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Research on automatic inspection system for defects on precise optical surface based on machine vision 被引量:1
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作者 王雪 《Journal of Chongqing University》 CAS 2006年第2期89-93,共5页
In manufacture of precise optical products, it is important to inspect and classify the potential defects existing on the products’ surfaces after precise machining in order to obtain high quality in both functionali... In manufacture of precise optical products, it is important to inspect and classify the potential defects existing on the products’ surfaces after precise machining in order to obtain high quality in both functionality and aesthetics. The existing methods for detecting and classifying defects all are low accuracy or efficiency or high cost in inspection process. In this paper, a new inspection system based on machine vision has been introduced, which uses automatic focusing and image mosaic technologies to rapidly acquire distinct surface image, and employs Case-Based Reasoning(CBR)method in defects classification. A modificatory fuzzy similarity algorithm in CBR has been adopted for more quick and robust need of pattern recognition in practice inspection. Experiments show that the system can inspect surface diameter of 500mm in half an hour with resolving power of 0.8μm diameter according to digs or 0.5μm transverse width according to scratches. The proposed inspection principles and methods not only have meet manufacturing requirements of precise optical products, but also have great potential applications in other fields of precise surface inspection. 展开更多
关键词 optical surface defect inspection machine vision CBR
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Rail fastener defect inspection method for multi railways based on machine vision 被引量:2
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作者 Junbo Liu YaPing Huang +3 位作者 ShengChun Wang XinXin Zhao Qi Zou XingYuan Zhang 《Railway Sciences》 2022年第2期210-223,共14页
Purpose–This research aims to improve the performance of rail fastener defect inspection method for multi railways,to effectively ensure the safety of railway operation.Design/methodology/approach–Firstly,a fastener... Purpose–This research aims to improve the performance of rail fastener defect inspection method for multi railways,to effectively ensure the safety of railway operation.Design/methodology/approach–Firstly,a fastener region location method based on online learning strategy was proposed,which can locate fastener regions according to the prior knowledge of track image and template matching method.Online learning strategy is used to update the template library dynamically,so that the method not only can locate fastener regions in the track images of multi railways,but also can automatically collect and annotate fastener samples.Secondly,a fastener defect recognition method based on deep convolutional neural network was proposed.The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region.The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.Findings–Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways.Specifically,fastener location module has achieved an average detection rate of 99.36%,and fastener defect recognition module has achieved an average precision of 96.82%.Originality/value–The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways,which has high reliability and strong adaptability to multi railways. 展开更多
关键词 Rail fastener Defects inspection Multi railways Image recognition Deep convolutional neural network machine vision
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RULE-BASED FABRIC INSPECTION USING MACHINE VISION
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作者 李允明 兰东 《Journal of China Textile University(English Edition)》 EI CAS 1993年第3期28-41,共14页
Automatic visual inspection of fabric is not only one of the potential application of machinevision but a considerable challenge in textile engineering as well.This paper mainly discusses howto inspect fabric defects ... Automatic visual inspection of fabric is not only one of the potential application of machinevision but a considerable challenge in textile engineering as well.This paper mainly discusses howto inspect fabric defects using machine vision.The introduced inspection system has a feature of:(?)Categorizing the fabric defects into 4 groups,for each group diffcrent image processing and recog-nizing methods are designed for fast and efficient inspection:2.The inspection and recognitionparameters are determined by training and self learning,these parameters vary with different kindsof fabric;3.Human inspetor’s experiences are summed up as rules to ensure the system has a s(?)lar evaluation performance of human inspector.This system can detect most of the fab(?) defects.the total recognition error is less than 5% except for the detection error of yarn irregularity,whichcould be as high as 20%. 展开更多
关键词 COMPUTER vision automatic inspection FABRIC inspection machine vision.
