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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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1. Introduction 1.2.2. Numericalsimulations Numerical simulation is preferred for more complicated scenarios where analytical solutions are not feasible. The idea of numerical simulation is to separate the original problem into a number of small parts, solve different parts individually and finally merge results of all small parts into the solution of the original problem. During the last 20 years, the rapid development of powerful computers has led to more and more implementations of numerical analysis for solving complex electrodynamics problems. Common numerical simulation methods used for modeling microwave heating scenarios consist of the finite-difference time-domain (FDTD) method, the finite-volume time-domain (FVTD) method, the finite element method (FEM), the method of moments (MoM), as well as the transmission line matrix (TLM) method. Detailed introductions of above methods exceed the scope of this dissertation, and they can be found in a large number of booksandpaperssuchas [KL93] [LNS04] [DLT12] [Chr05]. Numerical simulation is used not to directly control the microwave heating, but to help improve the heating homogeneity. The principle is to firstly use numerical techniques to simulate and estimate the EM field as well as the temperature distributions within the microwave cavity, and then to optimize the heating homogeneity according to the simulation results using some auxiliary approaches. For example, in [CZ05] and [SCV+10], FDTD methods were used to simulate tem- peratureprofilesofmicrowaveheating inone-dimensionalandthree- dimensional scenarios, and the thermal runaway phenomenon can be prevented based on the simulation. In [GRD07] FEM was applied to estimate the temperature distribution of the food within the mi- crowave oven in case of a rotating turntable. Afterwards the rotating speedandtimeoftheturntablecanbeoptimizedbasedonthesimula- tionresults. Hence, theoverall temperatureuniformitywasenhanced. Similarly, the influences of mode stirrers to the EM field distribution were simulated using FEM in [PGMCCCSH04]. The angle of mode stirrers was determined with the help of simulation results and the temperature distribution was also improved. More examples of us- ing numerical simulations to improve the performance of microwave heatingcanbefoundin[PS91] [FR93] [YG04] [GY07] [HM96]. 8
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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