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RISS 인기검색어
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- 저자 : Lilong Cai (검색결과 2 건)
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Zhou, Kang,Cai, Lilong The Korean Institute of Power Electronics 2015 JOURNAL OF POWER ELECTRONICS Vol.15 No.4
In this paper, an algorithm based on a model analysis of the online calculation of the root-mean-square (RMS) value of welding current for single-phase AC resistance spot welding (RSW) was developed. The current is highly nonlinear and typically non-sinusoidal, which makes the measuring and controlling actions difficult. Though some previous methods focused on this issue, they were so complex that they could not be effectively used in general cases. The electrical model of a single-phase AC RSW was analyzed, and then an algorithm for online calculation of the RMS value of the welding current was presented. The description includes two parts, a model-dependent part and a model-independent part. Using a previous work about online measurement of the power factor angle, the first part can be solved. For the second part, although the solution of the governing equation can be directly obtained, a lot of CPU time must be consumed due to the fact that it involves a lot of complex calculations. Therefore, a neural network was employed to simplify the calculations. Finally, experimental results and a corresponding analysis showed that the proposed algorithm can obtain the RMS values with a high precision while consuming less time when compared to directly solving the equations.
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Kang Zhou,Lilong Cai 전력전자학회 2015 JOURNAL OF POWER ELECTRONICS Vol.15 No.4
In this paper, an algorithm based on a model analysis of the online calculation of the root-mean-square (RMS) value of welding current for single-phase AC resistance spot welding (RSW) was developed. The current is highly nonlinear and typically non-sinusoidal, which makes the measuring and controlling actions difficult. Though some previous methods focused on this issue, they were so complex that they could not be effectively used in general cases. The electrical model of a single-phase AC RSW was analyzed, and then an algorithm for online calculation of the RMS value of the welding current was presented. The description includes two parts, a model-dependent part and a model-independent part. Using a previous work about online measurement of the power factor angle, the first part can be solved. For the second part, although the solution of the governing equation can be directly obtained, a lot of CPU time must be consumed due to the fact that it involves a lot of complex calculations. Therefore, a neural network was employed to simplify the calculations. Finally, experimental results and a corresponding analysis showed that the proposed algorithm can obtain the RMS values with a high precision while consuming less time when compared to directly solving the equations.
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