基于机器视觉的轮对磁粉探伤裂纹检测方法研究
Research on crack detection method of magnetic particle detection based on machine vision
乔辉 1曾勇 1刘德志 2杨冲 1徐仟祥 1姚苏恒1
作者信息
- 1. 盐城工学院,盐城 224007
- 2. 捷航设备制造股份有限公司,盐城 224053
- 折叠
摘要
为实现火车轮对荧光磁粉探伤裂纹的自动检测,提出一种基于机器视觉的裂纹识别和测量算法.基于工业相机分区采集的轮对荧光磁粉探伤图像,首先通过G通道分离处理、G通道阈值处理和高斯滤波处理等操作,降低图像噪点,提高裂纹特征对比度;然后在图像二值化和形态学处理初步提取目标区域的基础上,提出基于连通域的裂纹特征分割算法,进一步精确提取裂纹目标,并根据连通域信息完成裂纹分类和识别;最后,采用裂纹分割图像骨架细化拟合曲线的方法进行裂纹长度测量.实验表明,提出的方法可以有效精准地对轮对裂纹进行检测,查全率为98.56％,查准率为91.12％,识别速度为每幅48.5 ms.
Abstract
In order to realize the automatic crack detection of train wheel,a crack recognition and measurement algorithm based on machine vision is proposed.It reduces the image noise,improves the contrast of the image features,proposes crack feature seg-mentation algorithm,extracts the aspect ratio of the crack area,and completes the crack classification and recognition according to the connected domain information.Finally,the method is used to measure the crack length.Experiments show that the proposed method can effectively and accurately detect the cracks,with recall of 98.56％,accuracy of 91.12％and identification speed of 48.5 ms.
关键词
荧光磁粉探伤/火车轮对/连通域/裂纹检测Key words
fluorescent magnetic particle inspection/rain wheelset/connected domain/crack detection引用本文复制引用
基金项目
国家自然科学基金(51405418)
江苏省"青蓝工程"人才资助项目(2021)()
出版年
2024
国家科技期刊平台
NSTL
万方数据