基于机器视觉的发动机气缸壁珩磨角测量方法  

Crosshatch-angles detection of cylinder bore based on machine vision

作　　者：张农 黄凯 罗亮 郎霄 郑敏毅 Zhang Nong;Huang Kai;Luo Liang;Lang Xiao;Zheng Minyi(School of Automotive and Traffic Engineering,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]合肥工业大学汽车与交通工程学院,安徽合肥230009

出　　处：《电子测量技术》2022年第16期123-129,共7页Electronic Measurement Technology

摘　　要：针对实际工业检测中发动机气缸壁珩磨角人工测量存在效率低、精度低等问题,提出了一种基于机器视觉的发动机气缸壁珩磨角测量方法。首先利用Gabor最优滤波通道算法处理样本图像获得线性特征增强后的网纹图像,再对网纹图像进行DFT转化获取傅里叶频谱图像,然后基于数字微分分析算法获取频谱图像中的峰值直线并计算两条峰值直线的夹角作为计算结果,同时与基于Camera Measure测绘软件手动测量结果进行对比。通过实现测试结果表明:该方法相对于手动测量结果的误差仅为0.33%,重复测量的均值差为±1°以内;在检测时间上,检测一个工件的平均时间为0.53 s。该测量方法测量精度高、测量速度快等优势,可以有效地取代工业检测中的人工测量。Aiming at the problems of low efficiency and low precision in manual measurement of honing Angle of engine cylinder wall in practical industrial testing,a measuring method based on machine vision was proposed.Firstly,Gabor optimal filter channel algorithm is used to process the sample image to obtain the enhanced linear feature pattern image.Then,DFT transformation is performed on the pattern image to obtain the Fourier spectrum image.Then,the peak lines in the spectrum image are obtained based on the digital differential analysis algorithm and the included Angle of the two peak lines is calculated as the calculation result.Meanwhile,the results were compared with the manual measurement results based on Camera Measure software.The test results show that the error of this method is only 0.33%compared with manual measurement,and the mean difference of repeated measurement is within±1°.In terms of detection time,the average detection time of a workpiece is 0.53 s.This method has the advantages of high precision and fast speed,which can effectively replace manual measurement in industrial testing.

关 键 词：气缸套珩磨网纹 珩磨角 GABOR滤波 数字微分分析算法(DDA) 机器视觉 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]