人工智能驱动的合金增材制造智能参数优化方法和装置
By determining the influence coefficients of alloy parameters based on crack prediction expressions and optimizing alloy parameters, the problem of crack defects in alloy preparation was solved, achieving efficient and accurate parameter adjustment and improving alloy yield and performance stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- RESEARCH INSTITUTE OF ADVANCED MATERIALS (SHENZHEN) CO LTD
- Filing Date
- 2026-05-19
- Publication Date
- 2026-07-17
AI Technical Summary
In the alloy preparation process, existing technologies cannot avoid crack defects by using neural networks to back-engineer alloy parameters. This leads to blind parameter adjustments, numerous iterations, high costs, long cycles, and difficulty in meeting the conditions for crack-free synthesis.
Based on the preset alloy parameters and crack prediction expression, the influence coefficient of each sub-parameter on the crack prediction result is determined. By adjusting the target sub-parameters with high influence coefficients, the alloy parameters are optimized until the synthesis conditions are met, and the alloy is prepared.
Precise and efficient optimization of alloy parameters was achieved, which reduced the crack defect rate and improved the success rate of alloy preparation and the stability of material properties.
Smart Images
Figure CN122224381B_ABST