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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
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
- Kategorie
- Technik