Near-field microwave imaging and quantitative characterization of defects in PE pipeline
In order to effectively detect internal defects in polyethylene (PE) pipeline, microwave non-destructive testing technology was used to detect and quantify defects in PE pipelines.A clutter suppression imaging enhancement method based on principal component analysis (PCA) was proposed for extracting...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2023-09-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023180/ |
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| _version_ | 1841539187069681664 |
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| author | Mingshi LUO Mengmeng ZHANG Yang FANG |
| author_facet | Mingshi LUO Mengmeng ZHANG Yang FANG |
| author_sort | Mingshi LUO |
| collection | DOAJ |
| description | In order to effectively detect internal defects in polyethylene (PE) pipeline, microwave non-destructive testing technology was used to detect and quantify defects in PE pipelines.A clutter suppression imaging enhancement method based on principal component analysis (PCA) was proposed for extracting defect images from PE pipelines.Threshold segmentation techniques were used to extract defect features from the enhanced images.Experimental results demonstrate that the proposed method can effectively image PE pipelines and highlight defects.The imaging quality is superior to that of images without clutter suppression.Compared to theoretical values, the average relative error in defect localization is 2.38 mm, and the relative error in area quantification is 13.25%. |
| format | Article |
| id | doaj-art-45e46bb13cc340d9964e665e58f02b26 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2023-09-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-45e46bb13cc340d9964e665e58f02b262025-01-14T07:23:33ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2023-09-014413914859836070Near-field microwave imaging and quantitative characterization of defects in PE pipelineMingshi LUOMengmeng ZHANGYang FANGIn order to effectively detect internal defects in polyethylene (PE) pipeline, microwave non-destructive testing technology was used to detect and quantify defects in PE pipelines.A clutter suppression imaging enhancement method based on principal component analysis (PCA) was proposed for extracting defect images from PE pipelines.Threshold segmentation techniques were used to extract defect features from the enhanced images.Experimental results demonstrate that the proposed method can effectively image PE pipelines and highlight defects.The imaging quality is superior to that of images without clutter suppression.Compared to theoretical values, the average relative error in defect localization is 2.38 mm, and the relative error in area quantification is 13.25%.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023180/polyethylene pipelinenon-destructive testingmicrowave imagingdefect characterization |
| spellingShingle | Mingshi LUO Mengmeng ZHANG Yang FANG Near-field microwave imaging and quantitative characterization of defects in PE pipeline Tongxin xuebao polyethylene pipeline non-destructive testing microwave imaging defect characterization |
| title | Near-field microwave imaging and quantitative characterization of defects in PE pipeline |
| title_full | Near-field microwave imaging and quantitative characterization of defects in PE pipeline |
| title_fullStr | Near-field microwave imaging and quantitative characterization of defects in PE pipeline |
| title_full_unstemmed | Near-field microwave imaging and quantitative characterization of defects in PE pipeline |
| title_short | Near-field microwave imaging and quantitative characterization of defects in PE pipeline |
| title_sort | near field microwave imaging and quantitative characterization of defects in pe pipeline |
| topic | polyethylene pipeline non-destructive testing microwave imaging defect characterization |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023180/ |
| work_keys_str_mv | AT mingshiluo nearfieldmicrowaveimagingandquantitativecharacterizationofdefectsinpepipeline AT mengmengzhang nearfieldmicrowaveimagingandquantitativecharacterizationofdefectsinpepipeline AT yangfang nearfieldmicrowaveimagingandquantitativecharacterizationofdefectsinpepipeline |