液晶与显示, 2017, 32 (11): 895, 网络出版: 2017-12-01   

基于菌群算法的飞机铆钉表面缺陷检测系统光源优化控制

Bacterial foraging optimization control of light source for surface defect detection system based on colony algorithm
作者单位
陕西科技大学 电气与信息工程学院, 陕西 西安 710021
摘要
由于飞机铆钉缺陷检测系统的光照效果对缺陷检测质量发挥着关键作用, 因此本文对其照明系统进行优化。以被测零件背景图像灰度的均匀度为优化目标, 在拟合LED点光源照度分布函数的基础上, 利用菌群算法对光源系统参数进行寻优运算, 根据寻优结果对光源系统进行结构优化同时对各LED点光源进行功率控制, 并通过光学元件进一步提高优化效果。实验结果表明: 优化后光照均匀度在95%以上, 满足铆钉检测的光照要求。该方法实现了照明系统对铆钉顶圆面均匀照射的效果, 成像质量显著提高。
Abstract
As the lighting effects of aircraft rivets defect detection system play a key role on the defect detection quality, this paper optimized its lighting system.Based on the distribution function of fitting LED point light source illumination,taking the uniformity of background image grayscale of the measured part as optimization goal,the bacterial population algorithm is used to optimize the light source system parameters. According to the optimization results, the structure optimization of the light source system is carried out. The power control of each LED point light source is carried out, and the optimization effect is further improved through the optical component. The experimental results show that the optimal light uniformity is more than 95%, to meet the lighting requirements of rivet detection . This method realizes the effect of illumination system on the top surface of rivet, and the image quality is improved obviously.

周强, 王峥, 李敏. 基于菌群算法的飞机铆钉表面缺陷检测系统光源优化控制[J]. 液晶与显示, 2017, 32(11): 895. ZHOU Qiang, WANG Zheng, LI Min. Bacterial foraging optimization control of light source for surface defect detection system based on colony algorithm[J]. Chinese Journal of Liquid Crystals and Displays, 2017, 32(11): 895.

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