliably. Partial discharge (PD) detection is an important technique for condition monitoring and evaluation in GIS. Acoustic emission (AE) method is commonly used in on-site PD detection. However, in field applications, there are often problems such as low signal-to-noise ratio (SNR) of measured ultrasonic signals and difficulty in extracting PD pulses. To solve this problem, a denoising method for GIS ultrasonic signals based on the combination of ultrasonic and ultra-high frequency (UHF) signals is proposed in this paper. Based on the difference in correlation between noise and PD signals, the noise in measured signal can be suppressed through accumulating and averaging of multiple ultrasonic signals, and the SNR of PD signal can be significantly improved. An actual 500-kV GIS experiment platform is established, and PD measurements for different types of defects are conducted. Then, a comparative study is conducted on the denoising performance of the proposed method and traditional denoising methods, such as wavelet method and singular value decomposition (SVD) method. The results indicate that compared to traditional methods, the method proposed in this paper has a higher reduction in noise level. Especially for extremely low-SNR signals (PD pulses buried in noise), traditional methods have poor performance, while the proposed method can still extract the PD pulse form the noise. Furthermore, based on the denoised ultrasonic signals, the defect localization analysis is conducted to demonstrates the correctness of the denoising results. Finally, the proposed method is applied to on-site PD detection, which further evaluates the effectiveness of the denoising method.