Cable-driven transmissions are used widely in robotic applications. However, design variables and parameters of this kind of transmission remain under study, both analytically and experimentally. In this paper, an experimental test bench to evaluate the behavior of medium-low power pulley-cable transmissions is presented. The design of the test bench allows manipulating variables such as dimensions, external load, speed, and cable tension. The system consists mainly of a brushless direct current (DC) motor, two load cells to measure the mechanical reactive force in the motor, two dismountable pulleys, two drums, a perforated disk, and several masses that provide the load and the inertial load, and electronic modules to control the speed and position of the pulley. Special attention was paid to the calibration of the load cells, focused in compensating the effect of creep. Validation tests were carried out in order to evaluate the device design. Next, pilot experiments were performed to estimate the friction behavior in the transmission. Preliminary results suggest that the friction in the transmission is largely governed by the friction behavior of the bearings.
Although many friction models have been developed by various researchers over the years, a general model does not exist yet. In this article, we present the work that was developed to identify and propose an empirical model that represents the behavior of friction in a cable-driven transmission. We designed and built a test bench that allowed us to study the incidence of friction as evidenced by the type of cable thread, the dimensions of the pulley and the capstan and the application of an external load for pulley-cable type transmissions in a variety of configurations. The results obtained show a marked influence of the external load on friction behavior. Based on these results, we propose a friction model that involves the external load and the transmission ratio. During the validation of the model, it was found that the proposed model reproduced the friction behavior better than the LuGre model, obtaining errors up to 44% lower, mainly for high loads and low speeds.
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