并联式六维加速度传感器的参数辨识

尤晶晶1; 李成刚1; 吴洪涛1

doi:10.3788/OPE.20132110.2627

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并联式六维加速度传感器的参数辨识

微纳技术与精密机械 | 更新时间：2020-08-12

- 并联式六维加速度传感器的参数辨识
- Parameter identification of parallel type six-axis accelerometer
- 光学精密工程 2013年21卷第10期页码：2627-2638
- 作者机构：
  
  1. 南京航空航天大学机电学院,江苏南京,210016
  2. 江苏省精密与微细制造技术重点实验室,江苏南京,210016
- 作者简介：
- 基金信息：
  
  江苏省普通高校研究生科研创新计划基金资助项目();江苏省普通高校研究生科研创新计划资助项目()
- DOI：10.3788/OPE.20132110.2627
  中图分类号： TP212.17;TH825
- 收稿日期：2013-03-15，
  
  修回日期：2013-05-16，
  
  网络出版日期：2012-10-19，
  
  纸质出版日期：2013-10-15
- 稿件说明：
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尤晶晶李成刚吴洪涛. 并联式六维加速度传感器的参数辨识[J]. 光学精密工程, 2013,21(10): 2627-2638

YOU Jing-jing LI Cheng-gang WU Hong-tao. Parameter identification of parallel type six-axis accelerometer[J]. Editorial Office of Optics and Precision Engineering, 2013,21(10): 2627-2638
尤晶晶李成刚吴洪涛. 并联式六维加速度传感器的参数辨识[J]. 光学精密工程, 2013,21(10): 2627-2638 DOI： 10.3788/OPE.20132110.2627.

YOU Jing-jing LI Cheng-gang WU Hong-tao. Parameter identification of parallel type six-axis accelerometer[J]. Editorial Office of Optics and Precision Engineering, 2013,21(10): 2627-2638 DOI： 10.3788/OPE.20132110.2627.

摘要

针对六维加速度传感器的输入、输出量较多，且其动力学方程的解耦参数难以辨识的问题，提出了四步法对并联式六维加速度传感器的25个解耦参数实施分组辨识。设计并加工了基于双曲柄滑块机构的标定平台，为参数辨识提供外部激励；在LabVIEW平台上开发了虚拟仪器，为参数辨识提供软件支持。在静态情况下对预处理后的采集数据求均值得到零值漂移，完成第一组参数辨识；将传感器安装在标定平台上做1~2 Hz的纯线性运动，使动力学模型简化成关于刻度质量比的线性代数方程，运用最小二乘法完成第二组参数的辨识；做1~2 Hz的纯角运动，将动力学模型简化成关于惯性质量比的线性代数方程，完成第三组参数的辨识；做4~5 Hz的纯线性运动，通过关于刚度质量比的一维搜索完成第四组参数的辨识。试验结果表明：运用辨识后的参数对六维加速度实施解耦，最大误差为7.479%，比参数辨识前的解耦误差降低了1个数量级。结果验证了基于四步法实现并联式六维加速度传感器的参数辨识是有效、可行的。

Abstract

The parameter identification of a six-axis accelerometer is a difficult problem due to its higher input and output volumes and linear dynamic equation. According to this

a four-step method was proposed to identify the 25 decoupling parameters of a parallel type six-axis accelerometer. A calibration platform based on double slider-crank mechanisms was designed and processed to provide the external stimulation and a virtual instrument based on LabVIEW was developed to provide the software support for the parameter identification. The first sets of parameters were identified by averaging pretreatment data in static state. By putting the sensor on the platform to do a pure line movement with the frequency of 1-2 Hz

the dynamic equations were simplified to linear algebraic equations

then the second set of parameters were identified by using the least square method. Similarly

the third set of parameters were identified when the sensor did a pure angular movement with the frequency of 1-2 Hz. The fourth set of parameters were identified by one-dimensional searching about stiffness to mass ratio when the sensor did the pure line movement with the frequency of 4-5 Hz. Experimental results indicate that the maximum relative error is 7.479% after using the identified parameters to decouple the six-axis acceleration

which reduces a magnitude compared to that before parameter identification. Above results verify that the proposed four-step method is correct and feasible.

关键词

Keywords

references

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