The reconstruction and defects detection of fiber pack

•High resolution industrial X-ray computerized tomography was used for image acquisition.•According to the characteristics of the image, a series of image processing methods are used to optimize it.•The internal winding structure of the whole guidance fiber pack is reconstructed accurately.•Analyzin...

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Bibliographic Details
Published in:Optics and lasers in engineering Vol. 185; p. 108719
Main Authors: Shi, Tengyin, Zhang, Zhuo, Xue, Yaohui, Lv, Jingze, Zhang, Yiqun
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.02.2025
Subjects:
Computed tomography
Geometric modeling
Image processing
Missile guidance
Nondestructive testing
Missile guidance
Computed tomography
Image processing
Nondestructive testing
Geometric modeling
ISSN:0143-8166
Online Access:Get full text
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Summary:•High resolution industrial X-ray computerized tomography was used for image acquisition.•According to the characteristics of the image, a series of image processing methods are used to optimize it.•The internal winding structure of the whole guidance fiber pack is reconstructed accurately.•Analyzing the geometric features and formation mechanism of the fiber pack defects.•Automatic identification and detection of fiber pack defects. Fiber optic guidance technology is a crucial approach for weapon teleoperation. However, the reliable release of ultra-long-distance guidance fiber through tight winding has always posed a technical challenge that hinders its development. The winding and forming process of the guidance fiber pack often leads to various structural defects, significantly compromising its release reliability. Therefore, it is imperative to address geometric reconstruction and defect detection within the internal structure of formed fiber packs. In this study, an innovative approach is proposed utilizing industrial computerized tomography (CT) technology for precise geometric reconstruction and nondestructive defect detection in guidance fiber packs. The method initially acquires visualization data of the fiber pack through industrial CT scanning, followed by precise extraction of the fiber's cross-section centroid using image digitization techniques. Subsequently, an innovative algorithm based on centroid distance is developed for point determination, enabling the identification and connection of correlated centroid points to construct a geometric reconstruction model of the actual internal structure of the fiber pack for the first time. Finally, the geometric features of various typical structural defects are defined, and based on these features, the detection, identification, and location of the defects of the fiber pack structure are realized. Experimental results demonstrate that this method exhibits high accuracy and sensitivity, providing robust support for further advancements in fiber optic guidance technology.
ISSN:0143-8166
DOI:10.1016/j.optlaseng.2024.108719