Abstract
When infrared gas detection technology is applied to monitor gases, the detection accuracy decreases due to the influence of systematic noise. The noises are filtered using traditional denoising methods; however, these methods affect the useful signal. An infrared photoelectric signal is analyzed using the parameter-tuning stochastic resonance method. Based on the parameter normalization frequency and the output SNR tuning bistable system parameters, the system reaches the optimal resonance state, and the signal after denoising is obtained using the Runge–Kutta algorithm. The numerical simulation is conducted on the periodic photoelectric signal with input SNR of 10 dB. It is determined that the method is suitable for the photoelectric signal detection with a frequency from 1 to 10 Hz and that the output SNR is increased to 20 dB in the optimal resonance state. The comparison experiment results show that this method can improve the original signal more effectively than other denoising methods, improving the SNR to 25 dB. In the CO2 standard gas concentration range of 0% to 5%, the maximum relative error of inversion is ±7 % , and the correlation between the inversion result and the standard concentration is 0.9982. This suggests that the proposed method is effective for infrared photoelectric signal detection under strong noise conditions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
