The idea of measurement standard transformation is presented to analyze precision displacement measurement problems. Time series theory and space series theory are established based on the displacement measurement models of time grating sensors and optical grating sensors. Non-stationary time varying series can be transformed into stationary ones with wavelet decomposition technology.Based on the state variables of the system, the characteristics of high precision dynamic measurement signals can be identifyed to establish adaptive models for decomposed series respectively, and the future value of original series can be deduced from all deduced value of decomposed series with wavelet reconstruction technology. Therefore, the a general signal interpolation method and corresponding interpolation error correction methods are obtained for time grating sensors, optical grating sensors and some other displacement sensors developed with equal spatical division technology. Compared to some other interpolation techniques, the proposed interpolation method is independent of the high requirements on the quality of original sensor signal waves and hardware circuits, but depend on the sensors' precision and recursive algorithm precision. In addition, the proposed signal interpolation methods are suitable for both angular displacement measurements and linear displacemement measurements, which have the important general significances.
本项目提出采用测量基准转换的思维方式去分析精密位移测量问题,根据时栅和光栅位移测量模型构建时间序列理论和空间序列理论,采用小波技术将非平稳时变位移序列分解成平稳位移序列,基于各运动状态变量采用精密动态测量信号的特征辨识完成自适应递推算法,通过对各序列建模递推与合成,实现适用于时栅、光栅及其他基于等空间刻划原理位移传感器通用的信号细分技术,以及相关细分误差实时修正技术。该方法突破现有细分方法对位移传感器信号波形质量和硬件电路的高要求,细分精度只与传感器本身精度和递推算法精度有关。此细分方法不仅适用于传感器角位移信号细分,同时也适用于传感器直线位移的信号细分,具有重要的普遍性意义。
为了解决高精度数控装备对位移传感器高分辨力的反馈需求,提出采用测量基准转换的思维方式去解析精密位移测量问题。根据时栅和光栅位移测量模型,采用小波技术实现传感器在复杂组合运动条件下的精密位移信号多尺度分解的特征辨识,建立精密位移测量信号在动态和微观角度下的空间量和时间量的对应关系。通过采用时间序列和灰度理论研究在估计误差最小化原则条件下的各分量位移信号细分的自适应回归模型建模、参数寻优以及相关细分误差实时修正技术。实验结果证明直线式时栅在76.604mm测量范围内转换成增量式脉冲信号测量精度在±2μm,圆式时栅运动位移信号细分误差为-1.26″~1.3″,HEIDENHAIN圆光栅ROD880位移信号细分误差为±1.8″。该方法突破现有细分方法对位移传感器信号波形质量和硬件电路的高要求,细分精度只与传感器本身精度和递推算法精度有关。此细分方法不仅适用于传感器角位移信号细分,同时也适用于传感器直线位移的信号细分,具有重要的普遍性意义。
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数据更新时间:2023-05-31
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