Smartphone-based high durable strain sensor with sub-pixel-level accuracy and adjustable camera position

IF 8.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-11-19 DOI:10.1111/mice.13383

Pengfei Wu, Bo Lu, Huan Li, Weijie Li, Xuefeng Zhao

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Abstract

Computer vision strain sensors typically require the camera position to be fixed, limiting measurements to surface deformations of structures at pixel-level resolution. Also, sensors have a service term significantly shorter than the designed service term of the structures. This paper presents research on a high durable computer vision sensor, microimage strain sensing (MISS)-Silica, which utilizes a smartphone connected to an endoscope for measurement. It is designed with a range of 0.05 ε, enabling full-stage strain measurement from loading to failure of structures. The sensor does not require the camera to be fixed during measurements, laying the theoretical foundation for embedded computer vision sensors. Measurement accuracy is improved from pixel level to sub-pixel level, with pixel-based measurement errors around 8 µε (standard deviation approximately 7 µε) and sub-pixel calculation errors around 6 µε (standard deviation approximately 5 µε). Sub-pixel calculation has approximately 30% enhancement in measurement accuracy and stability. MISS-Silica features easy data acquisition, high precision, and long service term, offering a promising method for long-term measurement of both surface and internal structures.

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基于智能手机的高耐用应变传感器，精度达到亚像素级，摄像头位置可调

计算机视觉应变传感器通常要求相机位置固定，这就限制了以像素级分辨率对结构表面变形的测量。此外，传感器的使用期限远远短于结构的设计使用期限。本文介绍了对高耐用计算机视觉传感器--微图像应变传感（MISS）--二氧化硅的研究，该传感器利用连接到内窥镜的智能手机进行测量。该传感器的量程为 0.05 ε，可对结构进行从加载到失效的全阶段应变测量。该传感器在测量过程中无需固定摄像头，为嵌入式计算机视觉传感器奠定了理论基础。测量精度从像素级提高到子像素级，基于像素的测量误差约为 8 µε（标准偏差约为 7 µε），子像素计算误差约为 6 µε（标准偏差约为 5 µε）。亚像素计算的测量精度和稳定性提高了约 30%。MISS-Silica 具有数据采集简单、精度高、使用寿命长等特点，为表面和内部结构的长期测量提供了一种可行的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer-Aided Civil and Infrastructure Engineering 工程技术-工程：土木

CiteScore

17.60

自引率

19.80%

发文量

146

审稿时长

1 months

期刊介绍： Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.