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兵工学报 ›› 2014, Vol. 35 ›› Issue (1): 108-113.doi: 10.3969/j.issn.1000-1093.2014.01.016

• 论文 • 上一篇    下一篇

大尺寸箭弹质量特性测量过程中位姿标定方法研究

王超, 张晓琳, 唐文彦, 王军, 马强   

  1. (哈尔滨工业大学 电气工程及自动化学院, 黑龙江 哈尔滨 150001)
  • 收稿日期:2013-02-27 修回日期:2013-02-27 上线日期:2014-03-18
  • 通讯作者: 王超 E-mail:wangchao1984@hit.edu.cn
  • 作者简介:王超(1984—), 男, 博士研究生
  • 基金资助:
    国家自然科学基金青年科学基金项目(61108073)

Method for Improving Mass Property Measurement Accuracy of Large-size Projectiles

WANG Chao, ZHANG Xiao-lin, TANG Wen-yan, WANG Jun, MA Qiang   

  1. (School of Electrical Engineering Automation, Harbin Institute of Technology,Harbin 150001, Heilongjiang, China)
  • Received:2013-02-27 Revised:2013-02-27 Online:2014-03-18
  • Contact: WANG Chao E-mail:wangchao1984@hit.edu.cn

摘要: 为提高大尺寸箭弹质量特性的测量精度,对产品测量位姿的标定方法进行了研究。建立测量设备运动学模型,在模型基础上分析了测量位姿误差对测量结果的影响。阐述了基于运动学原理的标定方法和标定步骤,并对标定模型中参数进行分析和分类,将神经网络与运动学相结合进行位姿的标定。实验结果表明,采用运动学方法标定位姿后将质心测量误差减小到原来的10%,转动惯量和惯性积测量误差减小到原来的90%和23%;而采用神经网络与运动学相结合的方法标定位姿后,质心测量误差减小为原来的7%,转动惯量和惯性积测量误差减小为原来的45%和15%.

关键词: 仪器仪表技术, 质量特性, 位姿, 测量精度, 运动学, 神经网络

Abstract: In order to increase the mass property measurement accuracy of the large-size projectile, the calibration methods of measured pose are investigated. A kinematics model for measurement system is established, and the influence of measured pose errors on measuring results are analyzed. A method and process of calibration based on the kinematics are introduced, and the calibration parameters are analyzed and classified. A calibration method using neural networks is provided. Experimental results indicate that the Kinematics method is used to reduce the errors of CG, MOI and POI to 10%, 90% and 23%, respectively, before calibration. The combination method of neural networks and kinematics is used to reduce the errors of CG, MOI and POI to 7%, 45% and 25%, respectively, before calibration.

Key words: technology of instrument and meter, mass property, poses, measurement accuracy, kinematics, neural network

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