Insight最新文献

{"title":"Finite element analysis of magnetomechanical coupling behaviour of perforated steel plate","authors":"Fuchen Zhang, Zecheng Sun","doi":"10.1784/insi.2023.65.9.514","DOIUrl":"https://doi.org/10.1784/insi.2023.65.9.514","url":null,"abstract":"In this paper, finite element analysis is carried out for the stress of a 45# steel specimen with a round hole and its correlation with a magnetic signal. The leakage magnetic field signals of the specimen under different loads are obtained. The results show that the greater the tensile stress is, the greater the stress is at 2 mm above the round hole, and the permeability first increases and then decreases with the increase in stress. The leakage magnetic field signal is correlated with permeability and the tangential component of the magnetic flux leakage signal has a trend of increasing first and then decreasing. The phenomenon of zero crossing of the normal component of the leakage magnetic field signal appears.","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation into defect image segmentation algorithms for galvanised steel sheets under texture backgrounds","authors":"Rui Pan, Wei Gao, Yunbo Zuo, Guoxin Wu, Yuda Chen","doi":"10.1784/insi.2023.65.9.492","DOIUrl":"https://doi.org/10.1784/insi.2023.65.9.492","url":null,"abstract":"Image segmentation is a significant step in image analysis and computer vision. Many entropy-based approaches have been presented on this topic. Among them, Tsallis entropy is one of the best-performing methods. In this paper, the surface defect images of galvanised steel sheets were studied. A two-dimensional asymmetric Tsallis cross-entropy image segmentation algorithm based on chaotic bee colony algorithm optimisation was used to investigate the segmentation of surface defects under complex texture backgrounds. On the basis of Tsallis entropy threshold segmentation, a more concise expression form was used to define the asymmetric Tsallis cross-entropy in order to reduce the calculation complexity of the algorithm. The chaotic algorithm was combined with the artificial bee colony (ABC) algorithm to construct the chaotic bee colony algorithm, so that the optimal threshold of Tsallis entropy could be quickly identified. The experimental results showed that compared with the maximum Shannon entropy algorithm, the calculation time of this algorithm decreased by about 58% and the threshold value increased by about (26%, 54%). Compared with the two-dimensional Tsallis cross-entropy algorithm, the calculation time of this algorithm decreased by about 35% and about 20% was improved in the g-axis direction only. Compared with the two-dimensional asymmetric Tsallis cross-entropy algorithm, the calculation time of this algorithm decreased by about 30% and the threshold values of the two algorithms were almost the same. The algorithm proposed in this paper can rapidly and effectively segment defect targets, making it a more suitable method for detecting surface defects in factories with a rapid production pace.","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volume integral model for algebraic image reconstruction and computed tomography","authors":"R Hanna, M Sutcliffe, D Carswell, P Charlton, S Mosey","doi":"10.1784/insi.2023.65.9.484","DOIUrl":"https://doi.org/10.1784/insi.2023.65.9.484","url":null,"abstract":"Industrial computed tomography (CT) has seen widespread adoption as an inspection technique due to its ability to resolve small defects and perform high-resolution measurements on complex structures. The reconstruction of CT data is usually performed using filtered back-projection (FBP) methods, such as the Feldkamp-Davis-Kress (FDK) method, and are selected as they offer a good compromise between reconstruction time and quality. More recently, iterative reconstruction algorithms have seen a resurgence in research interest as computing power has increased. Iterative reconstruction algorithms, such as the algebraic reconstruction technique (ART), use a reconstruction approach based on linear algebra to determine voxel attenuation coefficients based on the measured attenuation of the sample at the detector and calculation of the ray paths traversing the voxel grid. This offers a more precise model for CT reconstruction but at the cost of computational complexity and reconstruction time. Existing ART implementations are based on the 2D weighting models of the binary integral method (BIM), line integral method (LIM) and area integral method (AIM). For full 3D reconstruction, BIM and LIM only offer approximations leading to numerical inaccuracies. AIM for 2D reconstruction is