大尺寸箭弹质量特性测量过程中位姿标定方法研究

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

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%.

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 calibra- tion.