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Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature
Journal of Manufacturing Systems ( IF 12.1 ) Pub Date : 2020-10-01 , DOI: 10.1016/j.jmsy.2020.07.021
Wang Cai , JianZhuang Wang , Ping Jiang , LongChao Cao , GaoYang Mi , Qi Zhou

Abstract Laser welding has been widely utilized in various industries. Effective real-time monitoring technologies are critical for improving welding efficiency and guaranteeing the quality of joint-products. In this paper, the research findings and progress in recent ten years for real-time monitoring of laser welding are critically reviewed. Firstly, different sensing techniques applied for welding quality monitoring are reviewed and discussed in detail. Then, the advanced technologies based on artificial intelligence are summarized which are exploited to realize varied objectives of monitoring such as process parameter optimization, weld seam tracking, weld defects classification, and process feedback control. Finally, the potential research problems and challenges based on real-time intelligent monitoring are discussed, such as intelligent multi-sensor signal acquisition platform, data depth fusion method and adaptive control technology. This fundamental work aims to review the research progress in laser welding monitoring and provide a basis for follow-on research.

中文翻译:

传感技术和基于人工智能的方法在激光焊接实时监控中的应用:近期文献综述

摘要 激光焊接已广泛应用于各行各业。有效的实时监控技术对于提高焊接效率和保证接头产品质量至关重要。本文对近十年来激光焊接实时监测的研究成果和进展进行了批判性综述。首先,详细回顾和讨论了应用于焊接质量监控的不同传感技术。然后总结了基于人工智能的先进技术,用于实现工艺参数优化、焊缝跟踪、焊缝缺陷分类和工艺反馈控制等多种监控目标。最后,讨论了基于实时智能监控的潜在研究问题和挑战,如智能多传感器信号采集平台、数据深度融合方法和自适应控制技术。本项基础性工作旨在回顾激光焊接监测的研究进展,为后续研究提供依据。
更新日期:2020-10-01
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