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基于3D點(diǎn)云數(shù)據(jù)的產(chǎn)品缺陷檢測(cè)研究

來源：電工電氣發(fā)布時(shí)間：2023-02-06 14:06 瀏覽次數(shù)：1156

基于3D點(diǎn)云數(shù)據(jù)的產(chǎn)品缺陷檢測(cè)研究

李潮林¹，陳仲生^1,2，左旺¹，侯幸林²

(1 湖南工業(yè)大學(xué) 電氣與信息工程學(xué)院，湖南株洲 412007；

2 常州工學(xué)院汽車工程學(xué)院，江蘇常州 213032)

摘要：傳統(tǒng) 2D 視覺檢測(cè)技術(shù)存在效率低下、檢測(cè)精確度較低等不足，3D 視覺技術(shù)因能顯著提高缺陷檢測(cè)的效率和可靠性得到了高度關(guān)注和廣泛研究。對(duì)已有文獻(xiàn)進(jìn)行了廣泛調(diào)研分析，介紹了 3D 點(diǎn)云數(shù)據(jù)的基本概念、獲取方式及其預(yù)處理方法，重點(diǎn)歸納了傳統(tǒng)點(diǎn)云數(shù)據(jù)缺陷檢測(cè)方法和點(diǎn)云數(shù)據(jù)深度學(xué)習(xí)缺陷檢測(cè)方法，并探討了當(dāng)前研究中存在的問題與挑戰(zhàn)。

關(guān)鍵詞： 3D 視覺；缺陷檢測(cè)；點(diǎn)云數(shù)據(jù)

中圖分類號(hào)：TP391.41 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1007-3175(2023)01-0048-07

Research on Product Defect Detection Based on 3D Point Cloud Data

LI Chao-lin¹, CHEN Zhong-sheng^1,2, ZUO Wang¹, HOU Xing-lin²

（1 School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China;

2 School of Automotive Engineering, Changzhou Institute of Technology, Changzhou 213032, China）

Abstract: The traditional 2D vision detection technology has disadvantages of low efficiency and detection accuracy, while 3D vision technology can significantly improve its detection efficiency and reliability, so it has been paid high attention and widely analyzed. After making extensive analysis of the existing literature, the paper introduces the basic concept, access and pretreatment method of 3D point cloud data, summarizes the traditional point cloud data defect detection method and point cloud data deep learning defect detection method, and finally discusses the problems and challenges of the current research.

Key words: 3D vision; defect detection; point cloud data

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基于3D點(diǎn)云數(shù)據(jù)的產(chǎn)品缺陷檢測(cè)研究