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

周强; 王峥; 李敏

doi:10.3788/YJYXS20173211.0895

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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

驱动与系统 | 更新时间：2020-08-12

- 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
- 液晶与显示 2017年32卷第11期页码：895-904
- 作者机构：
  
  陕西科技大学电气与信息工程学院, 陕西西安 710021
- 作者简介：
  
  [ "周强(1969-), 男, 重庆人, 教授, 研究生导师, 1993年于西北轻工业学院获得学士学位, 2001年于西北轻工业学院获得硕士学位, 2010年于西安交通大学获得博士学位, 主要研究方向为非平稳随机信号分析、图像处理技术。E-mail:zhouqiang@sust.edu.cn" ]
  [ "王峥(1992-), 女, 陕西宝鸡人, 硕士研究生, 2011年于陕西科技大学获得学士学位, 2011年就读于于陕西科技大学, 攻读硕士学位, 主要从事机器视觉及自动控制方面的研究。E-mail:295252145@qq.com.cn" ]
- 基金信息：
  
  陕西省教育厅专项科技项目(16JK1105);陕西省科技攻关项目(2016GY-005);Special Science and Technology Project of Shaanxi Provincial Department of Education(16JK1105);Shaanxi Science and Technology project(2016GY-005)
- DOI：10.3788/YJYXS20173211.0895
  中图分类号： TB811.1
- 收稿日期：2017-04-07，
  
  录用日期：2017-7-10，
  
  纸质出版日期：2017-11-05
- 稿件说明：
移动端阅览
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):895-904.

Qiang ZHOU, Zheng WANG, Min LI. 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): 895-904.
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):895-904. DOI： 10.3788/YJYXS20173211.0895.

Qiang ZHOU, Zheng WANG, Min LI. 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): 895-904. DOI： 10.3788/YJYXS20173211.0895.

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.

关键词

Keywords

references

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