A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

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.

Bridge Condition Assessment by Visual Inspection-Croatian Experience

Most decisions relating to bridge maintenance are founded on assessments that are based on visual inspections conducted by specially trained engineers,using procedures and aids defined in the management system.Visual inspection is the main tool for bridge condition assessment,and is therefore of crucial significance for planning periodic maintenance activities.Paper shall present the study aimed at harmonizing bridge assessment activities,which was conducted in early 2012 in company Hrvatske ceste-Croatian National Road Authority.Small RC bridges were chosen for this study,since visual inspection is usually only tool utilized for their assessment.Ratings obtained by inspection were analyzed using methods of mathematical statistics.The results point to weaknesses in the current assessment system,while the study itself constitutes a good basis for further improvement of management aids,manuals and procedures for bridge inspection.

Automated Visual Inspection System for Specifying Brick Quality

Automated visual inspection system has been developed to specify brick quality and the accepting of the bricks in a production line. This system is based on CMOS web-camera placed in manufacture line. Depending on diameters, area, perimeter and cracks of a brick, a strong algorithm has been developed, and this algorithm is created to befit the required for measuring bricks quality. The quality is measured by fuzzy system which can give percent accepting to a brick under the test. Fuzzy reasoning gives the system more reliability than other inspection system.

A smart assistance system for cable assembly by combining wearable augmented reality with portable visual inspection

Background Assembly guided by paper documents is the most widespread type used in the process of aircraft cable assembly.This process is very complicated and requires assembly workers with high-level skills.The technologies of wearable Augmented Reality(AR)and portable visual inspection can be exploited to improve the efficiency and the quality of cable assembly.Methods In this study,we propose a smart assistance system for cable assembly that combines wearable AR with portable visual inspection.Specifically,a portable visual device based on binocular vision and deep learning is developed to realize fast detection and recognition of cable brackets that are installed on aircraft airframes.A Convolutional Neural Network(CNN)is then developed to read the texts on cables after images are acquired from the camera of the wearable AR device.An authoring tool that was developed to create and manage the assembly process is proposed to realize visual guidance of the cable assembly process based on a wearable AR device.The system is applied to cable assembly on an aircraft bulkhead prototype.Results The results show that this system can recognize the number,types,and locations of brackets,and can correctly read the text of aircraft cables.The authoring tool can assist users who lack professional programming experience in establishing a process plan,i.e.,assembly outline based on AR for cable assembly.Conclusions The system can provide quick assembly guidance for aircraft cable with texts,images,and a 3 D model.It is beneficial for reducing the dependency on paper documents,labor intensity,and the error rate.

Automated visual inspection of surface defects based on compound moment invariants and support vector machine

The traditional inspection methods are mostly based on manual inspection which is very likely to make erroneous judgments due to personal subjectivity or eye fatigue, and can＇t satisfy the accuracy. To overcome these difficulties, we develop a machine vision inspection system. We first compare several kinds of methods for feature extraction and classification, and then present a real-time automated visual inspection system for copper strips surface （CSS） defects based on compound moment invariants and support vector machine （SVM）. The proposed method first processes images collected by hardware system, and then extracts feature characteristics based on grayscale characteristics and morphologic characteristics （Hu and Zernike compound moment invariants）. Finally, we use SVM to classify the CSS defects. Furthermore, performance comparisons among SVM, back propagation （BP） and radial basis function （RBF） neural networks have been involved. Experimental results show that the proposed approach achieves an accuracy of 95.8% in detecting CSS defects.

Development of a cervical cancer screening program in a slum setting using visual inspection with acetic acid: Analysis of feasibility and cost

Objective: In Bangladesh, cervical cancer is the second most common cause of cancer deaths in women. Annually, over 50 million women are at risk for cervical cancer, with 17,686 cases diagnosed and 10,362 deaths each year. Visual inspection with acetic acid (VIA) is a well validated tool in low resource areas for identifying cervical lesions. In this pilot study, AK Khan Health Care Trust (AKKHCT), in collaboration with oncologists at Massachusetts General Hospital (LB, BD, AG), launched a VIA cervical cancer-screening program. Methods: A clinic was established in the Korail Slum of Dhaka, a 90-acre slum with over 70,000 inhabitants, in the summer of 2011. From September 17, 2011 to November 1, 2011, ten women living in the Korail Slum were recruited and completed the three-month training program to learn how to do a pelvic examination and to evaluate the cervix using VIA. Three of the ten women performed VIA screening during the study period. Results: 44 patients were recruited and 8 women were identified to have VIA-positive results for a screen-positive rate of 18.2%. Two of the eight women underwent treatment. One woman underwent an excisional procedure for pre-invasive disease in the slum clinic. The other woman had an early invasive cervical cancer and was successfully treated in a local hospital. Conclusion: Our pilot project demonstrates some important factors in developing and implementing a successful screening program. Involving laywomen as healthcare workers provides a strong tie to community, as well as education, economic independence, and empowerment for women who would otherwise occupy a lower social standing in their community. VIA is feasible in the complicated environment of an inner city slum. It was feasible to perform minor excisional procedures to treat pre-invasive cervical disease in the slum clinic.

