Noise Reduction Study of Vacuum Interrupter Vacuum Level Spectra for Terahertz Detection Based on IWT-RTS
Shan Gao, Ke Zhao, Jingjun Wang, Hongtao Li, Hanyan Xiao · 2024
In order to address the issues of poor signal stability and low detection accuracy caused by noise interference in the terahertz spectral signals of vacuum interrupters, this study proposes a multidimensional fusion optimization method for noise reduction. Firstly, the PIMAF algorithm is employed during the signal sampling phase to eliminate potential sampling biases. Subsequently, the IWT algorithm is applied for comprehensive denoising of the signals. Finally, the RTS filtering algorithm is utilized to optimize the local peak intervals within the signal, significantly reducing noise and further enhancing signal quality-particularly in regions corresponding to terahertz pulse peaks. Additionally, experimental comparisons demonstrate that, compared with traditional wavelet thresholding noise reduction algorithms, the proposed method exhibits superior performance regarding noise reduction metrics and effectively restores characteristics of terahertz spectral signals.