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基于多传感器数据融合的Czochralski晶体生长中播种温度的检测方法
Lei Jiang1,2, Tongda Chang2, Ding Liu1,2
1School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
这项研究引入了一种新的方法,通过分析播种时间来评估晶体播种温度. 开发的多式融合网络准确量化温度,提高了半导体制造中的晶体质量和产量.
科学领域:
- 材料科学与工程 材料科学与工程
- 半导体制造业 半导体制造业
背景情况:
- 对于生产电力电子等级的晶体而言,Czochralski方法至关重要.
- 在播种阶段精确控制固体-液体接口温度对于晶体质量和产量至关重要.
- 直接测量固体-液体接口温度是不可能的,目前的手动方法缺乏定量评估.
研究的目的:
- 开发一种定量方法来评估晶体生长中的播种阶段温度.
- 为了解决直接温度测量和手动视觉检查的局限性.
- 通过确保适当的初始播种温度来提高晶体质量和生产产量.
主要方法:
- 建议使用播种阶段的持续时间作为温度评估的代理.
- 开发了一种改进的多式联通融合回归网络,集成了 pyrometer 数据和阴道特征.
- 采用波波变换用于时间频率分析,多模式特征融合 (MFF),通道注意力 (CA) 和空间注意力 (SA),使用随机向量功能链路网络 (RVFLN) 进行预测.
主要成果:
- 成功确定了多传感器数据与播种温度之间的间接定量关系.
- 与以前的方法相比,拟议的模型显示出更高的检测性能.
- 功能提取策略得到了验证,证实了它们的有效性.
结论:
- 开发的多式融合网络提供了一种有效的间接方法,用于在晶体播种过程中量化固体液体接口温度.
- 这种方法增强了对初始播种温度的控制,从而导致半导体晶体质量和生产产量的潜在改善.
- 该研究强调了使用时间频率表示和注意力机制在材料处理中复杂的传感器数据融合的有效性.
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