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Finite element modelling of a field-sensed magnetic suspended system for accurate proximity measurement based on a sensor fusion algorithm with Unscented Kalman Filter

机译:基于Unscented卡尔曼滤波传感器融合算法的场感磁悬浮系统有限元建模精确接近测量

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摘要

The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.
机译:本文介绍了一种用于磁场感应磁悬浮系统的精确距离测量。接近度测量基于霍尔效应传感器。接近传感器直接安装在电磁体的下表面,这意味着它对外部磁影响和干扰非常敏感。外部干扰会干扰信息信号,并降低接近度测量的可用性和可靠性,并因此降低整个应用程序的操作。由于上述原因,部署了传感器融合算法。传感器融合算法基于Unscented Kalman滤波器,其中使用有限元建模方法导出了非线性动态模型。这种建模的优点是可以更准确地估算动态模型参数,尤其是在已知实时应用程序的实际结构,材料和尺寸的情况下。本文的新颖之处在于紧凑型电磁致动器的设计,该致动器具有内置的低成本接近传感器,可精确测量磁性物体。本文依次介绍了有限元方法的建模过程,无味卡尔曼滤波器的传感器融合算法的设计和参数设置,最后给出了实时操作的实现过程和结果。

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