基于农机空间运行轨迹的作业状态自动识别试验
以物联网为代表的现代信息技术在农机作业管理领域的发展应用,实现了农机作业过程的定位监控,但现有农机远程监管系统对海量农机空间位置数据仅实现了远程存储、显示和简单分析,难以满足农机精准管理和数据智能处理的要求。该文采用数据挖掘中的聚类和空间数据分析方法,结合农机空间运行轨迹的特点,研究了基于空间运行轨迹点的农机作业状态自动识别算法;设计实现了典型农机运行状态自动识别方法,定量分析了农机作业班次内田间作业时间、空行转移时间、停歇时间的量化构成。农机试验表明:发展的基于空间索引和网格密度的聚类算法精度达89%以上。农机作业状态自动识别为农机作业生产率、农机利用率和作业成本核算提供了定量依据。...
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Published in | 农业工程学报 Vol. 31; no. 3; pp. 56 - 61 |
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Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
国家农业信息化工程技术研究中心,北京,100097%国家农业智能装备工程技术研究中心,北京,100097
2015
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Subjects | |
Online Access | Get full text |
ISSN | 1002-6819 |
DOI | 10.3969/j.issn.1002-6819.2015.03.008 |
Cover
Summary: | 以物联网为代表的现代信息技术在农机作业管理领域的发展应用,实现了农机作业过程的定位监控,但现有农机远程监管系统对海量农机空间位置数据仅实现了远程存储、显示和简单分析,难以满足农机精准管理和数据智能处理的要求。该文采用数据挖掘中的聚类和空间数据分析方法,结合农机空间运行轨迹的特点,研究了基于空间运行轨迹点的农机作业状态自动识别算法;设计实现了典型农机运行状态自动识别方法,定量分析了农机作业班次内田间作业时间、空行转移时间、停歇时间的量化构成。农机试验表明:发展的基于空间索引和网格密度的聚类算法精度达89%以上。农机作业状态自动识别为农机作业生产率、农机利用率和作业成本核算提供了定量依据。 |
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Bibliography: | 11-2047/S Abstract: With development and wide application of modem information technology as presented by the Intemet of things, the position monitoring of operation process of agricultural machinery has been realized easily. But the existing remote monitoring system for agricultural machinery has only realized the remote storage, display and simple analysis. It is difficult to meet the requirements of fine management and intelligent data processing of agricultural machinery. In this paper, combining with the characteristics of the space track of agricultural machinery, the methods of clustering in data mining and spatial data analysis method were used to study automatic segmentation algorithm of field operation area based on spatial track of agricultural machinery. The procedure is as follows: firstly, data preprocessing, including velocity threshold and projection transformation methods, is preparing for further gridding and density slicing for the next step; secondly, spatial track of agricultural machinery |
ISSN: | 1002-6819 |
DOI: | 10.3969/j.issn.1002-6819.2015.03.008 |