重庆理工大学学报(自然科学) ›› 2023, Vol. 37 ›› Issue (12): 92-102.

• “精密工程测量技术与仪器”专栏 • 上一篇    下一篇

时栅位移传感器动态误差预测及实时补偿方法

彭凯, 李翼, 樊星辰, 于治成, 蒲红吉   

  1. 重庆理工大学机械检测与装备技术教育部工程研究中心; 通用技术集团国测时栅科技有限公司; 重庆市科学技术研究院
  • 出版日期:2024-02-04 发布日期:2024-02-04
  • 作者简介:彭凯,男,博士后,副研究员,主要从事微纳传感理论和智能仪器研究,E-mail:pk@cqut.edu.cn;通信作者 樊星辰,男,博士,助理研究员,主要从事精密位移测量技术及智能传感器研究,E-mail:fxc@cqut.edu.cn

Research on dynamic error prediction and real time compensation methods for time-grating displacement sensors

  • Online:2024-02-04 Published:2024-02-04

摘要: 对精密位移测量系统的动态误差进行补偿可提高系统的稳定性、精确性和鲁棒性,但补偿的实时性会影响补偿的有效性和准确性。为此,提出了一种通过预测动态误差实时补偿时栅位移传感器测量值的方法,并结合时栅角位移传感器进行分析。首先根据时栅角位移传感器特性,建立了动态误差数学模型,结合无迹卡尔曼滤波算法对动态误差进行预测以提高补偿的实时性,最后在仿真软件和搭建的时栅伺服电机测试平台上验证了该方法的可行性和有效性。在电机保持恒定转速5、50、200 r/min,加速度为12 000 r/min2的匀加速和加速度在1 000、5 000、12 000 r/min2中由低到高变化的加速条件下,传感器动态误差分别降低约54.89%、67.37%、80.13%、59.29%和47.09%。通过预测对动态误差进行实时补偿能显著提高传感器的动态测量精度,并且转速越高补偿效果越好,相较于传统的谐波补偿法具有更好的实时性。

关键词: 时栅位移传感器, 动态误差, 误差预测, 实时补偿, 无迹卡尔曼滤波

Abstract:

Displacement sensors are widely employed in precision machining and metrology, serving as pivotal components for real-time position detection. In practical applications, displacement sensors typically undertake dynamic measurement tasks, and dynamic error, as a critical metric for assessing dynamic measurement accuracy, directly impacts the stability, precision, and robustness of the measurement system. In recent years, scholarly attention has increasingly focused on dynamic errors.

Both domestic and international scholars have conducted a series of in-depth studies on methods to mitigate dynamic errors. Currently, strategies for suppressing dynamic errors primarily involve control methodologies such as adaptive control, model predictive control, and fuzzy control, as well as compensation methods like harmonic compensation, genetic algorithms, and posterior error fitting algorithms. Among these, compensation methods have been widely applied due to their simplicity and efficiency. However, conventional compensation methods encounter challenges related to real-time performance. These methodologies necessitate data collection, transmission, and processing before implementation, causing delays at each stage. Consequently, delayed compensation actions hinder real-time effectiveness, resulting in suboptimal compensation outcomes. To address the real-time challenges associated with compensation, predictive technology, commonly utilized in servo control, is employed. Although predictive technology finds extensive application in various fields, its integration into displacement sensors remains limited.

The time-grating displacement sensor, as a novel variant, has witnessed extensive adoption. While extensive research has advanced the static measurement accuracy of time-grating displacement sensors, limited attention has been given to dynamic measurement accuracy. This paper proposes a real-time compensation method for the measured values of time-grating displacement sensors by predicting dynamic errors. The approach is analyzed in conjunction with the time-grating angular displacement sensor. A dynamic error mathematical model is built based on the characteristics of the time-grating angular displacement sensor, and the unscented Kalman filtering algorithm is applied to construct a dynamic error prediction model. Utilizing this model, the dynamic error of the time-grating displacement sensor at the next moment is predicted and employed as a real-time compensation value for the subsequent measurement. The proposed method’s feasibility and effectiveness are verified through simulation software and a constructed time grid servo motor testing platform. Under constant motor speeds of 5 revolutions per minute (r/min), 50 r/min, and 200 r/min, as well as uniform accelerations of 12 000 revolutions per minute squared (r/min2), and variable accelerations ranging from low to high (1 000 r/min2, 5 000 r/min2, and 12 000 r/min2), the dynamic error of the sensor is reduced by approximately 54.89%, 67.37%, 80.13%, 59.29%, and 47.09%, respectively. Real-time compensation for dynamic errors through prediction significantly enhances the dynamic measurement accuracy of sensors, exhibiting superior compensation effects at higher speeds. In comparison to traditional harmonic compensation methods, this approach demonstrates superior compensation efficacy and higher real-time performance in variable speed conditions.

中图分类号: 

  • TH7