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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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2.2. StructureofHEPHAISTOS Inprinciple, themetallicmeshisdesignedtoblockthemicrowaveand keepthesafetyoftheinfraredcamera. Butduringtheheatingprocess, this mesh absorbs parts of the infrared signals from the workpiece, and meanwhile it also emits a certain amount of infrared signals. The infrared signals received by the infrared camera are partly from the workpiece and partly from the mesh itself. As a result, the tempera- turedirectlymeasuredbytheinfraredcameraisdifferentfromthereal temperature of the workpiece. This difference is proportional to the temperature difference between the workpiece and the mesh. There- forewhentheworkpieceisheatedtoahightemperatureandthemesh stays cool, the temperature values measured by the infrared camera will be significantly differ from the real temperatures. In order to get theaccurate temperaturemeasurements, this influencehas tobecom- pensated. According to the above principles, the mesh can be considered as an infrared window [Gru03]. Once the emissivity of the workpiece, the transmittanceofthemeshandthetemperatureofthemeshareknown, the measured temperature can be compensated using the method as described in [Mad04]. In HEPHAISTOS, the compensation functions are included and applied using the FLIR ThermoVision LabVIEW Tool-kit [fli]. 0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 2 0 4 0 6 0 8 0 1 0 0 T i m e ( s ) T 1 b y F O ST 2 b y F O ST 3 b y F O ST 1 b y I R CT 2 b y I R CT 3 b y I R C M i s m a t c h e d r e g i o n 0 2 0 4 0 6 0 8 0 1 0 0T o t a l P o w e r (a) 35
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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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Technik
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources