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Dynamic Position Detection Method for Large-diameter Rotary Shaft Based on MIFA-AFKF

机译:基于MiFA-AFKF的大直径旋转轴动态位置检测方法

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The dynamic position variables of large-diameter rotary shaft are not easy to measure precisely or cheaply, however, the accuracy of dynamic position is of great significance to the movement controlling of key rotary shaft. In this paper, a novel real-time detection method is presented, which can be used to estimate the dynamic position of the large-diameter rotary shaft rotating with constant velocity, constant acceleration or variable acceleration. In order to estimate the position variables, multi-sensor information fusion algorithm based on adaptive fading Kalman filter (MIFA-AFKF), which combines conventional information fusion algorithm with an adaptive fading factor, is proposed to fuse multi grating-sensor information. The method based on MIFA-AFKF is demonstrated by Monte Carlo simulation, and also used to measure the angle position of the hollow shaft at the machine head and machine tail of a horizontal riveting machine. The two results show that the algorithm can significantly improve the dynamic position accuracy.
机译:大直径旋转轴的动态位置变量不容易测量或便宜地测量,然而,动态位置的准确性对关键旋转轴的运动控制具有重要意义。本文提出了一种新的实时检测方法,其可用于估计具有恒定速度,恒定加速度或可变加速度的大直径旋转轴的动态位置。为了估计位置变量,基于自适应衰落的卡尔曼滤波器(MiFA-AFKF)的多传感器信息融合算法,其将传统信息融合算法与自适应衰落因子组合起来,以熔化多光栅传感器信息。基于MiFA-AFKF的方法由Monte Carlo仿真证明,并且还用于测量空心轴在水平铆接机的机器头部和机尾的角度位置。这两个结果表明,该算法可以显着提高动态位置精度。

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