工艺与制造英文2022被引 11
基于人工神经网络目标分割的自动纤维铺放在线监测检测一体化系统
Single system for online monitoring and inspection of automated fiber placement with object segmentation by artificial neural networks
Marco Brysch, Mohammad Bahar, Hans Christoph Hohensee, Michael Sinapius · Technische Universität Braunschweig
摘要整理
减少自动纤维铺放（AFP）工艺中的材料缺陷是未来高效制造大型复杂构件的重要因素。然而，复杂制造工艺的监测通常需要复杂的传感器和计算机系统，这些系统往往对干扰和误差较为敏感。图像分割与神经网络等新技术为该问题提供了新的解决方案，具有更快速、更稳健地处理复杂工艺的潜力。本研究提出了一套系统，可同时执行自动纤维铺放工艺的监测、检测和测量任务。该系统基于SiamMask网络进行自动图像处理。人工神经网络经过训练能够识别单根碳纤维带并对其进行分割以供进一步分析。针对测试数据和训练数据的生成，提出了一种解析方法。对SiamMask网络主要输出的目标分割结果进行后处理，并识别单根纤维带，可获得精确的测量结果，并通过实例进行了验证。研究表明，与传统方法相比，SiamMask等现代图像分割方法在处理高度复杂的工程任务时具有更快速、更智能的优势，展现出巨大的应用潜力。
相关论文
A review of recent developments in natural fibre composites and their mechanical performance
Composites Part A Applied Science and Manufacturing · 2015
Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee
Clinical Neurophysiology · 2015
Lignocellulosic biomass: a sustainable platform for the production of bio-based chemicals and polymers
Polymer Chemistry · 2015
Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints
CIRP Annals · 2016
Nanoimprint Lithography: Methods and Material Requirements
Advanced Materials · 2007
Nanocomposites: synthesis, structure, properties and new application opportunities
Materials Research · 2009
← 返回论文库整理：复材站编辑部