الگوریتم تشخیص ترک در پل بتنی
ترجمه نشده

الگوریتم تشخیص ترک در پل بتنی

عنوان فارسی مقاله: تحقیق در مورد الگوریتم تشخیص ترک در پل بتنی بر اساس پردازش تصویر
عنوان انگلیسی مقاله: Research on Crack Detection Algorithm of the Concrete Bridge Based on Image Processing
مجله/کنفرانس: علوم کامپیوتر پروسیدیا – Procedia Computer Science
رشته های تحصیلی مرتبط: مهندسی کامپیوتر
گرایش های تحصیلی مرتبط: الگوریتم و محاسبات
کلمات کلیدی فارسی: پل بتنی، تشخیص ترک، پردازش تصویر، بهبود الگوریتم
کلمات کلیدی انگلیسی: Concrete bridge, Crack detection, Image processing, Algorithm improvement
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.procs.2019.06.096
دانشگاه: School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou and 310018,China
صفحات مقاله انگلیسی: 7
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 1.257 در سال 2018
شاخص H_index: 47 در سال 2019
شاخص SJR: 0.281 در سال 2018
شناسه ISSN: 1877-0509
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E12357
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1-Introduction

2-Image Preprocessing of Concrete bridge Crack

3-The Edge Detection of Concrete Bridge Crack

4-Feature Data Extraction of Concrete Bridge Crack

5-Case analysis

6-Conclusion

Acknowledgements

Reference

بخشی از مقاله (انگلیسی)

Abstract

The appearance and development of cracks in the concrete bridge will seriously affect the safe use of bridge buildings. In order to better satisfy the crack detection requirement, this paper comes up with an image preprocessing scheme combining multiple adaptive filtering and contrast enhancement based on the image processing technology of concrete crack, which can improve the removal effect of background noise and obtain the characteristic vein information of tiny cracks. Then we designed a local adaptive algorithm of Otsu threshold segmentation and integrated with modified Sobel operator for removing isolated noise spots, so as to extract the crack edge information and improve the positioning accuracy of the crack boundary. Furthermore, according to the image feature of the bridge crack edge, the target crack is identified as well as classified and the feature data is calculated. The results of case analysis show that the data processing precision of the detection algorithm can reach 0.02mm, which can satisfy the actual engineering detection requirements of concrete bridge crack.

Introduction

In order to ensure the safe operation of a reinforced concrete bridge, it needs regular detection and timely maintenance, which concrete crack detection is one of the important items of bridge detection. And the digital image processing has become an important technology of concrete bridge detection, scholars have done a lot of research about the crack image detection technology, such as Yao et al. [1] design a climbing robot for bridge crack detection, as well as realize the identification and classification of the crack image. But the detection precision of the video image is not enough, and the application cannot be popularized in engineering practice. And for improving the transmission quality of image data, the terrestrial laser scanning (TLS)[2] technology processes and evaluates the crack images obtained by laser scanning. Liu et al. [3] optimized the robust processing effect of the crack image by using the method based on multi-scale morphological enhancement and crack characteristics on the concrete surface, but the image edge after morphological processing was prone to distortion.