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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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1.2. Overviewof theStateof theArt Numerical simulation is the most important tool to analyze the EM field and temperature distributions of microwave heating, which is flexible and powerful to deal with different kinds of microwave heat- ing problems. It provides important and valuable foundations to op- timize the design and setup of the microwave heating system. Nev- ertheless, it is still not a direct and efficient way to improve the tem- perature homogeneity. On the one hand, the real EM and tempera- ture distributions are affected by multiple factors, including dielectric properties of the heated product, the position of the heated product, the resonant microwave frequency range, and the air flow rate within themicrowavecavity. Anylittlemismatchof these influencingfactors will cause that the simulation result dramatically differs from the real heating result. Therefore, the more variables a problem has, the less accurate the simulation result is. That is also why in many problems with highly complex heating scenarios, the simulated results are far fromsatisfactory. On the other hand, for certain highly complex systems (such as the HEPHAISTOSsystemusedinthisdissertation), eventhoughthesim- ulationresultsareaccurate, there isnosophisticatedguidelineofhow to improve the final temperature distributions based on correspond- ingsimulationresults. For instance, ifa localhotspot is foundinboth the simulated and real temperature distributions, great efforts have to be done to eliminate this hot spot without creating new hot spots, due to the fact that any small modifications of the heating setup or equipmentarepossibletocauseunexpectedimpacts totheentiretem- peraturedistribution. 1.2.3. Otherauxiliaryapproaches Besides the modern control method and the numerical simulation ap- proach, there are other auxiliary approaches that aim to improve the temperature homogeneity under microwave heating. They can be divided into two categories. The first category comprises methods that focusing on creating a more homogeneous EM field distribution, whichcorrespondinglyleadstoahomogeneoustemperaturedistribu- tion (for homogeneous workpieces). For example, the idea of vari- able frequency microwave heating was used in both [LBC+95] and 9
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Titel
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Autor
Yiming Sun
Verlag
KIT Scientific Publishing
Ort
Karlsruhe
Datum
2016
Sprache
englisch
Lizenz
CC BY-SA 3.0
ISBN
978-3-7315-0467-2
Abmessungen
14.8 x 21.0 cm
Seiten
260
Schlagwörter
Mikrowellenerwärmung, Mehrgrößenregelung, Modellprädiktive Regelung, Künstliches neuronales Netz, Bestärkendes Lernenmicrowave heating, multiple-input multiple-output (MIMO), model predictive control (MPC), neural network, reinforcement learning
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources