Research on an Ultraviolet Spectral Denoising Algorithm Based on the Improved SVD Method
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Published:2023-11-14
Issue:22
Volume:13
Page:12301
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Qin Zhaoyu1, Wang Zhaofan1, Wang Ruxing1
Affiliation:
1. Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, Hubei University of Technology, Wuhan 430068, China
Abstract
The utilization of ultraviolet (UV) absorption spectroscopy for monitoring the concentration of specific decomposition gas components in gas-insulated switchgear (GIS) can provide a means to assess its insulation status. Nevertheless, UV optical modules currently deployed in the field are susceptible to external interferences like ambient noise and equipment vibrations. Real-time spectral data acquisition often suffers from significant noise contamination, directly impinging on subsequent feature extraction and detection accuracy. This paper presents an optimized singular value decomposition (SVD) noise reduction method for mitigating noisy spectral signals. First, each singular value within the noisy signal is transformed into a component signal. Next, the highest frequency value in the signal serves as an indicator to characterize the signal. Finally, the primary frequency values are arranged based on the decreasing singular values of the original noisy signal. The singular value corresponding to the first primary frequency value surpassing a preset threshold is selected as the effective order for denoising. Random noise with varying intensities was intentionally introduced to the UV spectral signal of sulfur dioxide (SO2), followed by noise reduction procedures. It is shown that the improved SVD noise reduction algorithm proposed in this paper enhances the signal-to-noise ratio (SNR) by 18.02% and 16.86%, and reduces the root-mean-square error (RMSE) by 15.13% and 14.92%, respectively, compared with the singular value difference spectrum (SVDS) denoising method and wavelet transform denoising method under the condition of low SNR. Furthermore, there exists a linear relationship between the concentration of SO2 samples and the eigenvalues of the UV spectra, demonstrating a higher linear goodness with a coefficient of 0.99735. The denoising method proposed in this paper does not require the manual setting of various types of parameters, and has a better ability to deal with the noise of UV spectral signals in engineering sites with complex environments.
Funder
Hubei University of Technology
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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