吉林大学学报(工学版) ›› 2021, Vol. 51 ›› Issue (3): 1146-1152.doi: 10.13229/j.cnki.jdxbgxb20200108

• 农业工程·仿生工程 • 上一篇    

基于月面表取采样触月压痕的月壤力学状态分析

王康1(),姚猛1,李立犇2,李建桥2,邓湘金1,邹猛2,薛龙3()   

  1. 1.中国空间技术研究院 北京空间飞行器总体设计部,北京 100094
    2.吉林大学 工程仿生教育部重点实验室,长春 130022
    3.江西农业大学 江西省现代农业装备重点实验室,南昌 330045
  • 收稿日期:2020-02-27 出版日期:2021-05-01 发布日期:2021-05-07
  • 通讯作者: 薛龙 E-mail:68wangkang@163.com;ultimata@163.com
  • 作者简介:王康(1985-),男,高级工程师. 研究方向:空间机构设计. E-mail:68wangkang@163.com
  • 基金资助:
    国家自然科学基金项目(51865018);中国空间技术研究院预研项目(5010120160759);江西省自然科学基金项目(20192BAB206025)

Mechanical performance identification for lunar soil in lunar surface sampling

Kang WANG1(),Meng YAO1,Li-ben LI2,Jian-qiao LI2,Xiang-jin DENG1,Meng ZOU2,Long XUE3()   

  1. 1.Beijing Institute of Spacecraft System Engineering,China Academy of Space Technology,Beijing 100094,China
    2.Key Laboratory of Bionic Engineering,Ministry of Education,Changchun 130022,China
    3.Key Laboratory of Modern Agricultural Equipment of Jiangxi Province,Jiangxi Agricultural University,Nanchang 330045,China
  • Received:2020-02-27 Online:2021-05-01 Published:2021-05-07
  • Contact: Long XUE E-mail:68wangkang@163.com;ultimata@163.com

摘要:

以表取采样机械臂的触月传感组件与月表接触留下的压痕为研究对象,通过监视相机提取压痕的几何特征参数,结合偏最小支持向量机(LSSVM)建立评估月壤力学状态模型。采集压痕试验数据264组,按力学状态把数据随机划分为建模组和验证组,以压痕的深度、长边长、压痕周长和面积为输入变量,建立LSSVM模型,验证组预测精度分别为93.75%、83.33%和87.50%。结果表明,该模型可作为一种有效的判别手段,为表取采样深度的确定提供参考。

关键词: 仿生工程, 地面力学, 表取采样, 月壤, 图像处理, 支持向量机

Abstract:

To ensure the safety of the sampling task on lunar surface, the lunar sampling arm should contact with lunar soil in advance to identify the lunar soil compactness. Based on geometric parameters of the indentation between the manipulator and lunar soil obtained by the stereo cameras, a model was established to identify mechanical performance of the lunar soil using least squares support vector machine. A total of 264 data were collected. The data was split into two data set randomly, one was calibration set (contains 96 data) and the other was prediction set (contains 48 data). Indentation length, deep, area and cube were used as input parameters to establish the prediction model, and the accuracy of prediction set are 93.75% of CE5_1, 83.33% of CE5_2, and 87.50% of CE5_3, respectively. The results show that this prediction model can be used to identify mechanical performance quickly which can be used as a method to determine the sample’s depth for lunar soil surface.

Key words: bionic engineering, terramechanics, surface sampling, lunar regolith, image processing, support vector machine

中图分类号: 

  • TB17

表1

模拟月壤相对密度和孔隙比"

模拟月壤状态相对密度/%孔隙比
松散301.45
中密501.16
密实700.94

图1

触月部件模拟件"

图2

触月试验过程"

图3

左侧相机采集的压痕图像"

表2

试验数据统计"

模拟月壤类型状态试验数量建模组预测组合计
CE5标称模拟月壤松散489648144
中密48
密实48
CE5挑战模拟月壤松散20362460
中密20
密实20
CE5极端模拟月壤松散20362460
中密20
密实20

图4

压痕的侧视图"

图5

感兴趣区域提取及二值化"

表3

CE5模拟月壤容重"

模拟月壤类型状态容重均值/(g·cm-3)
CE5标称模拟月壤松散1.577
中密1.630
密实1.709
CE5挑战模拟月壤松散1.595
中密1.632
密实1.714
CE5极端模拟月壤松散1.613
中密1.671
密实1.856

图6

三种模拟月壤力学状态判别结果"

表4

试验数据统计"

模拟月壤类型状态建模组预测组预测组准确率%
数量误判数量误判
CE5_1松散32316193.75
中密322162
密实321160
CE5_2松散1208183.33
中密12182
密实12181
CE5_3松散1218187.50
中密12282
密实12180
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