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Imagery Creation based on Autonomic System for Finite Element by using Fully Convolutional Network

机译:基于自动系统的Imagery创建通过全卷积网络实现有限元

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For applications in Industry 4.0, a system that can analyze the deformation and stress of a target object from an image acquired by a smartphone or tablet is proposed in this paper. The process for the proposed system is more convenient for users than creating a computer-aided design model. The target objects include bridges and plant equipment, and the proposed process aims to facilitate maintenance inspections. To acquire results from this system, a fully convolutional network is employed to extract the target object from the obtained image, and density-based topology optimization is applied to produce a finite element model, which is imported to commercial software. Artificial intelligence image processing is adopted to generate the output of the finite element model for the target object. In this work, numerical examples demonstrate that the final model for the target object is accurate and appropriate for finite element deformation and stress analysis.
机译:对于工业4.0的应用,在本文中提出了一种系统,可以从智能手机或平板电脑中获取的图像中的目标对象的变形和应力。 对于用户而言,该系统的过程比创建计算机辅助设计模型更方便。 目标物体包括桥梁和工厂设备,所提出的过程旨在促进维护检查。 为了从该系统获取结果,采用完全卷积的网络来从所获得的图像中提取目标对象,并且应用了基于密度的拓扑优化来产生有限元模型,该模型将导入商业软件。 采用人工智能图像处理来生成目标对象的有限元模型的输出。 在这项工作中,数值示例表明目标物体的最终模型是准确的,适用于有限元变形和应力分析。

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