KEYWORDS: Microwave radiation, Electromagnetism, Thermodynamics, Magnetism, Finite element methods, Dielectrics, 3D modeling, Waveguides, Temperature metrology, Energy conversion efficiency
Uneven temperature distribution within the heated material is an important factor limiting the widespread use of microwave heating. This paper proposed a dynamic power regulation method to improve the uniformity of microwave heated materials. First, the microwave heating model was constructed by the finite element method (FEM), and the electromagnetic field model and temperature field model were solved to obtain the temperature distribution inside the heated material. Second, the effects of constant power heating methods and dynamic power heating were compared under the same conditions of total energy fed in. Finally, the simulation results showed that the dynamic power heating method was able to improve the uniformity in the horizontal and vertical sections by 69.1%-71.9% and 64.1%-71.8%, respectively, compared to the traditional constant power heating method. The energy conversion efficiency of the two heating methods was almost identical. These results showed that the dynamic power heating method can improve the uniformity of microwave heating and save energy.
The microwave source queue of high-power microwave heating system has only binary detection of whether there are running or not. Online real-time detection of the working status and changes of the microwave source queue is necessary in order to improve the economy and reliability of its queue. A fault detection method of microwave source queue in high power microwave heating system based on wavelet analysis is presented. Firstly, the fault of microwave source queue is judged according to the change of electric field intensity. Secondly, by acquiring the continuous wavelet transform of the input signal and output signal at multiple scales to calculate the residual signal generated by the extreme value, and the detection is completed according to the change of the residual signal. Finally, the wavelet time-frequency spectrum of the residual signal is drawn to obtain the feature information and perform visual analysis of the detection results. Three fault states of microwave source are simulated respectively, the effectiveness of the method is verified by simulation and result analysis. The continuous wavelet transform analysis method is used to detect the fault of the microwave source queue, which can accurately detect the fault location and time of microwave source queue online.
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