融合大语言模型与结构化模型的工艺参数优化诊断方法
By integrating large language models and structured models to optimize process parameters for diagnostic methods, the problem of insufficient defect identification accuracy and interactivity in welding quality inspection systems has been solved. This has resulted in a high-precision, interpretable, and user-friendly intelligent diagnostic system suitable for multi-parameter driven welding defect identification and human-computer interactive intelligent diagnostic scenarios.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENYANG INST OF COMPUTING TECH CO LTD THE CHINESE ACAD OF SCI
- Filing Date
- 2025-06-25
- Publication Date
- 2026-07-17
AI Technical Summary
Existing welding quality inspection systems are inadequate in terms of defect identification accuracy, reasoning ability, semantic understanding, and interactive capabilities, making it difficult to meet the industrial application needs under complex working conditions and high-quality standards.
A process parameter optimization diagnostic method that integrates large language models and structured models achieves deep collaboration between structured data and language models through a prompt alignment mechanism and function call framework, supporting multi-task closed-loop reasoning such as defect identification, cause analysis, and parameter optimization suggestions.
It improves the accuracy of welding defect identification, enhances the system's semantic reasoning and human-computer interaction capabilities, and has good interpretability and scalability, making it suitable for various industrial welding quality assessment and intelligent decision-making scenarios.
Smart Images
Figure CN120805035B_ABST