Adaptive compensation for positioning error of precision measurement platform
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摘要: 为了实现光学元件精密检测平台定位误差的自适应补偿,以保证在不同的检测环境中平台能够自行保持高精度,提出了基于检测环境监测和支持向量回归机的定位误差自适应补偿方法。首先,以多组检测环境中温度、湿度和气压的具体测量值作为训练数据,利用支持向量回归机建立定位误差最大值的预测模型,进行最大值预测。然后,将最大值同温度、湿度、气压等环境因素和位置信息一起作为训练数据,迭代使用支持向量回归机,建立任意位置定位误差预测模型。最后,将预测到的定位误差值传入检测平台控制器中进行补偿。应用雷尼绍激光干涉仪,温度、湿度和气压传感器等仪器设备,在光学元件精密检测平台上进行了具体实验。实验结果表明该技术切实可行,预测数据与实测数据差值绝对值的平均值为0.88 m,Pearson相关系数的平方为0.99,自适应补偿后平均定位误差由43 m降为1.4 m。Abstract: In order to realize adaptive compensation for positioning error of precision measurement platform, a new method has been proposed based on monitoring measurement environment and support vector regression for ensuring the high-precision of measurement platform used for optical element in different measurement environment. Firstly, a prediction model was established with the theory of support vector regression (SVR), using several group data of temperature, humidity, atmospheric pressure in different environment for predicting the maximum positioning error value. Then SVR was used iteratively to predict the positioning error value of any position, using both maximum positioning error value and environmental factors. Finally, the positioning error was input to the controller for compensation. Instruments including Renishaw laser interferometer along with temperature and humidity sensors were applied to experiments with the precision measurement platform. Experimental results indicate that, comparing the prediction data with the measured data, the average of the absolute difference is 0.88 m, and the Pearsons square of correlation coefficient is 0.99. After adaptive compensation, the average of positioning error decreases to 1.4 m from 43 m. It concludes that this method is feasible and accurate.
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