轨道强约束下的惯性微位移测量算法  

Inertial Micro-Displacement Measurement Algorithm under Strong Track Constraints

作　　者：陈璞[1] 张金红[1] 刘小溪[1] CHEN Pu;ZHANG Jinhong;LIU Xiaoxi(AVIC Xi'an Flight Automatic Control Research Institute,Xi'an 710072,China)

机构地区：[1]中国航空工业集团西安飞行自动控制研究所,陕西西安710072

出　　处：《工业技术创新》2022年第1期9-16,共8页Industrial Technology Innovation

基　　金：国家自然科学基金面上项目——煤矿掘进装备组合惯性测量系统多源信息融合精确定位与智能导航控制(项目编号:52174150)。

摘　　要：为提高轨道几何参数检测准确性和效率,提出一种轨道强约束下的惯性微位移测量算法。探讨了轨道几何参数与惯性空间紧耦合关系,将内部轨道几何参数定义为三个参数簇族;构建了惯性测量模型,以研究惯性器件和惯性测量组合误差对轨道几何参数检测精度的影响;构建了三种强约束模型——直线约束模型、曲线约束模型和缓和约束模型,设计了以卡尔曼滤波器为中心的惯性微位移测量模型。研制了动态精调小车对算法进行实际效果的验证,在0~10 km/h的速度下,可以得到误差不高于0.2 mm的平顺性,为全参数轨道动态检测提供了一种低成本、高效率的新方法。In order to improve the accuracy and efficiency of track geometric parameter detection,an inertial micro-displacement measurement algorithm under strong track constraints was proposed.The tight coupling relationship between track geometric parameters and inertial space was discussed,and the internal track geometric parameters were defined as three parameter families.The inertial measurement model was built to study the influence of the combined error of inertial devices and inertial measurement on the detection accuracy of track geometric parameters.Three strong constraint models,i.e.linear constraint model,curve constraint model and relaxation constraint model were constructed,and the inertial micro-displacement measurement model surround Kalman filter was designed.The actual effect of such an algorithm was verified by developing a dynamic fine-tuning trolley.At the speed of 0~10 km/h,the ride comfort with the error not higher than 0.2 mm can be obtained,which provides a new method with low cost and high efficiency for dynamic detection of all-parameter track.

关 键 词：微位移 轨道几何参数 惯性测量模型 轨道强约束 平顺性 

分 类 号：U463.71[机械工程—车辆工程]