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Backlit Keyboard Inspection Using Machine Vision
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作者 Der-Baau Perng Hsiao-Wei Liu Po-An Chen 《Journal of Electronic Science and Technology》 CAS CSCD 2015年第1期39-44,共6页
A robust system for backlit keyboard inspection is revealed. The backlit keyboard not only has changeable diverse colors but also has the laser marking keys. The keys on the keyboard can be divided into regions of fun... A robust system for backlit keyboard inspection is revealed. The backlit keyboard not only has changeable diverse colors but also has the laser marking keys. The keys on the keyboard can be divided into regions of function keys, normal keys, and number keys. However, there might have some types of defects: incorrect illuminating area, non-uniform illumination of specified inspection region(IR), and incorrect luminance and intensity of individual key. Since the illumination features of backlit keyboard are too complex to inspect for human inspector in the production line, an auto-mated inspection system for the backlit keyboard is proposed in this paper. The system was designed into the operation module and inspection module. A set of image processing methods were developed for these defects inspection. Some experimental results demonstrate the robustness and effectiveness of the proposed system. 展开更多
关键词 Backlit keyboard illumination defect inspection machine vision UNIFORMITY
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Development of an automatic weld surface appearance inspection system using machine vision
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作者 林三宝 伏喜斌 +2 位作者 范成磊 杨春利 罗璐 《China Welding》 EI CAS 2009年第3期74-80,共7页
In this paper, an automatic inspection system for weld surface appearance using machine vision has been developed to recognize weld surface defects such as porosities, cracks, etc. It can replace conventional manual v... In this paper, an automatic inspection system for weld surface appearance using machine vision has been developed to recognize weld surface defects such as porosities, cracks, etc. It can replace conventional manual visual inspection method, which is tedious, time-consuming, subjective, experience-depended, and sometimes biased. The system consists of a CCD camera, a self-designed annular light source, a sensor controller, a frame grabbing card, a computer and so on. After acquiring weld surface appearance images using CCD, the images are preprocessed using median filtering and a series of image enhancement algorithms. Then a dynamic threshold and morphology algorithms are applied to segment defect object. Finally, defect features information is obtained by eight neighborhoods boundary chain code algorithm. Experimental results show that the developed system is capable of inspecting most surface defects such as porosities, cracks with high reliability and accuracy. 展开更多
关键词 weld surface appearance visual inspection surface defects machine vision
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A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts
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作者 Zia Ullah Lin Qi +2 位作者 E.J.Solteiro Pires Arsénio Reis Ricardo Rodrigues Nunes 《Computers, Materials & Continua》 SCIE EI 2024年第8期2387-2421,共35页