mathematically exact but considers the divergent nature of a fan beam for 2D only. For a full 3D volumetric reconstruction, the X-ray cone beam is divergent in all directions and therefore AIM cannot be applied in its current form. A novel voxel weighting method for 3D volumetric image reconstruction using ART and providing a mathematically exact fractional volume weighting is introduced in this paper and referred to as the volume integral method (VIM). A set of algorithms is provided based on computer graphics techniques to determine ray/voxel intersections with volume reconstruction computed based on the divergence theorem. A set of experimental configurations is developed to provide a comparison against existing methods and conclusions are provided. Optimisation is achieved through graphic acceleration.","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic defect detection in a steel sample using frequency-modulated thermal wave imaging","authors":"J Ahmad, R Mulaveesala","doi":"10.1784/insi.2023.65.9.501","DOIUrl":"https://doi.org/10.1784/insi.2023.65.9.501","url":null,"abstract":"Non-stationary thermal wave imaging (NSTWI) techniques are primarily used to assess material properties and structural integrity without damaging a structure. Frequency-modulated thermal wave imaging (FMTWI) is a well-known NSTWI approach that uses a low-peak power heat source to examine structures in a reasonable experimentation time. Recently, various methods, such as pulse compression, Fourier transform, principal component analysis (PCA) and independent component analysis (ICA), have been introduced to handle the non-linearity of transient thermal signatures. However, handling non-linearity and developing a fully automatic defect detection system remains very challenging due to certain limitations of the aforementioned methods. To overcome these problems, this paper proposes an artificial neural network (ANN) for the identification of subsurface flaws in a mild steel sample investigated using the FMTWI approach. The accuracy and the performance of the proposed neural network (NN) are evaluated through a confusion matrix and region of convergence (ROC) analysis for the classification of defective and healthy pixels in an infrared image sequence. The developed NN model has achieved 99.7% accuracy in classifying the pixels correctly.","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agile MBSE: Doing the Same Thing We Have Always Done, but in an Agile Way with Models","authors":"Matthew Hause","doi":"10.1002/inst.12442","DOIUrl":"https://doi.org/10.1002/inst.12442","url":null,"abstract":"<div>\u0000 \u0000 <p>Agile systems engineering is not new. Work has progressed on this for many years to the point that criteria has been established regarding best practice as well as a means of quantifying adherence. The future of systems engineering (FuSE) initiative is reexamining how agile systems engineering fits into the FuSE (Willette et al. 2021). As model-based systems engineering (MBSE) is also a FuSE theme, it is only proper to look at how agile systems engineering and MBSE complement and enable each other. This article examines some of the aspects of MBSE–specifically the Systems Modeling Language® (SysML) – and show at how an agile approach to MBSE can help with the concepts of stakeholder engagement, continual integration, and dynamic learning and evolution. For reasons of space, the article will only provide minimal definitions and explanations of the basics of MBSE, agile, and SysML and as these are well known concepts.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50147043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Large Scale Agile Can Operate Systems Engineering in the Future","authors":"Laurent Alt,&nbsp;Mikaël Le Mouëlli","doi":"10.1002/inst.12440","DOIUrl":"https://doi.org/10.1002/inst.12440","url":null,"abstract":"<div>\u0000 \u0000 <p>The significant shift happening today towards more connected, more automated, and more autonomous systems is bringing software inside all systems, and at the same time agile practices. Our experience of large-scale agile deployments in companies building or operating complex systems in automotive and aerospace shows that, whereas both approaches can easily coexist in isolated teams within the same company, major problems arise when coordinating them at the leadership level, where they are perceived as antagonist, and create misalignments, friction and quality issues. In this article, we propose to describe why it is important to make agile and systems engineering work together, how to do it, and how this impacts how we see value, systems, digital twins, and leadership. The following concepts of the FuSE agile roadmaps are addressed:</p>\u0000 <p>\u0000 </p><ul>\u0000 \u0000 <li>▪ Agility with long lead time components and dependencies</li>\u0000 \u0000 <li>▪ Agility across organizations boundaries</li>\u0000 \u0000 <li>▪ Orchestrating agile operations.