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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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2. IntroductionofHEPHAISTOS close tof0 forheating. Fordifferentdielectricmaterials, thefrequency f0 is different. Many dielectric materials havef0 locating between 0.8 GHz∼3 GHz, and that is why the frequencies for industrial heating are915MHzand2.45GHz. Besidesdipolerelaxation, there isanotherheatgenerationmechanism ofmicrowaveheating: ionicconduction. Ionicconductionisthemove- ment of free ions or ionic species under the influence of external elec- tric field, within a solid (such as structurally disordered crystalline solids) or aqueous solutions (such as solution of salts) [Tul07]. It is essentially similar with the electronic conduction of conductors, ex- cept the moving particles are ions instead of electrons. The energy is transformed from the electric field to the material and an amount of heat is generated. The ionic conduction loss is characterized by an equivalent dielectric conductivityσd, and the corresponding heating powerdensitycanberepresentedas [Met96] pc= 1 2 σd ∥∥∥−→E∥∥∥2 (2.5) Combining above two loss mechanisms, the overall microwave heat- ingpowerdensity isexpressedas [Met96] pmw=pd+pc= 1 2 σe(ω,T) ∥∥∥−→E∥∥∥2 , σe(ω,T) :=σd+ωε0ε ′′(ω,T), (2.6) whereσe(ω,T) is the effective electrical conductivity. The total effec- tive loss factor isdefinedas [Met96] ε′′e(ω,T) := σe(ω,T) ωε0 = σd ωε0 +ε′′(ω,T), (2.7) which represents the microwave energy absorbing ability of a dielec- tric material. The effective loss factor for fixed temperature is shown in figure 2.4, which gives a clear impression about the influences of different loss mechanism at different frequencies. In this disser- tation, the effective electrical conductivityσe(ω,T) is considered as a parameterσe(T) that relies on only the temperatureT. Because it is assumed in the dissertation that the microwave frequency is fixed at 2.45GHz. 20
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Title
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Author
Yiming Sun
Publisher
KIT Scientific Publishing
Location
Karlsruhe
Date
2016
Language
English
License
CC BY-SA 3.0
ISBN
978-3-7315-0467-2
Size
14.8 x 21.0 cm
Pages
260
Keywords
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