Transverse and Longitudinal Vibration Measurement of Vertical Rope of Hoisting System Based on Machine Vision

Lateral and longitudinal vibration of vertical rope, which reflect the force characteristics of itself, are important parameters for fault diagnosis and condition monitoring of hoisting system, and the measurement result is the basis for failure analysis and vibration control. In this study, a novel vision-based measurement framework, which contains image preprocessing (IP) part and target tracking part based on accelerated modified inverse compositional (AMIC) algorithm, called IP-AMIC, is proposed to obtain the rope dynamic displacement. First, IP carried out to eliminate the measurement mutual influence of the transverse and longitudinal vibration of vertical rope. Additionally, a variable step-size strategy is used to increase the speed of the Lucas–Kanade algorithm, tracking speed reaches 500 fps (frame per second) with subpixel accuracy. The accuracy and efficiency of the proposed algorithm are demonstrated in the laboratory experiment. Finally, a field experiment of vertical rope vibration measurement of hoisting system is carried out, analyzed the dynamic displacement of ropes during unloading process. Experimental results show that the proposed algorithm can automatically adjust posture of the rope and obtain the lateral and longitudinal vibration of the vertical rope efficiently.