Vision-Based Moving Mass Detection by Time-Varying Structure Vibration Monitoring

In recent years, vision-based vibration measurement methods have been widely used in the field of mechanical engineering for structural health monitoring and fault diagnosis. However, these current methods mainly focus on monitoring the stationary vibrations of time-invariant systems or structures, which cannot deal with the time-varying conditions. In this paper, a video camera is used to monitor the non-stationary vibrations of a time-varying structure for an unexplored usage of moving mass detection. In the study, the laboratory time-varying structure is a clamped beam with one or more masses sliding on. The general parameterized time-frequency transform is first introduced to extract the time-dependent instantaneous frequencies (IFs) from the video motions. Then a parameterized mathematical model is proposed to estimate the weight of the moving mass based on the extracted IFs. By optimizing the parameters in this model, the moving mass can be estimated with high precision. Besides, multi-moving masses can be also detected for abnormal mass classification and identification. Both the finite element method (FEM) and experiments are performed to demonstrate the performance of the proposed vision-based moving mass detection (VMMD) technique. The VMMD technique has valuable potential for online detection, localization and classification of inferior products with abnormal mass in industrial automation.

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