Machine Vision-Based Method for Measuring and Controlling the Angle of Conductive Slip Ring Brushes

Abstract

The conductive slip ring is used for power or signal transmission between two objects rotating relative to each other. It has become an essential part of modern industrial development. In traditional automated production measurements, the typical method is to use calipers, goniometers, or angle gauges to measure a parameter of the workpiece several times and then average it. These inspection means have low measurement accuracy and slow measurement speed, and measurement data cannot be processed in a timely manner. A machine vision-based method for measuring and controlling the angle of the brushes is proposed for this problem. First, the brush angle forming device was built for the conductive slip ring brush wire, forming the principle and rebound characteristics. Then, machine vision and image processing algorithms were applied to measure the key parts of the conductive slip ring brushes. The data of the forming angle value and rebound angle value were obtained during the forming process of the brush wire angle. Finally, a pre-compensation model for the brush filament rebound was developed and validated based on the curve fitting method. The test results show that the error of the angle measurement is within 0.05°. The average error of the measured rebound angle and the calculated rebound angle of the brush filament pre-compensation model was 0.112°, which verifies the correctness of the pre-compensation model. The forming angle can be controlled more precisely, and the contact performance between the brush wire and the ring body can be improved effectively. This method has the potential to be extended to engineering applications.