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Vortex flow meters use microprocessors to adjust and compensate for the meter’s flow characteristics as well as the parameters related to the fluid state, thereby improving the measurement accuracy of the meter and endowing it with various intelligent functions. Another important aspect is its ability to perform signal processing tasks, namely distinguishing between signals and noise and processing them in order to isolate the true signals from the noise. By combining these two aspects effectively, the performance of the instrument can be truly improved. Many studies have been conducted by researchers at home and abroad on the signals and noise associated with vortex flowmeters. These studies mainly focus on the following aspects: 1. Investigating the characteristics and differences between vortex flowmeter signals and noise, as well as applying tracking filtering to these signals and noise. 2. Apply digital techniques to analyze and process the spectra of signals and noise in order to eliminate the impact of noise. 3. Starting from the study of detection methods for vortex street signals, suitable detection elements with strong signals and low noise are selected, as well as the appropriate installation locations for these elements; differential detection elements are used to eliminate the effects of noise and interference. 4. Starting with the study of the stability of Karman vortice streets, experimental investigations were conducted on the geometric parameters of the generating bodies, with the aim of selecting those that produce strong vortice street signals and good stability, thereby improving the signal-to-noise ratio of the vortice streets.