01
Process Design and Qualification
We build welding data and knowledge platforms, intelligent WPS design methods, and digital workshop tools for traceable process qualification.
Beijing Institute of Technology · AI Weld Defect Inspection
AI Weld Defect Inspection
We develop AI-enabled welding, arc additive manufacturing, simulation, and radiographic inspection technologies for high-end equipment manufacturing.
研究技术链
从工艺知识到工业验证
- 01工艺与材料Process & Materials
- 02多源感知Multimodal Sensing
- 03机理与仿真Physics & Simulation
- 04AI 识别与决策AI Decision
- 05设备与工业验证Equipment & Validation
跨越北京、重庆与珠海校区的协同研究与研究生培养
Research Profile
Research Base for AI-Empowered Welding
Intelligent welding in production environments depends on process knowledge, standardized data flows, sensing systems, simulation models, and engineering validation across equipment and materials.
90+
Published Papers
50+
Filed Patents
20+
Research Projects
1934
Google Scholar Citations
数据更新于 2026-05-28
Data-Driven Research
AI for Welding and Arc Additive Manufacturing
Led by Prof. Xinghua Yu at Beijing Institute of Technology, the Intelligent Welding Lab focuses on AI-enabled welding and arc additive manufacturing. The group connects process design, intelligent robotic systems, WAAM control, multiscale simulation, and radiographic defect recognition.
Research and graduate training span Beijing, Chongqing, and Zhuhai. Together, the three sites support fundamental process research, engineering deployment, platform development, and industrial inspection applications.
Sense
Understand
Optimize
Deploy
Research
Six Technologies for Intelligent Welding
02
Intelligent Welding Systems
We develop robot control, path planning, process-parameter recommendation, and quality-improvement systems for flexible welding production.
03
WAAM and Remanufacturing
We study geometry monitoring, interlayer temperature control, anomaly tracking, and automated repair for wire-arc additive manufacturing.
04
Process and Quality Optimization
We narrow process windows and verify forming quality, metallurgical performance, and mechanical properties for new materials and components.
05
Multiscale Simulation
We use FEM, CFD, and phase-field methods to predict stress, distortion, weld-pool behavior, and solidification microstructure.
06
AI Weld-Defect Inspection
We develop radiographic image enhancement, defect recognition, intelligent grading, and industrial inspection systems.
Sites
Three-Site Team
Beijing Team
Led by Prof. Xinghua Yu, the Beijing team focuses on welding metallurgy, welding automation, additive manufacturing, intelligent inspection, and machine learning.
- Site Lead
- Prof. Xinghua Yu
- Focus
- Welding metallurgy, welding automation, additive manufacturing, intelligent inspection, machine learning
Institute of Arc Cognitive Manufacturing
At the BIT Chongqing Innovation Center, the Institute of Arc Cognitive Manufacturing is directed by Dr. Zhen Sun, with Yan Li serving as Deputy Director responsible for overall operations. Its work focuses on weld radiography, AI-assisted radiograph interpretation, intelligent welding, and arc additive manufacturing.
- Institute Leadership
- Dr. Zhen Sun, Director · Yan Li, Deputy Director (responsible for overall operations)
- Focus
- Weld radiography, deep-learning defect recognition, radiograph interpretation software, and inspection equipment
Zhuhai Campus Team
The Zhuhai Campus team conducts research through the Marine Science and Technology Domain at Beijing Institute of Technology. Dr. Xiangbo Liu works on arc additive manufacturing, multi-step finite-element simulation, and PINN-assisted prediction.
- Faculty
- Dr. Xiangbo Liu, Assistant Professor / Special Associate Researcher
- Focus
- Arc additive manufacturing, multi-step simulation, solidification microstructure, and PINN-assisted prediction
News
Latest News
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Magnetic-field-assisted TIG welding paper published
A collaborative paper on the effect of magnetic field orientation on bead formation and microstructure was published in Materials Letters.
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Review on X-ray welding defect recognition published
Lab members co-authored a comprehensive review of automated weld-defect recognition in the Journal of Manufacturing Processes.
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Attention mechanisms for welding defect detection
A paper in Expert Systems with Applications examined how different attention mechanisms affect welding-defect detection.
Selected Papers
Selected Publications
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Journal of Manufacturing Processes · 2025
A comprehensive review of welding defect recognition from X-ray images
X Wang, U Zscherpel, P Tripicchio, S D'Avella, B Zhang, J Wu, Z Liang, X Yu.
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Expert Systems with Applications · 2025
On the effect of the attention mechanism for automatic welding defects detection based on deep learning
X Wang, S D'Avella, Z Liang, B Zhang, J Wu, U Zscherpel, P Tripicchio, X Yu.
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Review · 2021
A review of wire arc additive manufacturing of titanium alloys
A highly cited review of wire-arc additive manufacturing of titanium components.