Image Quality Improvement for Underwater Visual Inspections of Nuclear Power Plants

Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.

Control System Design and Validation for Visual Based Indoor Inspection Helicopter

This paper is on control system design for visual based indoor inspection by the model helicopters. For the indoor inspection system for large structures, there are some cases where it is difficult for htunans to work with. This paper introduces indoor inspection helicopter system with only inspection camera and prism for position sensing as payload. The control system is designed to help the operator of the inspection system to control the helicopter to designated position without much practice. The cases of the control by experienced and novice operators are compared and results show that the system has feasibility for indoor inspection system to be used by any kind of users.

Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

SpyGlass application for duodenoscope working channel inspection: Impact on the microbiological surveillance

BACKGROUND Patient-ready duodenoscopes were designed with an assumed contamination rate of less than 0.4%;however,it has been reported that 5.4%of clinically used duodenoscopes remain contaminated with viable high-concern organisms despite following the manufacturer’s instructions.Visual inspection of working channels has been proposed as a quality control measure for endoscope reprocessing.There are few studies related to this issue.AIM To investigate the types,severity rate,and locations of abnormal visual inspection findings inside patient-ready duodenoscopes and their microbiological significance.METHODS Visual inspections of channels were performed in 19 patient-ready duodenoscopes using the SpyGlass visualization system in two endoscopy units of tertiary care teaching hospitals(Tri-Service General Hospital and National Taiwan University Hospital)in Taiwan.Inspections were recorded and reviewed to evaluate the presence of channel scratches,buckling,stains,debris,and fluids.These findings were used to analyze the relevance of microbiological surveillance.RESULTS Seventy-two abnormal visual inspection findings in the 19 duodenoscopes were found,including scratches(n=10,52.6%),buckling(n=15,78.9%),stains(n=14,73.7%),debris(n=14,73.7%),and fluids(n=6,31.6%).Duodenoscopes>12 mo old had a significantly higher number of abnormal visual inspection findings than those≤12 mo old(46 findings vs 26 findings,P<0.001).Multivariable regression analyses demonstrated that the bending section had a significantly higher risk of being scratched,buckled,and stained,and accumulating debris than the insertion tube.Debris and fluids showed a significant positive correlation with microbiological contamination(P<0.05).There was no significant positive Spearman’s correlation coefficient between negative bacterial cultures and debris,between that and fluids,and the concomitance of debris and fluids.This result demonstrated that the presence of fluid and debris was associated with positive cultures,but not negative cultures.Further multivariate analysis demonstrated that fluids,but not debris,is an independent factor for bacterial culture positivity.CONCLUSION In patient-ready duodenoscopes,scratches,buckling,stains,debris,and fluids inside the working channel are common,which increase the microbiological contamination susceptibility.The SpyGlass visualization system may be recommended to identify suboptimal reprocessing.

Oil/Gas Pipeline Leak Inspection and Repair in Underwater Poor Visibility Conditions: Challenges and Perspectives

Mechanical pressure clamps are examples of innovative tools commonly used in the oil and gas industry for arresting leaks from damaged oil and gas pipelines. However, if leaks result from pipeline rupture, clamps are not usually recommended. It is therefore obvious that inspection of the leaking pipeline is very crucial in deciding the strategy for repair. For subsea pipelines where underwater poor visibility is pronounced, this important aspect of the pipeline repair process becomes difficult to implement. The result is a repair-leak-repair cycle. This challenge is commonly found in repairs of old pipelines in unclear water conditions. Old pipelines and their vulnerability to fractures that often lead to ruptures are discussed. In this paper, the challenges and technologies available for visualisation and examination in such unclear water conditions are discussed. There appears to be a gap in the existing pipeline integrity management system with respect to inspection and repair of pipelines in unclear water conditions. This gap needs to be filled in order to minimise spills and pollution. For pipelines installed in unclear water condition, a perspective is suggested to extend the capability of existing remotely operated vehicles to employ the use of clear laminar water system or a related technique to provide integrity engineers and operators with close visual assess to inspect leaking pipelines and effect adequate repairs. This paper suggests that the use of optical eye as the main tool for examination remains valuable in managing the challenges in underwater pipeline repairs in unclear water condition.

Development of an automatic weld surface appearance inspection system using machine vision

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.

