Design of signal detection and separation device based on FFT algorithm

The swift advancement in microprocessor and digital signal processing technologies has led to the employment of advanced digital tools and evaluators to process and scrutinize the layered signals produced in industrial settings, aiming to yield more precise waveform data for accurate waveform identification and segregation. In pursuit of this goal, the study introduces an innovative "dual-channel signal detection and separation device" on the STM32 platform. This device amalgamates functions like signal mixing, acquisition, spectrum analysis, and signal separation, utilizing the FFT algorithm to identify and distinguish between two signals from identical or varied cycles. Initially, the signal undergoes pre-processing through an adder, followed by AD discrete sampling and FFT processing via the STM32 microprocessor, culminating in signal reconstruction by DAC, culminating in the precise segregation of two-channel periodic signals. Experimental evaluations reveal that the apparatus effectively distinguishes between diverse intricate signal pairings, with the output signal frequency's relative inaccuracy remaining under 8%, thereby confirming its superior efficiency and precision.