Displacement sensing based on microscopic vision with high resolution and large measuring range

IF 8.5 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-05-07 DOI:10.1111/mice.13227
Pengfei Wu, Weijie Li, Xuefeng Zhao
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Abstract

Microimage strain sensing (MISS) is a novel piston-type sensor based on microscopic vision. In this study, optical disc slice is used as information carriers to improve MISS. There are multiple pits on the surface of an optical disc. By using machine vision algorithms, the pits can be converted into digital information, making them scales for recording displacements. By this means, we proposed a sensing method that combines high resolution, wide range, and strong robustness. The study measured displacement under different conditions. To address inevitable factors such as pixel drift, and manufacturing errors, corresponding compensation methods were provided. The results show that the measurements closely match those of the linear variable differential transformer, with a resolution of up to 20 nm and a range approaching the sensor size. Despite the sensor's dependence on machine vision, it demonstrates strong resistance to environmental factors such as brightness and angle. Combining compensation methods for pixel drift, and manufacturing errors, this sensor can be well-applied in various working conditions.
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基于显微视觉的位移传感,分辨率高,测量范围大
微图像应变传感(MISS)是一种基于微观视觉的新型活塞式传感器。本研究利用光盘切片作为信息载体来改进 MISS。光盘表面有多个凹坑。通过使用机器视觉算法,可以将凹坑转化为数字信息,使其成为记录位移的标尺。通过这种方法,我们提出了一种集高分辨率、宽范围和强鲁棒性于一体的传感方法。研究测量了不同条件下的位移。针对像素漂移和制造误差等不可避免的因素,提供了相应的补偿方法。结果表明,测量结果与线性可变差动变压器的测量结果非常接近,分辨率高达 20 nm,量程接近传感器尺寸。尽管传感器依赖于机器视觉,但它对亮度和角度等环境因素具有很强的抵抗力。结合对像素漂移和制造误差的补偿方法,该传感器可以很好地应用于各种工作条件。
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来源期刊
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.
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