</li>\u0000 </ul>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying Agility for Sustainable Security","authors":"Larri Ann Rosser","doi":"10.1002/inst.12445","DOIUrl":"https://doi.org/10.1002/inst.12445","url":null,"abstract":"<div>\u0000 \u0000 <p>Systems engineering faces ongoing challenges due to the pace of change in technology and needs as well as the complexity, resilience, and adaptability demanded of solutions. System security needs and challenges are a prominent factor in the increasing demands placed on solutions and the systems engineers who design and develop them. The adoption of program level agile execution is one strategy for addressing these escalating challenges. In this article we describe how the broadly adopted technical processes from the ISO/IEEE/IEC 15288:2015 standard can be executed using agile methods to realize a large complex solution. In addition, we provide specific recommendations for executing these processes in a manner that enables systems to be sustainably secure – that is, to retain the desired level of security throughout the life cycle.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50147046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systems Engineering Agility in a Nutshell","authors":"Rick Dove,&nbsp;Kerry Lunney,&nbsp;Michael Orosz,&nbsp;Mike Yokell","doi":"10.1002/inst.12438","DOIUrl":"https://doi.org/10.1002/inst.12438","url":null,"abstract":"<div>\u0000 \u0000 <p>Systems engineering must necessarily have the agility to anticipate and effectively respond to an increasingly dynamic and uncertain environment. Agile systems engineering, agile software engineering, and agile any-kind-of engineering share common goals and leverage common agility-enabling strategies. This article succinctly describes eight strategic aspects with application discussions at the systems engineering level.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50147050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-Based Systems Engineering as an Enabler of Agility","authors":"Sophie Plazanet,&nbsp;Juan Navas","doi":"10.1002/inst.12441","DOIUrl":"https://doi.org/10.1002/inst.12441","url":null,"abstract":"<div>\u0000 \u0000 <p>Model-based systems engineering (MBSE) with agility can help systems engineering programs which deal with both increasing complexity and frequent changes in environment and usages, shorter time-to-market, uncertainty of the needs, and more sophisticated industrial schemes. Agile approaches originated in software engineering can be extended and tailored to a certain extent to complex systems engineering and particularly to MBSE. Main benefits of agility are provision of a minimum viable product as early as possible in the schedule, early capture of changes of needs, enabling to deliver a system answering to the real needs, and securing of the value proposal. It includes also potential reduction in rework of the final system through regular customer feedback throughout development (left shift for the defect correction with early exposure), and efficiency of the use of resources. Concerning MBSE, the use of models as a single source of truth for completeness and consistency is useful to share and secure the design by improving communication within engineering teams and the building and support of the development strategy, and to help to automate some tasks such as model exchange and synchronization. In addition to the benefits of each approach, combining them may help to:</p>\u0000 <p>\u0000 </p><ul>\u0000 \u0000 <li>▪ <b>Organize and synchronize</b> the development and validation effort of one or multiple engineering teams.</li>\u0000 \u0000 <li>▪ <b>Faster impact analysis</b> including trade-off studies/options and hence a <b>faster reaction to evolutions</b> in expectations and constraints, that is, the agility of systems.</li>\u0000 \u0000 <li>▪ <b>Show regularly “end to end” value</b> to the customer and other stakeholders.</li>\u0000 </ul>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50147042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FROM THE EDITOR-IN-CHIEF","authors":"William Miller","doi":"10.1002/inst.12436","DOIUrl":"https://doi.org/10.1002/inst.12436","url":null,"abstract":"","PeriodicalId":13956,"journal":{"name":"Insight","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}