Surface Defects Detection Based on Adaptive Multiscale Image Collection and Convolutional Neural Networks
文献类型：期刊论文
| 作者 | Sun, Jia ; Wang, Peng; Luo, Yong-Kang; Li, Wanyi
|
| 刊名 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
 |
| 出版日期 | 2019-12-01 |
| 卷号 | 68期号:12页码:4787-4797 |
| ISSN号 | 0018-9456 |
| 关键词 | Inspection Surface treatment Training Metals Task analysis Instruments Visualization Adaptive multiscale image collection (AMIC) convolutional neural networks (CNNs) image classification surface inspection |
| DOI | 10.1109/TIM.2019.2899478 |
| 通讯作者 | Wang, Peng(peng_wang@ia.ac.cn) |
| 英文摘要 | Surface flaw inspection is of great importance for quality control in the field of manufacture. In this paper, a novel surface flaw inspection algorithm is proposed based on adaptive multiscale image collection (AMIC) using convolutional neural networks. First, the inspection networks are pretrained with ImageNet data set. Second, the AMIC is established, which consists of adaptive multiscale image extraction and with-contour local extraction from training images. Through the AMIC, the training data set is greatly augmented, and labels of images can be accomplished automatically without artificial consumption. Then, transfer learning is performed with the AMIC established from training data set. Finally, an automatic surface flaw inspection instrument for large-volume metal components embedded with the proposed inspection algorithm is designed. Experiments with small metal components are performed to analyze the influence of parameters, and comparative experiments are carried out. The inspecting precisions for indentation, scratch, and pitted surface of the proposed method are 97.3, 99.5, and 100, respectively. The experimental results demonstrate the effectiveness of the proposed method in the detection of various surface flaws. |
| WOS关键词 | ARCHITECTURES ; INSPECTION |
| 资助项目 | National Natural Science Foundation of China[91748131] ; National Natural Science Foundation of China[61379097] ; National Natural Science Foundation of China[61771471] ; National Natural Science Foundation of China[U1613213] ; China Postdoctoral Science Foundation[2018M641523] ; National Key Research and Development Plan of China[2017YFB1300202] ; Youth Innovation Promotion Association Chinese Academy of Sciences[2015112] |
| WOS研究方向 | Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000497484000020 |
| 资助机构 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; National Key Research and Development Plan of China ; Youth Innovation Promotion Association Chinese Academy of Sciences |
| 源URL | [http://ir.ia.ac.cn/handle/173211/29371]  |
| 专题 | 智能机器人系统研究 |
| 通讯作者 | Wang, Peng |
| 作者单位 | Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sun, Jia,Wang, Peng,Luo, Yong-Kang,et al. Surface Defects Detection Based on Adaptive Multiscale Image Collection and Convolutional Neural Networks[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2019,68(12):4787-4797. |
| APA | Sun, Jia,Wang, Peng,Luo, Yong-Kang,&Li, Wanyi.(2019).Surface Defects Detection Based on Adaptive Multiscale Image Collection and Convolutional Neural Networks.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,68(12),4787-4797. |
| MLA | Sun, Jia,et al."Surface Defects Detection Based on Adaptive Multiscale Image Collection and Convolutional Neural Networks".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 68.12(2019):4787-4797. |
入库方式： OAI收割
来源：自动化研究所
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