Robotic Enabled Sensing/Welding

该项目的目标是研究基于超声波体积数据的传感器驱动的高完整性焊接自动化，以便在具有挑战性的工业环境中每次都能安全地提供高质量的焊缝。传统上，高完整性接头的焊接和检查是单独的、顺序的，通常是制造和维修中的手动过程。最终，这些限制会降低生产率、产量、进度确定性，并在焊接完成时检测到缺陷时增加返工。由于焊接是一个动态的体积过程，融合深度和宽度的接缝，该项目旨在利用超声波的体积成像能力，并将这种检测方式直接引入焊接过程控制回路。通过研究机器人在线超声波检测和控制，该项目旨在每次都能正确地提供高完整性的焊缝，并克服当前的技术和工艺限制。在线超声波焊接控制旨在提供显著的减少，根据当前的操作数据估计：- > 55%的焊接工艺时间- > 50%的总焊接成本- > 75%的工时这些显着的技术、商业和安全效益支撑了长期研究的可持续性，并为未来的研究提供资金，研究和商业化。该学生将在新开设的210万英镑传感器启用自动化与控制中心（Sensor Enabled Automation & Control Hub，简称EHC）实验室工作，与超过35名研究人员和博士生组成的研究团队一起工作，同时还可以使用最先进的传感器，机器人和焊接设备。

The goal of the project is to investigate sensor-driven automation of high-integrity welding, based on ultrasonic volumetric data, to safely deliver high-quality welds right first time, every time, in challenging industrial environments. Traditionally, welding and inspection of high-integrity joints are separate, sequential, often manual processes in manufacturing and repair. Ultimately, these limitations reduce productivity, throughput, schedule certainty and increase rework if defects are detected at weld completion. As welding is a dynamic volumetric process, fusing joints of depth and width, this project seeks to exploit the volumetric imaging capability of ultrasonics, and introduce this inspection modality directly into the welding process control loop. By investigating robotic in-process ultrasonic inspection and control, this project aims to deliver high-integrity welds right, first time, every time and overcome current technical and process limitations.In-process ultrasonic-enabled welding control aims to offer significant reductions, estimated from current operational data of:- > 55% in weld process time- > 50% in overall weld cost- > 75% in man hoursThese significant technical, commercial and safety benefits underpin long-term research sustainability and empower research for future funding, research and commercialisation. The student will be based in the newly opened £2.1M Sensor Enabled Automation & Control Hub (SEARCH) Laboratory, working alongside a research team of over 35 researchers and PhD Students, while also having access to state of the art sensor, robotic and welding equipment.