评估承受双轴载荷的钢板机械应力状态的直觉模糊发散法

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Mario Versaci, Giovanni Angiulli, Fabio La Foresta, Filippo Laganà, Annunziata Palumbo
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引用次数: 0

摘要

钢结构连接板所承受的外部机械载荷的不确定性决定了等时变形分布的非唯一性。由于钢板上感应出的涡流会产生与等时变形类似的高模糊度磁场图,因此可以利用这些磁场图来评估决定特定感应电流图的外部负载程度。根据文献中已知的方法,图谱与外部负载的关联是通过模糊相似性计算来实现的,而在本文中,我们通过提出基于发散计算的分类,用直觉模糊逻辑对该方法进行了重新表述,从而对该方法进行了推广。我们的方法对地图的模糊化进行了自适应处理,从而提高了分类率,并显著减少了由于每个施加载荷的不确定性而产生的可疑情况。此外,我们还开发了一种有限元软件工具,它在一定程度上可以替代实验程序,而实验程序的成本是出了名的高。即使该程序适用于承受双轴载荷的板材,它也可用于其他类型的载荷,因为分类运算器只处理涡流图,而不考虑其原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intuitionistic fuzzy divergence for evaluating the mechanical stress state of steel plates subject to bi-axial loads
The uncertainty that characterizes the external mechanical loads to which any connection plate in steel structures is subjected determines the non-uniqueness of the isochoric deformation distributions. Since the eddy currents induced on the plates produce magnetic field maps with a high fuzziness content, similar to those of the isochoric deformations, their use can be exploited to evaluate the extent of the external load that determines a specific induced current map. Starting from an approach known in the literature, according to which the map-external load association is operated through fuzzy similarity computations, in this paper, we generalize this method by reformulating it in terms of intuitionistic fuzzy logic by proposing a classification based on divergence computations. Our approach, acting adaptively on the fuzzification of the maps, results in a better classification percentage, besides significantly reducing the presence of doubtful cases due to the uncertainty of each applied load. Furthermore, a FEM software tool was developed, which turned out to be, to a certain extent, a substitute for the experimental procedure, notoriously more expensive. Even if the procedure was applied on plates subjected to bi-axial loads, it could be used for other types of loads since the classification operator processes the eddy current maps exclusively, regardless of their cause.
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来源期刊
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
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