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.

Automated Alignment of U-Notch in Iron Caps Using Machine Vision: A System for Suspended Insulators

“…As the position of the four vertices is not fixed, combined with the characteristics of the coordinates of the four vertices of the minimum outer rectangle, through the box [0], box [1] and box [2] three points to find the length of the box [0] and box [1], box [1] and box [2], resulting in the length of the rectangle adjacent to the length of the two sides of the distance 1 and distance 2, through the length of the length of the comparison can be determined the long side and short side, can be fixed to get the long side (AB) coordinates, the formula is:…”

“…To achieve automation in the production of suspended insulators, the alignment of the iron notch must be absent. In traditional automated production measurement, the typical method is to use calipers, goniometers, or angle gauges to measure a certain parameter of the workpiece several times, then the average value [1]. With the rapid development of science and technology and the popularity of machine vision technology, there are more and more algorithms for image detection and recognition, such as the non-contact rotation angle measurement method based on a monocular camera [2], image direction determination based on feature extraction [3], dynamic angle measurement method based on machine vision [4], 3D vertebra rotation angle automatic measurement direction recognition based on deep learning [5].…”

Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision

“…Finally, they calculated the surface braiding angle information through image rotation and gray projection. Reference [13] addressed the problem of slow angle detection of conductive slip ring brushes by applying machine vision and image processing algorithms to measure the key components of conductive slip ring Although the existing literature proposes detection methods that provide satisfactory results for the parameters under test, there are still issues regarding their applicability. Therefore, this article utilizes machine vision technology to design a noncontact method for measuring the tilt angle of transformer windings.…”

“…Finally, they calculated the surface braiding angle information through image rotation and gray projection. Reference [ 13 ] addressed the problem of slow angle detection of conductive slip ring brushes by applying machine vision and image processing algorithms to measure the key components of conductive slip ring brushes, using the Shi–Tomasi angular point detection algorithm to obtain the position information of the brushes and using the positioning block as a reference, the actual angle information of the brushes was calculated using tangent lines. Reference [ 14 ] investigated the optical properties of fiber materials and proposed a photometric stereo vision method to measure the diffuse reflectance and specular reflectance of each pixel as well as the fiber orientation.…”

Analysis of Kinematics and Dynamics of Rolling Ring Based on Finite Element Method

“…An optimization scheme for the aluminum shielding structure, insulating baffle, and grounding structure is proposed. Li [10] proposed a brush angle measurement and control method based on machine vision. Zhang [11] proved that crystalline nanocrystals have higher electromagnetic compatibility in slip rings compared with other magnetic materials.…”