Study on weak signal amplitude detection and circuit simulation based on a new chaotic system

The filtering circuit is a crucial component in signal conditioning systems for noise reduction. However, its susceptibility to the measurement environment makes it challenging for signal conditioning circuits to process weak signals with high precision. In the context of flow signal detection using slurry-type electromagnetic flowmeters, the limited capability of traditional filter circuits to detect weak signals has led to difficulties in the measurement of small flow signals. To address this, in this study, we present a novel N-dimensional nonlinear dynamic system designed to outperform conventional filter circuits in weak signal detection. Under the excitation of weak low-frequency square wave signals, we verified the existence of chaotic states in the proposed system and analysed its chaos synchronisation. We proposed a method for detecting weak low-frequency square wave signals in the time domain using chaos synchronisation, thus overcoming the limitation of traditional chaotic systems, which are typically constrained to phase diagram analysis for weak signal detection. Numerical simulation and circuit simulation experiments were conducted, and the results showed that, in the absence of noise, the chaos synchronisation curve outputted by the new chaotic system demonstrates a linear relationship with the inputted weak square wave signal. The peak-to-peak values derived from the curve were used to accurately determine the amplitudes of weak square wave signals. A signal processing procedure was proposed to identify the amplitudes of weak signals under strong noise interference based on the peak-to-peak values outputted by the new chaotic system and two traditional analogue filters. Circuit simulation results showed that, under the influence of noise, the accuracy of the new chaotic circuit in linearly recognising the weak square wave amplitude was as high as 93.39 %, whereas those of the band-pass and low-pass filter circuits were only 81.76 % and 74.42 %, respectively. This validates the excellent anti-noise ability of chaotic circuits, which is essential for weak signal detection.