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永磁直流电机电磁力的分析和参数预测

Analysis and Parameter Prediction of Electromechanical Force of Permanent Magnet Direct Current
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摘要 通过变量分析电机气隙中的电磁力得出电磁噪声的影响因素。首先对电机进行模态分析得出模态频率,然后运用Mawell2D对电机转子偏心、永磁体不同厚度等工况下进行静磁场分析,得出两者对电机气隙电磁力的影响,运用压电阻抗实验得出电机的模态频率验证模态仿真的结果,最后运用BP神经网络通过气隙电磁力实现对电机永磁体的厚度进行预测。结果表明避免转子偏心、适当微调永磁体的厚度,可以有效地减小径向电磁力;BP神经网络可以通过气隙电磁力实现对永磁体厚度的识别。 Through variable analysis of the electromagentic force in the motor airgap,the influencing factors of electromagnetic noise are obtained.The modal frequency of the motor was first obtained by modal analysis.Then,the static magnetic field was analyzed under the condition of motor rotor eccentricity and different thickness of permanent magnet by MAWELL2D,and the influence of the two on the electromagnetic force in the air gap of the motor was obtained.Piezoelectric impedance experiment was used to obtain the modal frequency of the motor to verify the results of modal simulation.Finally,BP neural network was used to predict the thickness of the permanent magnet of the motor through the air gap electromagnetic force.The results show that radial electromagnetic force can be effectively reduced by avoiding rotor eccentricity and adjusting the thickness of permanent magnet appropriately.The BP neural network can recognize the thickness of permanent magnet through the air gap electromagnetic force.
作者 张军 赵林玉 李健生 ZHANG Jun;ZHAO Lin-yu;LI Jian-sheng(School of Mechanical Engineering,Anhui University of Science and Technology,232001,Huainan,Anhui,China;School of Artificial Intelligence,Anhui University of Science and Technology,232001,Huainan,Anhui,China)
出处 《河北水利电力学院学报》 2022年第2期35-45,共11页 Journal of Hebei University Of Water Resources And Electric Engineering
基金 国家自然科学基金资助项目(51175005) 安徽省科技重大专项计划项目(16030901012)。
关键词 径向电磁力 电磁噪声 BP神经网络 永磁电机 压电阻抗 radial electromagnetic force modal analysis electromagnetic noise BP neural network permanent magnet motor piezoelectric impedance
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