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<p>Complex electromagnetic environments can cause a large amount of high-frequency noise in the rotor displacement signals of active magnetic bearings (AMBs), and the support accuracy of the system can be degraded. The steady state Kalman filter (SSKF) can effectively suppress the high-frequency noise of the system. Compared with the traditional Kalman filter algorithm, it has the advantage of occupying fewer hardware resources. In this paper, based on a one degree of freedom AMB system model, a high-frequency noise suppression method for an AMB using the SSKF has been carried out. Firstly, based on the mathematical model of magnetic bearing, the transfer function of SSKF is obtained, and then the influence of SSKF on the AMB system is analyzed by using the frequency domain analysis method. In addition, an optimal selection method for SSKF variance is also proposed. The experimental results show the effect of SSKF on the dynamic characteristics of AMB and the effectiveness of the optimization method.</p>

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High-frequency noise suppression method for active magnetic bearings using the steady state Kalman filter

  • 期刊论文

  • 发表日期：

    2025年5月7日

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  • Shouding Xu,
  • Zhenzhong Su,
  • Hao Jiang,
  • Zicheng Liu

摘要

Complex electromagnetic environments can cause a large amount of high-frequency noise in the rotor displacement signals of active magnetic bearings (AMBs), and the support accuracy of the system can be degraded. The steady state Kalman filter (SSKF) can effectively suppress the high-frequency noise of the system. Compared with the traditional Kalman filter algorithm, it has the advantage of occupying fewer hardware resources. In this paper, based on a one degree of freedom AMB system model, a high-frequency noise suppression method for an AMB using the SSKF has been carried out. Firstly, based on the mathematical model of magnetic bearing, the transfer function of SSKF is obtained, and then the influence of SSKF on the AMB system is analyzed by using the frequency domain analysis method. In addition, an optimal selection method for SSKF variance is also proposed. The experimental results show the effect of SSKF on the dynamic characteristics of AMB and the effectiveness of the optimization method.