基于动态视觉传感器的铝基盘片表面缺陷检测  

Dynamic Vision Sensor Based Defect Detection for the Surface of Aluminum Disk

作　　者：马居坡 陈周熠 吴金建 MA Ju-Po;CHEN Zhou-Yi;WU Jin-Jian(School of Artificial Intelligence,Xidian University,Xi'an 710071;Pazhou Lab(Huangpu),Guangzhou 510555)

机构地区：[1]西安电子科技大学人工智能学院,西安710071 [2]琶洲实验室(黄埔),广州510555

出　　处：《自动化学报》2024年第12期2407-2419,共13页Acta Automatica Sinica

基　　金：国家重点研发计划(2023YFA1008500);陕西省自然科学基础研究计划(2024JC-YBQN-0627);中央高校基本科研业务费专项资金(XJSJ23079,ZYTS24006)资助。

摘　　要：现有视觉缺陷检测技术通常基于传统电荷耦合器件(Charge-coupled device,CCD)或互补金属氧化物半导体(Complementary metal-oxide-semiconductor,CMOS)相机进行缺陷成像和后端检测算法开发.然而,现有技术存在成像速度慢、动态范围小、背景干扰大等问题,难以实现对高反光产品表面弱小瑕疵的快速检测.针对上述挑战,创新性地提出了一套基于动态视觉传感器(Dynamic vision sensor,DVS)的缺陷检测新模式,以实现对具有高反光特性的铝基盘片表面缺陷的高效检测.DVS是一种新型的仿生视觉传感器,具有成像速度快、动态范围大、运动目标捕捉能力强等优势.首先开展了面向铝基盘片高反光表面弱小瑕疵的DVS成像实验,并分析总结了DVS缺陷成像的特性与优势.随后,构建了第一个基于DVS的缺陷检测数据集(Event-based defect detection dataset,EDD-10k),包含划痕、点痕、污渍三类常见缺陷类型.最后,针对缺陷形态多变、纹理稀疏、噪声干扰等问题,提出了一种基于时序不规则特征聚合框架的DVS缺陷检测算法(Temporal irregular feature aggregation framework for event-based defect detection,TIFF-EDD),实现对缺陷目标的有效检测.Current visual defect detection technologies usually rely on conventional charge-coupled device(CCD) or complementary metal-oxide-semiconductor(CMOS) cameras for defect imaging and the development of backend detection algorithms.However,these technologies encounter challenges such as slow imaging speed,limited dynamic range,and significant background interference,which hinder the rapid detection of minor defects on highly reflective product surfaces.To address these challenges,we innovatively propose a new defect detection mode based on dynamic vision sensor(DVS) to achieve efficient defect detection on the highly reflective surfaces of aluminum disks.DVS is a novel bio-inspired visual sensor with advantages such as fast imaging speed,high dynamic range,and excellent ability to capture moving objects.First,we conduct DVS imaging experiments for minor defects on the highly reflective surfaces of aluminum disk and analyze the characteristics and advantages of DVS on defect imaging.Then,we establish the first event-based defect detection dataset(EDD-10k) based on DVS,including three common defect types:Scratch,point and stain.Finally,to address the issues such as varying defect shapes,sparse textures,and noise interference,we propose a temporal irregular feature aggregation framework for event-based defect detection(TIFF-EDD),and realize the effective detection of defect targets.

关 键 词：缺陷检测 动态视觉传感器 高反光表面 不规则特征提取 时序融合 事件相机 

分 类 号：TG115[金属学及工艺—物理冶金] TP391.41[金属学及工艺—金属学] TP212[自动化与计算机技术—计算机应用技术]