Non-Invasive Temperature Estimation and Control in Titanium Casting

钛铸造中的非侵入式温度估算和控制

• 批准号: 9908378
• 负责人: Slawomir Spiewak
• 金额: $ 8万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-10-01 至 2002-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9908378&HistoricalAwards=false
• 关键词: Non; Invasive; Temperature; Estimation; Control

This project is to develop an accurate, non-invasive method for the estimation of molten titanium temperature in the Vacuum Arc Remelted (VAR) casting process; and, a control strategy to assure target pour temperatures by adjusting arc parameters (voltage and gap) and the pour initiation instance. The estimation and control algorithms will employ a constitutive-empirical model of thermal energy conservation in the VAR process. This model will be continuously updated by analyzing in-process measured signals, such as the arc power, or temperature and flow of water that cools the crucible and electrode gripper. In particular, the actual temperature of the melt flowing over the crucible lip will be measured during each pour by infrared pyrometers to close the feedback loop in the estimation procedure and assure accurate temperature prediction for the next execution of the process. On-line identification of crucial physical properties, such as the thermal resistance between the melt and cooling water, will facilitate predictive control of the arc power to accomplish target pour temperatures despite strong disturbances present in the process. A prototype system will be developed and implemented in a plant that manufactures titanium castings for aviation, defense, space exploration and medical applications. This project should produce the prototype of a non-invasive temperature estimation and control system valuable to quality control in titanium casting. The developed algorithms and system architecture may be applicable to other high performance casting processes as well.

本项目旨在开发一种准确、无创的方法来估算真空电弧重熔（VAR）铸造过程中的熔融钛温度；通过调节电弧参数（电压、间隙）和电弧起爆点，提出了一种控制电弧浇注温度的策略。估计和控制算法将采用VAR过程中热能守恒的本构-经验模型。该模型将通过分析过程中测量的信号，如电弧功率，或冷却坩埚和电极夹具的温度和水流，不断更新。特别是，在每次浇注过程中，将通过红外高温计测量流过坩埚唇的熔体的实际温度，以关闭估计过程中的反馈回路，并确保准确的温度预测。在线识别关键的物理性质，如熔体和冷却水之间的热阻，将有助于电弧功率的预测控制，以实现目标浇注温度，尽管在过程中存在强烈的干扰。原型系统将在一家制造航空、国防、太空探索和医疗应用的钛铸件的工厂中开发和实施。该项目将产生一个对钛铸件质量控制有价值的无创温度估计和控制系统的原型。所开发的算法和系统架构也可应用于其他高性能铸造工艺。