悬臂式掘进机导航技术现状及其发展方向

田原

田原.悬臂式掘进机导航技术现状及其发展方向[J].工矿自动化,2017,43(8):37-43.. DOI: 10.13272/j.issn.1671-251x.2017.08.008
引用本文: 田原.悬臂式掘进机导航技术现状及其发展方向[J].工矿自动化,2017,43(8):37-43.. DOI: 10.13272/j.issn.1671-251x.2017.08.008
TIAN Yuan. Present situation and development direction of navigation technology of boom-type roadheader[J]. Journal of Mine Automation, 2017, 43(8): 37-43. DOI: 10.13272/j.issn.1671-251x.2017.08.008
Citation: TIAN Yuan. Present situation and development direction of navigation technology of boom-type roadheader[J]. Journal of Mine Automation, 2017, 43(8): 37-43. DOI: 10.13272/j.issn.1671-251x.2017.08.008

悬臂式掘进机导航技术现状及其发展方向

基金项目: 

中国煤炭科工集团有限公司科技项目(2016MS016)

详细信息
  • 中图分类号: TD632.2

Present situation and development direction of navigation technology of boom-type roadheader

  • 摘要: 阐述了悬臂式掘进机导航定位问题,并分析了其特殊性,给出了其数学描述;详细分析了掘进机光电导航和位姿检测技术现状、掘进机惯性导航技术现状、基于多信息融合的掘进机导航定位技术现状,并进行了比较与评价。得出结论:光电导航装备技术成熟、精度高,但在煤矿井下应用存在较严重的环境适应性问题;惯性导航技术环境适应性强、姿态检测精度较高,但长时定位精度差;将光电导航技术和惯性导航技术相结合的多信息多传感器融合的导航技术可能是解决悬臂式掘进机空间位姿检测问题的较优途径,实现信息融合的关键在于解决多信息多传感器带来的测量基准统一问题,且需要鲁棒性更强的融合算法。
    Abstract: Problems of navigation and positioning of boom-type roadheader and its particularity and mathematical description were described. Status of technology of electro-optical navigation and positioning and pose detection, technology of inertial navigation, and navigation and positioning technology based on multi-information fusion were analyzed in details. The conclusions were obtained: the technology of electro-optical navigation is mature and has high precision, but there are serious environmental adaptability problems in coal mine application; the inertial navigation technology has strong adaptability, high accuracy of pose detection, but has poor precision of long-term positioning; the technology based on fusions of multi-information and multi-sensor, which combining electro-optical navigation and inertial navigation, may be the better way to solve the problem of spatial position and pose detection of boom-type roadheader, the key to realization of information fusion is to solve measuring benchmarking issues brought from multi-information and multi-sensor, and more robust fusion algorithm is needed.
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出版历程
  • 刊出日期:  2017-08-09

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