Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials
With the slow rise of the construction industry, cranes, as indispensable mechanical equipment in construction projects, are widely used in the lifting and handling of specific space ranges of construction projects. The quality of crane booms is particularly important for safety. This paper uses ima...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/8379621 |
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| _version_ | 1850161754529595392 |
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| author | Honghua Liu Wenping Tan Shen Cao Hongmei Li |
| author_facet | Honghua Liu Wenping Tan Shen Cao Hongmei Li |
| author_sort | Honghua Liu |
| collection | DOAJ |
| description | With the slow rise of the construction industry, cranes, as indispensable mechanical equipment in construction projects, are widely used in the lifting and handling of specific space ranges of construction projects. The quality of crane booms is particularly important for safety. This paper uses image measurement methods including filter processing, mean filtering, and Gaussian filtering to detect the quality of the crane boom material. The image is processed by the wavelet transform and Fourier transform. The grayscale transformation stretching method is applied to the surface image analysis of the boom material to obtain the final inspection. The research results show that the use of image measurement methods can effectively measure the thickness of the crane boom material, the geometric information of the boom material, and the surface roughness of the material and obtain effective image information. The detection accuracy reaches 98.1%. The error can be controlled better. The inspection and research on the quality of crane jib materials can ensure the quality and performance of crane jib materials, reduce the potential safety hazards of cranes during operation, and improve safety. This article organically combines workpiece surface roughness detection with digital image processing technology to preprocess the surface picture of the arm tube material. On this basis, the texture features in the image are extracted and programmed to calculate, and the final workpiece is obtained by the surface roughness value, which proves the feasibility of this method. The research results have very important practical significance for the detection of the quality of the arm tube material and the improvement of the quality level of the arm tube material. |
| format | Article |
| id | doaj-art-ff27f73e5d8c47bea85c0bf4ecc18b7c |
| institution | OA Journals |
| issn | 1687-8442 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-ff27f73e5d8c47bea85c0bf4ecc18b7c2025-08-20T02:22:44ZengWileyAdvances in Materials Science and Engineering1687-84422022-01-01202210.1155/2022/8379621Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom MaterialsHonghua Liu0Wenping Tan1Shen Cao2Hongmei Li3College of Information and Mechatronical EngineeringCollege of Information and Mechatronical EngineeringCollege of Information and Mechatronical EngineeringCollege of Information and Mechatronical EngineeringWith the slow rise of the construction industry, cranes, as indispensable mechanical equipment in construction projects, are widely used in the lifting and handling of specific space ranges of construction projects. The quality of crane booms is particularly important for safety. This paper uses image measurement methods including filter processing, mean filtering, and Gaussian filtering to detect the quality of the crane boom material. The image is processed by the wavelet transform and Fourier transform. The grayscale transformation stretching method is applied to the surface image analysis of the boom material to obtain the final inspection. The research results show that the use of image measurement methods can effectively measure the thickness of the crane boom material, the geometric information of the boom material, and the surface roughness of the material and obtain effective image information. The detection accuracy reaches 98.1%. The error can be controlled better. The inspection and research on the quality of crane jib materials can ensure the quality and performance of crane jib materials, reduce the potential safety hazards of cranes during operation, and improve safety. This article organically combines workpiece surface roughness detection with digital image processing technology to preprocess the surface picture of the arm tube material. On this basis, the texture features in the image are extracted and programmed to calculate, and the final workpiece is obtained by the surface roughness value, which proves the feasibility of this method. The research results have very important practical significance for the detection of the quality of the arm tube material and the improvement of the quality level of the arm tube material.http://dx.doi.org/10.1155/2022/8379621 |
| spellingShingle | Honghua Liu Wenping Tan Shen Cao Hongmei Li Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials Advances in Materials Science and Engineering |
| title | Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials |
| title_full | Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials |
| title_fullStr | Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials |
| title_full_unstemmed | Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials |
| title_short | Image-Based Precision Measurement Technology for the Quality Inspection of Crane Boom Materials |
| title_sort | image based precision measurement technology for the quality inspection of crane boom materials |
| url | http://dx.doi.org/10.1155/2022/8379621 |
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