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2. IntroductionofHEPHAISTOS
2 0 3 0 4 0 5 0 6 0 7 0 8 0 9
02
0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
T
1T
2T
3
T e m p e r a t u r e m e a s u r e d b y F O S ( ° C )
M i s m a t c h e d r e g i o n
(b)
Figure2.18. TemperaturecomparisonbetweenFOSandIRC(aftercompensa-
tion).
After the compensation, the temperature measured by the infrared
camera is further verified. Temperatures of three different locations
onthesurfaceofaworkpieceweremeasuredbybothfiberopticesen-
sors and the infrared camera. The corresponding temperature curves
andfittingresultsareshowninfigure 2.18.
Fromtheresult infigure 2.18, it isclearthatafterthecompensationthe
temperaturesmeasuredbytheinfraredcameraareclosetothetemper-
atures measured by the fiber optic sensors. The differences between
them are limited within±2◦C except the mismatched region, which
is labeled in both figures in 2.18. This region is caused by the fact
that when the temperatures have large changes (see figure 2.18a), the
response of the infrared camera is much faster than the response of
fiber optic sensors. In other words, this mismatched region is gener-
ated because of the time delay of fiber optic sensors. Due to the fast
andaccurate temperaturemeasurementresults, the infraredcamerais
mainlyusedin the followingexperiments.
36
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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
- Category
- Technik