Noise reduction and characteristic analysis of fluid signal in the jet impact‐negative pressure deamination reactor based on wavelet transform

Abstract The jet impact‐negative pressure deamination reactor (JI‐NPDR) is a new type of continuous and efficient deamination equipment. The study of the random flow pattern of porous jet impingement in the reactor under negative pressure conditions is an important issue. In this work, the signal processing method based on wavelet transform is used to analyze the characteristics of random flow signals in the reactor. Meanwhile, an analog similar signal is built and three sets of Gaussian white noise with various signal‐to‐noise ratios are employed via the MATLAB platform. Based on the adjustment of threshold function, threshold, decomposition level and other parameters of wavelet transform, the noise ratio (SNR) and mean squared error (MSE) are used to evaluate the wavelet denoising effect. And then, the optimal denoising scheme for the obtained signal will be applied in processing the vacuum flow signal collected inside the deamination reactor. Subsequently, the 8‐layer wavelet decomposition is investigated by using sym7 as the wavelet basis, soft threshold function, and heursure threshold for signal denoising. Then, the analog signal is fed back through the results of the actual signal denoising, and the number of wavelet decomposition layers is adjusted from 8 to 9 layers to optimize the original wavelet denoising combination. By analyzing the low‐frequency and high‐frequency parts of the signal spectrum before and after denoising, it was found that wavelet transform can effectively denoise the fluid signal in the reactor.