基于多相机视觉技术的锥齿轮质量检测系统

A Bevel Gear Quality Inspection System Based on Multi-Camera Vision Technology.

作者信息

Liu Ruiling, Zhong Dexing, Lyu Hongqiang, Han Jiuqiang

机构信息

School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

出版信息

Sensors (Basel). 2016 Aug 25;16(9):1364. doi: 10.3390/s16091364.

DOI:10.3390/s16091364

PMID:27571078

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5038642/

Abstract

Surface defect detection and dimension measurement of automotive bevel gears by manual inspection are costly, inefficient, low speed and low accuracy. In order to solve these problems, a synthetic bevel gear quality inspection system based on multi-camera vision technology is developed. The system can detect surface defects and measure gear dimensions simultaneously. Three efficient algorithms named Neighborhood Average Difference (NAD), Circle Approximation Method (CAM) and Fast Rotation-Position (FRP) are proposed. The system can detect knock damage, cracks, scratches, dents, gibbosity or repeated cutting of the spline, etc. The smallest detectable defect is 0.4 mm × 0.4 mm and the precision of dimension measurement is about 40-50 μm. One inspection process takes no more than 1.3 s. Both precision and speed meet the requirements of real-time online inspection in bevel gear production.

摘要

通过人工检测汽车锥齿轮的表面缺陷和尺寸测量成本高、效率低、速度慢且精度低。为了解决这些问题，开发了一种基于多相机视觉技术的合成锥齿轮质量检测系统。该系统可以同时检测表面缺陷并测量齿轮尺寸。提出了三种高效算法，即邻域平均差（NAD）、圆逼近法（CAM）和快速旋转定位（FRP）。该系统可以检测敲击损伤、裂纹、划痕、凹痕、凸起或花键的重复切削等。最小可检测缺陷为0.4毫米×0.4毫米，尺寸测量精度约为40-50微米。一次检测过程不超过1.3秒。精度和速度均满足锥齿轮生产中实时在线检测的要求。