基于GNSS的智能水田旋耕平地机研究

设计了一种基于GNSS的智能水田旋耕平地机,将两个GNSS天线分别固定在旋耕平地机两端,以天线高程定位数据与俯仰角数据作为旋耕平地机高程与倾角信息,采用模糊PID控制算法,通过向电液比例换向阀输入驱动电压信号控制调节油缸伸缩,使旋耕平地机绕中间旋转轴转动或沿滑槽上下移动,实现了机具的水平与高度调节。设计了一种蓄能器、液压泵协同工作的液压系统,提出了基于最小二乘法的基准面生成方法。为验证智能水田旋耕平地机的工作性能,在水稻、小麦等不同前茬作物以及砂质土、粘质土、壤土等不同土壤类型条件下,对其进行了水田平整试验。试验结果表明,智能水田旋耕平地机平整效果较好,平整度达到3cm左右。该系统稳定性较好,适应性强,对水田平整度有较大的改善,平整后的水田满足水稻种植的农艺要求。     

GNSS平地作业路径实时规划与导航方法研究

为有效提高GNSS（Global navigation satellite system）控制土地平整的工作效率,提出了基于导航技术的GNSS平地作业路径实时规划与辅助决策方法。通过拉力传感器实现了平地作业中铲车载荷的实时检测,利用数学建模的方法,建立了拖拉机平地作业行驶过程的路径实时规划与导航模型。通过拉力传感器实时采集铲车载荷反馈值,根据拖拉机行驶目标区域的地势情况,以避免铲车过载和空载为原则,确定拖拉机的行驶目标点,解算出拖拉机行驶的转向角,实现了最优导航平地作业。农田平地试验结果分析表明,该方法能够较好地实时规划路径并提供导航方向,引导拖拉机高效地平地作业;基于该方法的平地作业,其铲车的过载或空载率总和不大于6.9%,远低于未使用导航时的平地情况。     

基于双GNSS天线及单陀螺的车轮转角测量系统

针对农业机械自动导航中,传统绝对角度传感器连接件多、安装复杂且容易出现故障,而陀螺测量前轮转角虽然安装容易,但陀螺零偏等仪器误差造成测量误差随时间累积的问题,提出了基于双GNSS天线和单轴MEMS陀螺组合测角系统,该系统通过双GNSS天线解算的航向角、速度等信息计算观测量,通过卡尔曼滤波器对陀螺计算的角度进行实时校正,提高了车轮转角的测量精度。实车试验结果表明,该系统具有较好的合理性和准确性,车轮转角测量结果与绝对角度传感器输出结果比较:直线试验误差在0.5°以内,曲线试验误差在1°以内,满足了农业机械自动导航的测角精度要求。     

GNSS技术及其发展趋势

对全球导航卫星系统(GNSS-Global Navigation Satellite System)中的几个重要的导航系统—GPS、GLONASS、Galileo及北斗卫星导航系统进行了概要的介绍。同时,对各个系统陆续开展的现代化建设及发展进行了探讨,并指出各个系统并存对民用及军用所产生的影响。     

Using a vision sensor system for performance testing of satellite-based tractor auto-guidance

A vision sensing system for the measurement of auto-guidance pass-to-pass and long-term errors was implemented to test the steering performance of tractors equipped with auto-guidance systems. The developed test system consisted of an optical machine vision sensor rigidly mounted on the rear of the tested tractor. The center of the drawbar hitch pin point was used as the reference from which to measure the deviation of the tractor's actual travel path from its desired path. The system was built and calibrated to a measurement accuracy of better than 2 mm. To evaluate the sensor, two auto-guidance systems equipped with RTK-level GNSS receivers were tested and the results for different travel speeds compared. Pass-to-pass and long-term errors were calculated using the relative positions of a reference at a collocated point when the tractor was operated in opposite directions within 15 min and more than 1 h apart, respectively. In addition to variations in speed, two different auto-guidance steering stabilization distances allowed for comparison of two different definitions of steady-state operation of the system. For the analysis, non-parametric cumulative distributions were generated to determine error values that corresponded to 95% of the cumulative distribution. Both auto-guidance systems provided 95% cumulative error estimates comparable to 51 mm (2 in.) claims and even smaller during Test A. Higher travel speeds (especially 5.0 m/s) significantly increased measured auto-guidance error, but no significant difference was observed between pass-to-pass and long-term error estimates. The vision sensor testing system could be used as a means to implement the auto-guidance test standard under development by the International Standard Organization (ISO). Third-party evaluation of auto-guidance performance will increase consumer awareness of the potential performance of products provided by a variety of vendors.     

Accurate single-tree positions from a harvester: a test of two global satellite-based positioning systems

Accurate positioning of single trees registered automatically during harvesting operations opens up new possibilities for reducing the field sampling effort in forest inventories utilising remotely sensed data. In the present study, we propose to use a harvester to collect single-tree data during regular harvest operations and use these data to substitute or supplement traditional measurements on sample plots. Today’s harvesters are capable of recording single-tree information such as species and diameter at breast height, and a cut-to-length harvester was equipped with an integrated accurate positioning system based on real-time kinematic global satellite positioning, as well as a low-cost global navigation satellite system (GNSS) receiver mounted directly on the harvester head. Positions from 73 trees were evaluated and compared to coordinates obtained using a total station. At the single-tree level, the mean error for the integrated positioning system was 0.94?m. The low-cost GNSS receiver mounted on the harvester head yielded a mean error of 7.00?m. The sub-meter accuracy obtained with the integrated system suggests that data acquired with a harvester using this positioning system may have a great potential as a method for single-tree field data acquisition.     

农田精准平整过程中三维地形实时测量方法研究

为提高农田平整作业过程中平后区域田面地形实时测量精度，本文提出一种农田精准平整过程中三维地形实时测量方法(Real-time 3D terrain measurement, Rt3DTM)。以安装有GNSS双天线和姿态传感器的支撑轮式旱地平地机为地形测量平台，利用卡尔曼滤波器融合GNSS与加速度提高定位精度，通过建立平地铲运动学模型获得支撑轮底点的车体坐标，结合平地铲位姿信息对支撑轮底点进行世界坐标解算，并利用最邻近插值法生成地形图。静态试验表明，Rt3DTM方法能准确解算支撑轮底点坐标，平面测量均方根误差小于10 mm,高程测量均方根误差不大于20 mm。水泥路面试验结果表明，在3组不同车速下测量同一段水泥路面三维地形，与真值的高差均方根误差均小于30 mm。田间试验结果表明，Rt3DTM测量的高程均方根误差为16.5 mm,平整度为16 mm,小于30 mm的高差分布列为95.8%,相比机载GNSS测量方法的均方根误差准确性提高29.5%,平整度准确性提高11.1%,高差分布列准确性提高9.5%。提出的Rt3DTM方法能实时准确地获取平整作业过程中平后区域的地形信息，为无人化农田平...