The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity.Antenna defects,ranging from manufacturing imperfections to environmental wear... The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity.Antenna defects,ranging from manufacturing imperfections to environmental wear,pose significant challenges to the reliability and performance of communication systems.This review paper navigates the landscape of antenna defect detection,emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection.This review paper serves as a valuable resource for researchers,engineers,and practitioners engaged in the design and maintenance of communication systems.The insights presented here pave the way for enhanced reliability in antenna systems through targeted defect detection measures.In this study,a comprehensive literature analysis on computer vision algorithms that are employed in end-of-line visual inspection of antenna parts is presented.The PRISMA principles will be followed throughout the review,and its goals are to provide a summary of recent research,identify relevant computer vision techniques,and evaluate how effective these techniques are in discovering defects during inspections.It contains articles from scholarly journals as well as papers presented at conferences up until June 2023.This research utilized search phrases that were relevant,and papers were chosen based on whether or not they met certain inclusion and exclusion criteria.In this study,several different computer vision approaches,such as feature extraction and defect classification,are broken down and analyzed.Additionally,their applicability and performance are discussed.The review highlights the significance of utilizing a wide variety of datasets and measurement criteria.The findings of this study add to the existing body of knowledge and point researchers in the direction of promising new areas of investigation,such as real-time inspection systems and multispectral imaging.This review,on its whole,offers a complete study of computer vision approaches for quality control in antenna parts.It does so by providing helpful insights and drawing attention to areas that require additional exploration. 展开更多
关键词 Computer vision end-of-line visual inspection of antenna parts machine learning algorithms image processing techniques deep learning models
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A MACHINE VISION SYSTEM FOR INSPECTING WOOD SURFACE DEFECTS BY USING NEURAL NETWORK
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作者 王克奇 白景峰 《Journal of Northeast Forestry University》 SCIE CAS CSCD 1996年第2期63-65,共3页
With the development of wood industry, the processing of wood products becomemore significant. This paper discusses the developmen of machine vision system used to inspect andclassny the various types of defects of wo... With the development of wood industry, the processing of wood products becomemore significant. This paper discusses the developmen of machine vision system used to inspect andclassny the various types of defects of wood suxface. The surface defeds means the variations ofcolour and textUre. The machine vision system is to dated undesirable 'defecs' that can appear onthe surface of rough wood lwnber. A neural network was used within the Blackboard framework fora labeling verification step of the high-level recognition module of vision system. The system hasbere successfully tested on a number of boards from several different species. 展开更多
关键词 Neural network machine vision Defects inspection
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Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring 被引量:69
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作者 Billie F. Spencer Jr. Vedhus Hoskere Yasutaka Narazaki 《Engineering》 SCIE EI 2019年第2期199-222,共24页
