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《Transactions of China Electrotechnical Society》 2007-01
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Optimization of the Electromagnetic System of Contactor by Neural Network

Liu Guojin Lu Jianguo Su Xiuping Zhao Jingying (Hebei University of Technology Tianjin 300130 China)  
The electromagnetic system decides the size of contactors. So the size of electromagnetic system is often considered as optimization aim. However, the optimization of electromagnetic system is usually involved in the intricate electromagnetic computation. So in this paper, the electromagnetic system of contactor is optimized by neural network which has greatly nonlinear convergence and high efficient parallel computation. The three-layer forward network applies the improved BP arithmetic, in which the coil currents and attraction forces at four sport places of spring force are inputs nodes, the sizes of structure are output nodes and five nodes at layer 2 and layer 3. The neural network is trained by the CJX1 contactor in variational step. Once the train of neural network is finished, the size of electromagnetic system can be optimized quickly without the intricate electromagetic field computation. After optimization, the sizes of a contactor are reduced greatly.
【CateGory Index】: TM572
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