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An improved fourier eight-sensor (F8S) method for separating straightness, yawing and rolling errors of a linear slide

机译:一种改进的傅立叶八传感器(F8S)方法,用于分离线性滑块的直线度,偏航和滚动误差

摘要

This paper proposes an improved Fourier eight-sensor (F8S) measurement method for separating the straightness, yawing and rolling motion errors as well as determining the profile of a linear slide. The previous F8S method [1] used the constant parameters C2 and C4 to estimate the profile function f1 (θ) in different angle ranges and f2 (θ) is also computed with the same fused sensor data. By constant parameters, the profile estimation and error separation are implemented via iterative method which is a time-consuming procedure and can not maintain the acceptable accuracy. Here, the improved F8S method applies the matrix technique instead of the iterative method to estimate the profile functions by three distinct sets of C2 and C4 parameters and different fused sensor data according to the linear slide motion within different angle ranges. Furthermore various errors can be separated through simple equations based on the calculated profile functions. In the second part of this paper the uncertainty induced by the sensor reading error is analyzed in both frequency and spatial domains, and the uncertainty for the profile function can also be obtained. The simulation results confirm that the improved F8S method provides better performance and effectiveness, and is more feasible than the previous F8S method [1].
机译:本文提出了一种改进的傅立叶八传感器(F8S)测量方法,用于分离直线度,偏航和滚动运动误差以及确定线性滑轨的轮廓。先前的F8S方法[1]使用常数参数C2和C4来估计不同角度范围内的轮廓函数f1(θ),并且还使用相同的融合传感器数据来计算f2(θ)。通过恒定的参数,轮廓估计和误差分离是通过迭代方法实现的,这是一个耗时的过程,并且不能保持可接受的精度。在这里,改进的F8S方法应用矩阵技术而非迭代方法,以根据不同角度范围内的线性滑动运动,通过三组不同的C2和C4参数以及不同的融合传感器数据来估计轮廓函数。此外,可以基于计算的轮廓函数通过简单的方程式分离各种误差。在本文的第二部分中,在频域和空间域中分析了由传感器读取误差引起的不确定性,并且还可以获得轮廓函数的不确定性。仿真结果表明,改进的F8S方法具有更好的性能和有效性,比以前的F8S方法更可行[1]。

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