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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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2.2. StructureofHEPHAISTOS The remote control interface functions like a transfer station. It re- ceives different types of data, including the temperature values, pre- diction length (used in MPC) and other required information, from the LabVIEW control interface, and send them to the MATLAB con- trol system. After thenewcontrol input iscalculatedbytheMATLAB control system, the remote interface picks it up and further sends it to the LabVIEW control interface. The communication between the re- mote interfaceandtheLabVIEWcontrol interface isdonethroughthe TCP/IPprotocol. 2.2.3. TemperatureMeasurementApproaches In HEPHAISTOS, there are three different temperature measurement approaches, including the thermocouple, fiber optic sensor and in- frared camera. The infrared camera is put right above the metallic table,whichisusedtoget thewhole temperatureprofileof theheated workpiece during the heating process. Both thermocouples and fiber optic sensors can be fixed at any locations using microwave transpar- enttapes, tomeasurethesurfacetemperatureoftheworkpiece. Differenttemperaturemeasurementapproacheshavedifferentperfor- mance in practical experiments. For thermocouples, their presence in the microwave cavity significantly influence the EM field, lead- ing to thermal instability and microwave breakdown [PCB+01]. Even shielded with aluminium or copper backed tape, the shielding itself will be heated which also affects the measurement accuracy of ther- mocouples. Compared with thermocouples, the fiber optic sensor is much more convenient that can be directly used without any shield- ing or other processing. But the main problem is its large time delay duringthe temperaturemeasurement. The figure 2.17 demonstrates the time delay occurred in temperature measurement using fiber optic sensors. After the microwave sources are switched on, the temperatures measured by fiber optic sensors stayed constant for quite a period. The time between switching on heating power and temperature changes is around 8 s to 10 s. What is even worse is that this time delay value is not fixed. It differs from time to time and from sensor to sensor. This time delay brings extra 33
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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