Computer vision techniques, in conjunction with acquisition through remote cameras and unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure condition assessment. The ultimate ... Computer vision techniques, in conjunction with acquisition through remote cameras and unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure condition assessment. The ultimate goal of such a system is to automatically and robustly convert the image or video data into actionable information. This paper provides an overview of recent advances in computer vision techniques as they apply to the problem of civil infrastructure condition assessment. In particular, relevant research in the fields of computer vision, machine learning, and structural engineering is presented. The work reviewed is classified into two types: inspection applications and monitoring applications. The inspection applications reviewed include identifying context such as structural components, characterizing local and global visible damage, and detecting changes from a reference image. The monitoring applications discussed include static measurement of strain and displacement, as well as dynamic measurement of displacement for modal analysis. Subsequently, some of the key challenges that persist toward the goal of automated vision-based civil infrastructure and monitoring are presented. The paper concludes with ongoing work aimed at addressing some of these stated challenges. 展开更多
关键词 Structural inspection and MONITORING Artificial INTELLIGENCE Computer vision machine learning Optical flow
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Realtime Vision-Based Surface Defect Inspection of Steel Balls 被引量:4
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作者 王仲 邢芊 +1 位作者 付鲁华 孙虹 《Transactions of Tianjin University》 EI CAS 2015年第1期76-82,共7页
In the proposed system for online inspection of steel balls, a diffuse illumination is developed to enhance defect appearances and produce high quality images. To fully view the entire sphere, a novel unfolding method... In the proposed system for online inspection of steel balls, a diffuse illumination is developed to enhance defect appearances and produce high quality images. To fully view the entire sphere, a novel unfolding method is put forward based on geometrical analysis, which only requires one-dimensional movement of the balls and a pair of cameras to capture images from different directions. Moreover, a realtime inspection algorithm is customized to improve both accuracy and efficiency. The precision and recall of the sample set were 87.7% and 98%, respectively. The average time cost on image processing and analysis for a steel ball was 47 ms, and the total time cost was less than 200 ms plus the cost of image acquisition and balls' movement. The system can sort 18 000 balls per hour with a spatial resolution higher than 0.01 mm. 展开更多
关键词 machine vision steel ball defect inspection image processing
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Automatic Quality Inspection of Bakery Products Based on Shape and Color Information 被引量:2
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作者 Babar Khan Fang Han +1 位作者 Zhijie Wang Ather Iqbal 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2017年第5期88-96,共9页
An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX base... An automatic intelligent system for the colour and texture inspection of bakery products is proposed.In this system,advance classification technique featuring Support Vector Machine and biologically inspired HMAX based shape descriptor integrated with biologically plausible RGB Opponent-Colour-Channel Descriptor is used to classify bakery products to their respective classes based on the shape and based on their colour referring to different baking durations. The results of this paper are compared with other methods for the automatic bakery products inspection. It is discovered that biologically inspired computer vision models performs accurately and efficiently as compared to the computer vision models which are not biologically plausible,in the bakery products quality inspection. It is also discovered that the One Versus One SVM and Directed Acyclic Graph SVM acquired the maximum accurate classification rate. The proposed method acquired classification accuracy of 95% and 100% for the biscuit shape and biscuit colour recognition,respectively. The proposed method is also consistently stable and invariant. This shows that the biologically inspired computer vision models have the capability to replace existing inspection methods as more reliable and accurate alternative. 展开更多
关键词 BAKERY products quality inspection computer vision HMAX OPPONENT COLOR channel RGB COLOR DESCRIPTOR Support Vector machine (SVM)
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基于机器视觉的飞机故障检查系统 被引量:1
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作者 袁忠大 程秀全 王大伟 《机床与液压》 北大核心 2024年第6期196-200,共5页
针对当前飞机维修检查工作以人工目视检查为主、效率低且存在人为因素影响的情况,设计一套基于图像识别与机器深度学习的飞机部件表面无损检测系统。收集并整理了某航空公司一线飞机维修员拍摄的飞机机身及发动机部件图片,对图片集进行... 针对当前飞机维修检查工作以人工目视检查为主、效率低且存在人为因素影响的情况,设计一套基于图像识别与机器深度学习的飞机部件表面无损检测系统。收集并整理了某航空公司一线飞机维修员拍摄的飞机机身及发动机部件图片,对图片集进行预处理,包括通道提取、Sobel滤波处理及二值化;最后用Blob分析对处理后的图像进行特征提取与系统分析。系统运行速度快、准确率高且可连续自动识别图像。利用机器视觉技术对飞机部件表面进行无损检测不仅可以提高生产效率,同时可以去除人为因素对航空器飞行安全的影响,使得飞机的飞行安全得到进一步提升。实践证明,该系统性能稳定可靠,具有极高的推广应用价值。 展开更多
关键词 机器视觉技术 图像处理 飞机部件 无损检测
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大尺寸工件螺孔的机器视觉测量方法研究
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作者 汪志成 赵杰 +1 位作者 黄南海 王哲 《计算机仿真》 2024年第5期318-324,共7页
基于3C产品外壳工件螺纹圆孔加工时通常采用角点定位的特点,利用线阵相机采集子图像的连续性,提出基于直线特征和圆特征定位的螺纹圆孔位置尺寸测量方法。基于拟合法改进的Hough直线定位方法和基于乘同余法改进Hough变换圆形检测方法,实... 基于3C产品外壳工件螺纹圆孔加工时通常采用角点定位的特点,利用线阵相机采集子图像的连续性,提出基于直线特征和圆特征定位的螺纹圆孔位置尺寸测量方法。基于拟合法改进的Hough直线定位方法和基于乘同余法改进Hough变换圆形检测方法,实现3C外壳工件图像边缘定位及螺纹圆孔的圆心坐标提取及直径尺寸测量;基于图像的连续性,采用子图像逐一检测,相邻子图像起始像素累加的方式,实现大尺寸图像螺纹圆孔尺寸全局检测。上述方法最终实现大尺寸3C外壳工件螺纹圆孔的位置尺寸测量精度为±0.2220mm和孔径大小测量±0.0904mm,单工件检测耗时为33.737s。 展开更多
关键词 机器视觉 大尺寸工件 直线检测 圆孔检测
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基于机器视觉的小白杏热风干燥控制系统设计
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作者 杨嘉鹏 王帅帅 +1 位作者 黄卉 刘子绰 《农业工程》 2024年第3期91-96,共6页
设计了一种基于机器视觉的小白杏热风干燥控制系统,该系统使用计算机视觉技术,对小白杏进行检测和分类,并自动控制热风干燥过程中的温度、风速。系统采用基于神经网络的目标检测算法,对小白杏进行检测和分割,利用图像处理技术提取小白... 设计了一种基于机器视觉的小白杏热风干燥控制系统,该系统使用计算机视觉技术,对小白杏进行检测和分类,并自动控制热风干燥过程中的温度、风速。系统采用基于神经网络的目标检测算法,对小白杏进行检测和分割,利用图像处理技术提取小白杏的特征,并使用YOLOv7对小白杏进行分类。通过调整热风干燥的温度、风速和时间等参数,实现了对小白杏干燥过程中的品质保护,可保持小白杏品质和口感,提升杏干经济价值,该系统具有一定的应用前景。 展开更多
关键词 机器视觉 热风干燥 小白杏 目标检测 YOLOv7
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基于机器视觉的机器人环境感知技术研究
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作者 黄晓清 朱荣钊 《太原学院学报(自然科学版)》 2024年第4期24-29,共6页
环境感知技术是巡检机器人场景应用的核心技术,对传统单目感知技术存在的环境适应性差的问题,提出了融合雷达感知和视觉感知的双目环境感知技术。通过雷达外参、相机外参、相机内参建立了5个坐标系之间的转换关系,实现了雷达传感与视觉... 环境感知技术是巡检机器人场景应用的核心技术,对传统单目感知技术存在的环境适应性差的问题,提出了融合雷达感知和视觉感知的双目环境感知技术。通过雷达外参、相机外参、相机内参建立了5个坐标系之间的转换关系,实现了雷达传感与视觉传感之间的有效融合。将其应用于矿井用巡检机器人环境感知中,采用Canny边缘检测算法检测图像边缘,SVM实现图像语义分割。通过样机实验验证了雷达传感与视觉传感融合的双目感知技术对环境的感知能力比较强,感知结果明显优于单独的视觉感知和雷达感知。这对巡检机器人在复杂、恶劣环境下的应用提供了技术支撑。 展开更多
关键词 机器视觉 环境感知 巡检机器人
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新型无损检测技术在番茄品质检测中的研究与应用进展 被引量:3
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作者 韩子馨 张丽丽 +2 位作者 张博 邹方磊 尚楠 《食品科学》 EI CAS CSCD 北大核心 2024年第1期289-300,共12页
