intelligent Weld inspection

定期检查焊缝的完整性对于维护关键资产的安全和高效运行至关重要。基于超声波的方法有许多优点--它们快速、方便、无干扰--但当用于具有复杂微观结构的厚焊缝时，它们会遇到严重的障碍。H2020咨询项目开发并展示了应对核能领域这些挑战的技术。对于其中的大多数，焊缝内部材料结构的知识是必不可少的。在ADVISE奠定的基础上，iWeld的目标是在就地实施成像和表征方法方面取得进展，并将其应用范围扩大到核能部门以外。该项目将结合来自广泛行业的见解来构建一个全面的焊接库，该库将用于训练预测焊缝内部材料结构的人工智能模型。这些预测将用于进一步改进的反演和成像算法，以提供全面的检查计划工作流程。IWeld的目标是改变对多个行业分支的复杂焊缝进行超声波检测的方式，并提供开放的工具来支持它们的发展。

Periodic inspection of the integrity of welds is essential for maintaining safe and efficient operation of critical assets. Methods based on ultrasound have numerous advantages – they are fast, accessible and non-disruptive – but they meet serious obstacles when used on thick welds with a complex microstructure. The H2020 ADVISE project developed and demonstrated techniques to address these challenges in the nuclear energy context. For most of these, the knowledge of the internal material structure of the weld is essential. Building up foundations laid by ADVISE, iWeld aims to progress towards implementing the imaging and characterisation methods insitu and broaden their application scope beyond the nuclear energy sector. The project will combine insights from a wide spectrum of industries to construct a comprehensive weld library which will be used to train an AI model predicting the internal material structure of the weld. These predictions will be used in further refined inversion and imaging algorithms to deliver a comprehensive inspection planning workflow. The ambition of iWeld is to transform the way to perform ultrasonic inspection on complex welds across several branches of industry and to deliver open tools to support their development.