Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network
Detecting distance between surfaces of transparent materials with large area and thickness has always been a difficult problem in the field of industry. In this paper, a method based on low-cost TOF continuous-wave modulation and deep convolutional neural network technology is proposed. The distance...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/8340179 |
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| _version_ | 1832560529403543552 |
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| author | Rong Zou Yu Zhang Junlan Gu Jin Chen |
| author_facet | Rong Zou Yu Zhang Junlan Gu Jin Chen |
| author_sort | Rong Zou |
| collection | DOAJ |
| description | Detecting distance between surfaces of transparent materials with large area and thickness has always been a difficult problem in the field of industry. In this paper, a method based on low-cost TOF continuous-wave modulation and deep convolutional neural network technology is proposed. The distance detection between transparent material surfaces is converted to the problem of solving the intersection of the optical path and the transparent material’s front and rear surfaces. On this basis, the Gray code encoding and decoding operations are combined to achieve distance detection between surfaces. The problem of holes and detail loss of depth maps generated by low-resolution TOF depth sensors have been also effectively solved. The entire system is simple and can achieve thickness detection on the full surface area. Besides, it can detect large transparent materials with a thickness of over 30 mm, which far exceeds the existing optical thickness detection system for transparent materials. |
| format | Article |
| id | doaj-art-76d91fd80c6f4d6180b5e019af7b31ec |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-76d91fd80c6f4d6180b5e019af7b31ec2025-02-03T01:27:23ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422021-01-01202110.1155/2021/83401798340179Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural NetworkRong Zou0Yu Zhang1Junlan Gu2Jin Chen3School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, ChinaDetecting distance between surfaces of transparent materials with large area and thickness has always been a difficult problem in the field of industry. In this paper, a method based on low-cost TOF continuous-wave modulation and deep convolutional neural network technology is proposed. The distance detection between transparent material surfaces is converted to the problem of solving the intersection of the optical path and the transparent material’s front and rear surfaces. On this basis, the Gray code encoding and decoding operations are combined to achieve distance detection between surfaces. The problem of holes and detail loss of depth maps generated by low-resolution TOF depth sensors have been also effectively solved. The entire system is simple and can achieve thickness detection on the full surface area. Besides, it can detect large transparent materials with a thickness of over 30 mm, which far exceeds the existing optical thickness detection system for transparent materials.http://dx.doi.org/10.1155/2021/8340179 |
| spellingShingle | Rong Zou Yu Zhang Junlan Gu Jin Chen Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network Advances in Materials Science and Engineering |
| title | Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network |
| title_full | Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network |
| title_fullStr | Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network |
| title_full_unstemmed | Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network |
| title_short | Detecting Distance between Surfaces of Large Transparent Material Based on Low-Cost TOF Sensor and Deep Convolutional Neural Network |
| title_sort | detecting distance between surfaces of large transparent material based on low cost tof sensor and deep convolutional neural network |
| url | http://dx.doi.org/10.1155/2021/8340179 |
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