番茄是我国种植面积最广的蔬菜之一,受到广大消费者的青睐。近年来,随着人们对健康饮食需求的逐步提升,番茄的品质愈发受到关注。番茄形状较为规则,但不同品种间的大小、果型、颜色差异较大,蕴含的营养成分种类繁多、化学结构复杂,导致... 番茄是我国种植面积最广的蔬菜之一,受到广大消费者的青睐。近年来,随着人们对健康饮食需求的逐步提升,番茄的品质愈发受到关注。番茄形状较为规则,但不同品种间的大小、果型、颜色差异较大,蕴含的营养成分种类繁多、化学结构复杂,导致其品质检测存在一定难度。传统番茄品质检测方法大多存在主观性强、破坏性强、耗时费力的缺点,难以满足大规模品质检测的需求。近年来,随着各类无损检测技术的发展,机器学习、多光谱技术、电子鼻/电子舌等新型检测方法也已逐步应用于番茄品质的快速、无损检测中。本文在传统番茄品质检测技术的基础上,重点总结了基于图像识别的人工智能、电子鼻技术和光谱技术在番茄无损检测方面的发展与应用,为番茄品质检测的研究与发展提供参考。 展开更多
关键词 番茄品质检测 可见-近红外光谱 高光谱成像 拉曼光谱 电子鼻 机器视觉
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基于机器视觉的回转体表面微孔数量在机检测方法
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作者 李秀鑫 程雪峰 +3 位作者 王磊 顾菘 龙玲 韩雷 《工具技术》 北大核心 2024年第4期149-153,共5页
油滤是液压系统油路中的一个重要零件,油滤上通孔数量是油滤零件质量检测的关键指标之一。由于其尺寸较小,微孔数目大,难以用人工检测的方式进行统计,因此针对数控加工工序后的油滤零件建立了一种回转体零件表面微孔数量统计的在机检测... 油滤是液压系统油路中的一个重要零件,油滤上通孔数量是油滤零件质量检测的关键指标之一。由于其尺寸较小,微孔数目大,难以用人工检测的方式进行统计,因此针对数控加工工序后的油滤零件建立了一种回转体零件表面微孔数量统计的在机检测系统,该系统在数控加工后可以直接对加工零件进行在机检测,避免了零件二次装夹产生的加工误差。利用机器视觉技术,提出了一种不需要预先建立匹配模板、通用性较强的回转体零件表面微孔统计方法,可以自适应地统计各种回转体表面微孔数目。其中,扫描线自适应定位和周期估计算法保证了孔数统计的精确度。结果证明,提出的实际孔数标定方法为孔数统计算法的性能评估提供了重要参考依据。 展开更多
关键词 油滤 机器视觉 回转体 微孔 在机检测
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航空发动机叶片表面损伤与检测研究进展
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作者 程亚茹 李湉 +3 位作者 薛辉 黎红英 王丹 唐鋆磊 《航空发动机》 北大核心 2024年第2期32-44,共13页
航空发动机叶片的工作环境极其恶劣,表面会出现各种类型的损伤。在损伤早期进行表面检测能够有效预防因损伤扩展导致的叶片失效断裂。发动机叶片表面损伤的检测和评估主要由人工操作,严重依赖工作经验,但人工检测不仅效率低下,而且检测... 航空发动机叶片的工作环境极其恶劣,表面会出现各种类型的损伤。在损伤早期进行表面检测能够有效预防因损伤扩展导致的叶片失效断裂。发动机叶片表面损伤的检测和评估主要由人工操作,严重依赖工作经验,但人工检测不仅效率低下,而且检测结果容易受到人为因素的影响。为了高效、高精度地检测发动机叶片表面损伤,从叶片失效形式出发,综述了发动机叶片在停放和运行2种状态下的损伤机理,并重点阐述了涡流检测、渗透检测等常用于叶片表面损伤检测的方法。总结了基于机器视觉的检测技术,分析机器视觉检测面临数据集稀缺和单一性的挑战,认为收集大量数据并进一步完善评估标准是未来发动机叶片表面损伤检测系统研究的重点方向。 展开更多
关键词 叶片损伤 无损检测 机器视觉 深度学习 航空发动机
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基于机器视觉的水果外观品质检测研究进展
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作者 马跃 张文强 +3 位作者 牛宽 常君瑞 徐亭 于新海 《食品安全质量检测学报》 CAS 2024年第13期177-185,共9页
水果中富含多种营养成分,随着经济和社会生活水平的提高,高品质水果越来越受人们的青睐,其外观品质已经成为影响消费者采购的重要因素。早期我国主要依赖人工对水果进行分级,效率和准确率较低,成本和工人劳动强度较大。近年来随着机器... 水果中富含多种营养成分,随着经济和社会生活水平的提高,高品质水果越来越受人们的青睐,其外观品质已经成为影响消费者采购的重要因素。早期我国主要依赖人工对水果进行分级,效率和准确率较低,成本和工人劳动强度较大。近年来随着机器视觉技术的不断发展,大量的学者将视觉技术应用到水果外观品质的检测中,这种技术具有无损坏、低成本、高效率和操作方便等优点。本文结合国内外学者的研究成果,梳理了机器视觉在水果外观颜色、形状、大小、缺陷和纹理检测中的应用,着重介绍了缺陷提取和分类器对水果识别算法的研究进展,分析了传统视觉分级、机器学习和深度学习的应用特点,提出了机器视觉技术存在的问题并对未来发展趋势进行了展望,以期为水果外观品质检测研究提供参考与借鉴。 展开更多
关键词 机器视觉 水果分级 品质检测
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基于机器视觉的输电线路巡检路径三维自适应调度模型 被引量:2
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作者 谢晓刚 《电子设计工程》 2024年第6期42-46,共5页
为准确规划输电线路巡检路径,提出基于机器视觉的输电线路巡检路径三维自适应调度模型。以无人机群为飞行平台,采集并拼接目标巡检区域的输电线路图像;通过逐一构建杆塔、导地线及其他输电设备三维模型,获取整体输电线路三维模型;建立... 为准确规划输电线路巡检路径,提出基于机器视觉的输电线路巡检路径三维自适应调度模型。以无人机群为飞行平台,采集并拼接目标巡检区域的输电线路图像;通过逐一构建杆塔、导地线及其他输电设备三维模型,获取整体输电线路三维模型;建立输电线路巡检路径智能规划模型,通过模糊状态寻优控制方法,规划无人机群巡检路线并寻找最优路线;引入码间干扰抑制法去除干扰因子,优化通信的连续性,实现输电线路巡检路径三维自适应调度。实验证明,该模型能合理地规划输电线路巡检路径,实现输电线路巡检路径三维自适应调度,同时可以输出全面、清晰的巡检图像。 展开更多
关键词 机器视觉 输电线路 巡检路径 自适应调度 图像采集 三维模型
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桥梁面相学及其研究进展
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作者 周志祥 周丰力 楚玺 《重庆交通大学学报(自然科学版)》 CAS CSCD 北大核心 2024年第3期1-9,共9页
为了探索更加实效、经济、便捷、可信的桥梁安全状态检(监)测新方法,受中医望、闻、问、切诊断人体健康状态理念启迪,提出了依据桥梁外观形态变化来获知结构近期安全状态的桥梁面相学;总结了10多年来基于桥梁面相学的桥梁安全状态检(监... 为了探索更加实效、经济、便捷、可信的桥梁安全状态检(监)测新方法,受中医望、闻、问、切诊断人体健康状态理念启迪,提出了依据桥梁外观形态变化来获知结构近期安全状态的桥梁面相学;总结了10多年来基于桥梁面相学的桥梁安全状态检(监)研究进展;介绍了基于定点相机平转+竖转拍摄的桥梁动静影像全息性态监测系统、基于激光雷达+全景数码相机拍摄的WWWQ-G桥梁安全巡检车、基于普通摄像头拍摄的常规跨径桥梁安全监测系统和基于定点旋转测量装置的拉索性态远距全域视频检测系统的构成理论,以及各系统应用于桥梁构件损伤检测的试验研究案例和实际工程应用案例;展望了融合“测点传感器+机器视觉”实现桥梁结构状态的“精+密”监测方法及其应用前景。 展开更多
关键词 桥梁工程 桥梁检(监)测 机器视觉 全息变形 装备研发
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