Defect inspection of indoor components in buildings using deep learning object detection and augmented reality

Visual inspection is commonly adopted for building operation,maintenance,and safety.The durability and defects of components or materials in buildings can be quickly assessed through visual inspection.However,implementations of visual inspection are substantially time-consuming,labor-intensive,and error-prone because useful auxiliary tools that can instantly highlight defects or damage locations from images are not available.Therefore,an advanced building inspection framework is developed and implemented with augmented reality(AR)and real-time damage detection in this study.In this framework,engineers should walk around and film every corner of the building interior to generate the three-dimensional(3D)environment through ARKit.Meanwhile,a trained YOLOv5 model real-time detects defects during this process,even in a large-scale field,and the defect locations indicating the detected defects are then marked in this 3D environment.The defects areas can be measured with centimeter-level accuracy with the light detection and ranging(LiDAR)on devices.All required damage information,including defect positions and sizes,is collected at a time and can be rendered in the 2D and 3D views.Finally,this visual inspection can be efficiently conducted,and the previously generated environment can also be loaded to re-localize existing defect marks for future maintenance and change observation.Moreover,the proposed framework is also implemented and verified by an underground parking lot in a building to detect and quantify surface defects on concrete components.As seen in the results,the conventional building inspection is significantly improved with the aid of the proposed framework in terms of damage localization,damage quantification,and inspection efficiency.

Development of a certified reference material for visual inspection of unsound maize kernels

Maize unsound kernel content is one of the limited items in maize trade, and generally determined by sensory detection. A certified reference material(CRM) for visual inspection of maize unsound kernels was developed according to a national standard of China, GB 1353-2018, and five items, such as insect-damaged kernels, spotted kernels, broken kernels, sprouted kernels and moldy kernels, were included. Unsound maize kernels were collected from fields or prepared in a laboratory, then screened, and ten kernels demonstrating varying levels of unsoundness or damage for each item were embedded in epoxy resin. The CRM showed excellent homogeneity and stability, which was stable for 14 days at the temperature from-20℃ to 45℃ and for at least 18 months at room temperature out of direct sunlight and strong light. Co-laboratory confirmation showed the CRM conformed to the morphological characteristics described in GB 1353-2018. The research filled the gap of unsound maize kernel CRM in maize detection.

基于线激光的煤矿输送带纵向撕裂检测系统研究

针对煤矿输送带纵向撕裂检测准确率、实时性和响应性均不高的问题,设计了一种基于线激光和机器视觉的检测系统。介绍了该系统的工作原理,重点讲述了撕裂特征的视觉检测算法,包括图像预处理、激光条纹中心线提取、中心线断点补偿、重合误差和局部曲率的撕裂特征综合判断等。实验结果表明,该系统可实时、准确地检测输送带纵向撕裂,提升撕裂响应速度,降低撕裂事故成本,具有一定的推广应用价值。

水泥混凝土下承层精铣刨露浆率检测方法研究

桥梁、隧道水泥混凝土下承层精铣刨质量直接影响沥青面层与下承层的层间粘结和抗剪性能。通过对拓形法检测用标准片材密度稳定性分析及不同方法检测露浆率的分析研究,确定了不同规格的A4打印纸及0.5 mm和0.8 mm的透明PVC标准片材均能用于检测露浆率;拓形法操作性强,操作过程简单方便且成本低,可以客观地检测出水泥混凝土下承层精铣刨施工露浆率;拓形法可有效弥补目测法主观性太强而无法提供准确的露浆率和图像处理法成本高、操作繁琐的缺点,它是对目测法的一种补充,有利于推动水泥混凝土精铣刨施工质量检测方法的完善和发展。

基于Jetson NANO的机器人智能码垛系统

随着工业自动化的快速发展,机器人智能码垛系统在物流和制造领域中扮演着越来越重要的角色。该文设计并实现一个基于NVIDIA Jetson NANO的机器人智能码垛系统,系统选用合适的传感器和执行器,集成机器视觉检测技术,能够实现对物块的自动识别、定位和码垛。测试结果表明,该系统在识别准确率、码垛速度以及稳定性方面均达到了预期目标,并在高负载下保持稳定运行,展现了良好的性能和较高的码垛效率。

用Visual Basic实现智能仪表的微机串口连续监测与记录系统

简要介绍了Visual Basic中MSComm控件的使用方法、智能仪表的串行通信接口,并详细描述了由传感器、智能仪表、转接卡和微机组成的连续监测与记录系统的组成,以及系统软件的编程方法。该系统可实现多个传感器采样率10 Hz以下的长时间连续采集与记录。

天然气场站设备焊缝试压开裂失效分析

针对某天然气场站设备在试压时发生焊缝开裂的问题,通过宏观形貌和理化试验等方法对焊缝进行了失效分析。结果显示,该不等壁厚焊缝存在根部下塌和焊根未熔合等质量问题,在试压应力和残余应力的作用下,焊缝缺陷处从内壁起裂,并扩展至外壁。针对导致焊缝开裂的原因,提出了包括优化坡口设计、加强施工过程质量管控、对重点焊缝进行内部目视检查和表面无损检测等建议,可为预防不等壁厚焊缝失效提供参考。