基于机器视觉的运载火箭舱体铆接质量在线检测方法  

Method of Launch Vehicle Capsule Automatic Riveting Quality Online Detection Based on Machine Vision

作　　者：袁桢棣 徐兴中[1] 盛王鼎 成群林[1] YUAN Zhendi;XU Xingzhong;SHENG Wangding;CHENG Qunlin(Shanghai Spaceflight Precision Machinery Institute,Shanghai 201600,China)

机构地区：[1]上海航天精密机械研究所,上海201600

出　　处：《上海航天(中英文)》2025年第1期141-148,共8页Aerospace Shanghai(Chinese&English)

基　　金：上海市自然科学基资助金项目(21ZR1427600)。

摘　　要：针对运载火箭舱体自动铆接质量依靠人工目视、卡尺测量等检验方法存在检验效率低、工作强度大、错检漏检率高的突出问题,本文提出基于机器视觉系统的铆接质量在线检测方法,在舱体进行自动钻铆加工的同时实现对铆接质量的高效高质量检测。建立了铆钉数字图像到物理空间映射关系,通过基于透视变换的角度矫正算法获得高质量的铆钉镦头图像,利用镦头边缘及表面图像获得镦头关键尺寸与表面缺陷信息,实现铆接质量判定。工艺试验结果表明:该方法的平均检测速度达0.92 s/钉,可与铆接过程同步完成,大幅提升了铆接质量的检测质量和检测效率,对不合格铆钉的检出率为100%,检测准确率为99.8%,显著降低了错检漏检率。In view of the problems of low detection efficiency,high work intensity,and high error detection rate in the detection methods,e.g.,artificial visual vision and stalk measurement,for the automatic riveting quality detection of launch vehicle capsules,an online detection method for the automatic riveting quality of launch vehicle capsules based on the machine visual system is proposed.With the method,launch vehicle capsules can be detected with high efficiency and high quality while being automatically drilled and riveted.The mapping relationship of a rivet digital image to the physical space is established,and high-quality rivet pier head images are obtained by the angle correction algorithm based on the perspective transformation.The pier head edges and surface images are used to obtain the key size parameters and surface defect information of the pier head,and then the riveting quality is determined.The results of the process test show that the average detection speed of this method is up to 0.92 s/rivet,which can be completed synchronously with the riveting process,and greatly improves the efficiency of riveting quality detection.The detection rate of unqualified rivets is 100%,and the detection accuracy is 99.8%,which significantly reduces the false detection and missed detection rate.

关 键 词：铆接质量 机器视觉 系统标定 缺陷判别 在线检测 

分 类 号：TG453.9[金属学及工艺—焊接]