基于差商法的嵌入式角位移传感器自标定

发布时间：2018-08-20 17:19

【摘要】：为了摆脱对高精度基准器具的依赖实现对嵌入式角位移传感器的现场标定,结合传感器的结构特点提出了一种利用单个读数头测量值差商的方法实现自我标定。该方法利用傅里叶逼近模型将读数头的误差分离为多次谐波的叠加,采用测量值向前差商的方法获取标定模型的中间变量,运用泰勒展开对差商方法进行了误差估计,并通过提高差商阶数降低模型误差,为了保证标定精度,结合最小二乘算法对标定参数进行了寻优。运用自标定方法对两台不同对极数的嵌入式角位移传感器进行了标定实验,并与传感器常用的比较标定方法进行了对比实验。实验结果表明,两台传感器的误差分别从标定前的±30″和±25″,降低至±2.6″和±2.2″,精度得到了大幅度提高,最终的标定参数与传感器实际的误差成分相吻合,标定精度与比较标定的精度基本相同,能够满足嵌入式角位移传感器的高精度、高效率标定要求。
[Abstract]:In order to get rid of the dependence on high precision reference instruments to realize the field calibration of the embedded angular displacement sensor, a method of self-calibration using single reading head to measure the difference quotient of the values is proposed according to the structural characteristics of the sensor. In this method, the error of the readout head is separated into multiple harmonics by Fourier approximation model, the intermediate variable of the calibration model is obtained by the method of forward difference quotient of measurement value, and the error estimation of difference quotient method is carried out by Taylor expansion. In order to ensure the calibration accuracy, the calibration parameters are optimized by improving the order of difference quotient and reducing the model error. Two embedded angular displacement sensors with different pairs of poles are calibrated by using self-calibration method and compared with the conventional calibration methods. The experimental results show that the errors of the two sensors have been reduced from 卤30 "and 卤25" to 卤2.6 "and 卤2.2", respectively, and the accuracy of the two sensors has been greatly improved. The final calibration parameters are consistent with the actual error components of the sensor. The calibration accuracy is basically the same as that of the comparison calibration, which can meet the requirements of high precision and high efficiency of the embedded angular displacement sensor.
【作者单位】：重庆交通大学机电与车辆工程学院;江苏昆山留学人员创业园博士后科研工作站;重庆交通大学交通运输工程博士后科研流动站;
【基金】：国家自然科学基金资助(51405047) 重庆市教委科学技术(KJ1600534;KJ1600503) 重庆市基础科学与前沿技术研究(CSTC2016JCYJA0514)
【分类号】：TP212

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