Defect detection of wire rope for oil well based on adaptive angle
This paper uses a digital image processing method which is based on texture feature of steel cable to detect the fracture of steel wire. At first, it uses a modified homomorphic filtering method to eliminate environment heterogeneous shining. Next, it obtains the body image of the steel line by usin...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Gruppo Italiano Frattura
2015-09-01
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| Series: | Fracture and Structural Integrity |
| Subjects: | |
| Online Access: | https://www.fracturae.com/index.php/fis/article/view/1617 |
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| _version_ | 1841562321183309824 |
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| author | Zhang Jijun Meng Xiangqing |
| author_facet | Zhang Jijun Meng Xiangqing |
| author_sort | Zhang Jijun |
| collection | DOAJ |
| description | This paper uses a digital image processing method which is based on texture feature of steel cable to detect the fracture of steel wire. At first, it uses a modified homomorphic filtering method to eliminate environment heterogeneous shining. Next, it obtains the body image of the steel line by using the method of edge detecting and section counting filtering to detect the bunch part of steel wire. By using an improved Radon transformation method to indicate if those steel wire are in good condition or not. Finally, by using BP neural network model it aims to judge the final result. Test result shows that this method is easy to use and fulfill real time request. |
| format | Article |
| id | doaj-art-7b0e4a2cada24749a7c161351f1e4488 |
| institution | Kabale University |
| issn | 1971-8993 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | Gruppo Italiano Frattura |
| record_format | Article |
| series | Fracture and Structural Integrity |
| spelling | doaj-art-7b0e4a2cada24749a7c161351f1e44882025-01-03T01:03:09ZengGruppo Italiano FratturaFracture and Structural Integrity1971-89932015-09-01934Defect detection of wire rope for oil well based on adaptive angleZhang JijunMeng XiangqingThis paper uses a digital image processing method which is based on texture feature of steel cable to detect the fracture of steel wire. At first, it uses a modified homomorphic filtering method to eliminate environment heterogeneous shining. Next, it obtains the body image of the steel line by using the method of edge detecting and section counting filtering to detect the bunch part of steel wire. By using an improved Radon transformation method to indicate if those steel wire are in good condition or not. Finally, by using BP neural network model it aims to judge the final result. Test result shows that this method is easy to use and fulfill real time request.https://www.fracturae.com/index.php/fis/article/view/1617BP neural network |
| spellingShingle | Zhang Jijun Meng Xiangqing Defect detection of wire rope for oil well based on adaptive angle Fracture and Structural Integrity BP neural network |
| title | Defect detection of wire rope for oil well based on adaptive angle |
| title_full | Defect detection of wire rope for oil well based on adaptive angle |
| title_fullStr | Defect detection of wire rope for oil well based on adaptive angle |
| title_full_unstemmed | Defect detection of wire rope for oil well based on adaptive angle |
| title_short | Defect detection of wire rope for oil well based on adaptive angle |
| title_sort | defect detection of wire rope for oil well based on adaptive angle |
| topic | BP neural network |
| url | https://www.fracturae.com/index.php/fis/article/view/1617 |
| work_keys_str_mv | AT zhangjijun defectdetectionofwireropeforoilwellbasedonadaptiveangle AT mengxiangqing defectdetectionofwireropeforoilwellbasedonadaptiveangle |