Prediction of Temperature in Vacuum Arc Remelting in the Presence of Strong Disturbances |
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| Affiliation: | 1. State Key Laboratory of Advanced Welding and Joining, Harbin Institute of Technology, Harbin 150001, China;2. National Engineering and Research Center for Commercial Aircraft Manufacturing, Commercial Aircraft Corporation of China, Ltd., Shanghai 200436, China;1. Department of Mechanical Engineering, Sri Krishna College of Technology, Coimbatore 641042, India;2. Department of Mechatronics Engineering, Park College of Engineering and Technology, Coimbatore 641659, India;1. College of Materials Science and Engineering, Hunan University, Changsha 410082, China;2. Institute of Aluminum Alloy, Beijing Institute of Aeronautical Materials, Beijing 100095, China;3. Beijing Engineering Research Center of Advanced Aluminum Alloys and Applications, Beijing Institute of Aeronautical Materials, Beijing 100095, China |
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| Abstract: | A system for predictive, noninvasive temperature measurement in a broad class of manufacturing processes is presented. The system employs a comprehensive, three-tier signal processing algorithm to achieve high accuracy and reliability in the presence of strong disturbances. Temperature estimates are generated by ‘unstructured, shallow knowledge’ based algorithms. The estimation process employs a set of robust features obtained by signal processing that involves constitutive models representing ‘deep knowledge’ about the process dealt with. The application of these models is combined with ‘structured, shallow knowledge’ based techniques. Results obtained in application to the investment casting of titanium, which employs the vacuum arc remelting (VAR) process, are presented. |
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