Signal-to-noise ratio enhancement for MEMS resonant sensors with potential barrier adjustable stochastic resonance

The signature of stochastic resonance is that additional noise surprisingly enhances the signal-to-noise ratio (SNR). A noise-adaptive system that learns to add an optimal amount of noise to trigger stochastic resonance and improve SNR is known as adaptive stochastic resonance. However, the current stochastic resonance mechanism fails when environmental noise exceeds the optimal noise level, as any additional noise merely worsens the SNR. In this case, instead of adding noise, stochastic resonance can be facilitated by adapting the potential energy landscape of the bistable system. Here, we propose a novel approach to enhance SNR in noisy environments, involving a potential adjustable microelectromechanical systems resonator. A periodic signal with an amplitude of 0.28 Vrms is buried in ambient noise, emulated by a white noise signal with amplitude ranging from 0.7 Vrms to 4 Vrms. Experimental results show that when the ambient noise exceeds 1 Vrms, adding additional noise leads to a decline in SNR. However, SNR enhancement induced by stochastic resonance is experimentally demonstrated by tuning the potential well of the resonator. This advancement highlights the feasibility of potential adjustable systems to overcome the limitations of conventional noise adjustable stochastic resonance methods in noisy environments. The proposed mechanism is further applied to detect the frequency of 2.7 nN periodic forces with various waveforms.