Temperature Field Optimization for Multi-Microwave Sources Based on Collaborative Switching under Uncertain Communication
Source abstract
Abstract
The multi-microwave sources reactor can significantly reduce energy consumption and processing time with broad application prospects in industrial processing. In order to optimize the temperature field of materials, this paper proposes the heating strategy of multi-microwave sources based on collaborative switching, particularly in distributed combined heat source networks with poor communication conditions. Firstly, simplifying system control variables to enhance the design of the microwave intelligent agent system, and optimizing the time-frequency characteristics of combined power output from multi-microwave sources to emphasize the process of energy partition. Meanwhile, an event-triggered strategy reduces communication frequency and energy consumption between agents. Secondly, a fixed positive lower limit τmin is used in event-triggered to avoid Zeno behavior caused by DoS attacks. Finally, The finite element method was used with the time domain for thermal analysis. The simulation results of SiC show that the energy utilization efficiency of microwave heating equipment is increased by 4.3∼10.7%, temperature uniformity is improved by 25.6∼43.6%, and the results of the potato experiment simulation showed that the multi-microwave source collaborative switching heating strategy can effectively optimize the temperature field distribution of the material.
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Research context
OpenAlex topics: Microwave-Assisted Synthesis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Key Laboratory of Unconventional Metallurgy of Ministry of Education, Kunming University of Science and Technology, Kunming 650093, China
Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming 650500, China
The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, Kunming 650500, China
Funding
National Natural Science Foundation of China
References (29)
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