鲁植雄, 钟文军, 刁秀永, 梅士坤, 周 晶, 程 准. 基于拖拉机作业轨迹的农田面积测量[J]. 农业工程学报, 2015, 31(19): 169-176. DOI: 10.11975/j.issn.1002-6819.2015.19.023
    引用本文: 鲁植雄, 钟文军, 刁秀永, 梅士坤, 周 晶, 程 准. 基于拖拉机作业轨迹的农田面积测量[J]. 农业工程学报, 2015, 31(19): 169-176. DOI: 10.11975/j.issn.1002-6819.2015.19.023
    Lu Zhixiong, Zhong Wenjun, Diao Xiuyong, Mei Shikun, Zhou Jing, Cheng Zhun. Measurement of field area based on tractor operation trajectory[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(19): 169-176. DOI: 10.11975/j.issn.1002-6819.2015.19.023
    Citation: Lu Zhixiong, Zhong Wenjun, Diao Xiuyong, Mei Shikun, Zhou Jing, Cheng Zhun. Measurement of field area based on tractor operation trajectory[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(19): 169-176. DOI: 10.11975/j.issn.1002-6819.2015.19.023

    基于拖拉机作业轨迹的农田面积测量

    Measurement of field area based on tractor operation trajectory

    • 摘要: 为了精确测量拖拉机在农田作业时的作业面积,以评价拖拉机的作业效率。该文选用双星定位(GPS卫星和伽利略卫星)接收机采集定位数据,采用自适应卡尔曼滤波算法提高接收机单点定位精度,利用高斯投影算法将GPS接收机采集经纬度转化成平面坐标来计算面积。选用回耕法、梭形耕法、套耕法3种方法旋耕地块,利用安装拖拉机上的GPS识别出作业轨迹,利用图像处理计算3种方法的有效作业面积、实际作业面积和重漏耕面积。试验表明:卡尔曼滤波提高了GPS单点定位精度;面积测量相对误差为2.09%;地块1(回耕法)漏耕率为14.29%,重耕率为6.19%,地块2(梭形耕法)漏耕率为10.72%,重耕率为5.54%,地块3(套耕法)漏耕率为1.80%,重耕率为6.82%。随测量面积增加,测量精度越高;套耕法效率最高,梭形耕法其次;回耕法的漏耕率最大,作业效率最低。

       

      Abstract: Abstract: The rapid development of modern agriculture in China has put forward higher requirements for agricultural machinery operation. In terms of area measurement, GPS (global positioning system) has become an important measuring tool, completely changed the traditional mode of operation, liberated the labor force, and improved the operation efficiency. Field operation is still basically in the stage of manual operation, so it is inevitable that there is much repetitive operation and missing operation. How to accurately measure the area of operation, this is a necessary issue. In this paper, the adaptive Kalman filter was used to improve GPS positioning accuracy for accurately measuring the tractor operation area. The adaptive Kalman filtering algorithm was mainly to solve the problem of the degradation of the system's filtering accuracy and the divergence of the system in the case of noise statistics being unknown or not accurate. In order to achieve the system noise estimation of adaptive filtering, we used the covariance matching technology and the Kalman filter residual error to realize the algorithm. In this research, the LABVIEW software was used to get latitude and longitude data of GPS receiver. And then the Gauss projection algorithm was used to change the longitude and latitude data into plane coordinates to calculate the area. To test and verify the influence of different ways of operation on the operation efficiency, back tillage, spindle tillage and alternative plough method were chosen. Firstly, this research used MATLAB to identify the operation trajectory, then used different color to show the area of operation, and used the image processing method to calculate the effective operation area, the actual operation area, and the missed and repeated tillage rate, which were used to evaluate the operation efficiency of the tractor. In order to verify the feasibility of the algorithm, the accuracy of single point positioning and the accuracy of area measurement were tested. The single point positioning experiment showed that the Kalman filter improved the accuracy of GPS single point positioning. The numerical changes at the x and y direction before filtering had relatively big fluctuation, and became flat after filtering. The mean value of coordinates changed after filtering, and the mean square error became smaller. The x coordinate reduced from 0.06317 to 0.05807 m after filtering, and the y coordinate reduced from 0.07901 to 0.04097 m after filtering. In the test of GPS area measuring precision, which was the preparation for its work in the measurement of field area, this research used the GPS to measure some regular and irregular figures. The result showed that the relative error of area measurement was 2.09%. Finally, the field experiment was conducted. The result showed that Block 1 missed tillage rate was 14.29%, and repeated tillage rate was 6.19%; Block 2 balk rate was 10.72%, and backset rate was 5.54%; Block 3 balk rate was 1.81%, and backset rate was 6.82%. With the measurement area increasing, the measurement accuracy was higher. The most efficient farming method was alternative tillage, and the second was spindle tillage. Back tillage's balk rate was the highest, and its operating efficiency was the lowest. Image processing method was used to calculate the backset and balk acreage in this paper. Different colors were used to display normal area, repeated tillage area and missed tillage area, through which it could visually display missed and repeated tillage locations, and then calculate the working efficiency. We can use this method to guide the actual agricultural production operation, and select the operation mode with high efficiency.

       

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