A vibration transducer framework for the measurement and reconstruction of vibration signals via low-rate sampling

Abstract

This study presents a novel, cost-effective, and highly accurate computer vision-based vibration transducer framework, enabling the measurement and reconstruction of vibration signals using video frames captured at a low frame per second (fps) relative to the Nyquist rate of the measured signal. In the proposed framework, an assembly consisting of several spring-mass systems serves as the primary sensor, while a camera module tracks the motion of the seismic masses as the secondary sensor. The setup, along with the modified compressive sensing equation (CS) equation, results in a transducer scheme that can recover the base motion signals from the displacement history of seismic masses sampled at rates much lower than the maximum predominant frequency of the original signal. The performance of the proposed transducer framework has been successfully verified by numerical simulations. In addition, an experimental study has been conducted in order to validate the concept under modelling and measurement error.