Authors

Abstract

It is of great significance to acquire the soil surface roughness accurately for the study of the interaction between tractors and soil. Based on the laser sensor, this paper proposed the non-contact measuring instrument of the soil surface roughness with the data acquiring system by using Lab-View software. By using W-M theory, three commonly used fractal dimension calculation methods are compared and analyzed.. The result showed that the Root-mean-square method has the highest accuracy and clear physical meaning, which is ideal method to calculate the soil surface roughness characteristics. When the fractal dimension is between 1.4 and 1.6, the acquired data is analysed by the Root-mean-square method to obtain the fractal features of the soil surface roughness. The experiment results indicated that the fractal dimension of the ploughed surface is 1.39, that of disc harrow surface is 1.550, and that of rolled surface is 1.46-1.54. Obviously, the fractal dimension can accurately distinguish the soil surface roughness with the different treatments. However, the fractal dimension selected from different scales showed an obvious instability during calculations. The surface roughness index combined with the two parameters can effectively represent the soil surface roughness, and the larger the surface roughness index is, the greater the surface roughness is.

Abstract in Chinese

准确获取土壤表面粗糙度对于研究拖拉机与土壤的相互作用具有重要意义。基于激光传感器，利用软件Lab View的数据采集系统，提出了一种非接触式土壤表面粗糙度测量仪。利用W-M理论的分形曲线对3种常用的分形维数计算方法进行了比较分析。结果表明，均方根法具有较高的精度和明确的物理意义，是计算土壤表面粗糙度特性的理想方法。当分形维数在1.4～1.6之间时，用均方根法对采集的数据进行分析，得到土壤表面粗糙度的分形特征。试验结果表明，犁耕表面的分形维数为1.39，圆盘耙耕作表面的分形维数为1.55，驱动耙耕作表面的分形维数为1.46-1.54。可见，分形维数可以准确区分不同处理的土壤表面粗糙度。然而，选取不同尺度得到的分形维数在计算过程中表现出明显的不稳定性。结合分形维数与标准差这两个参数的表面粗糙度指数可以有效地表征土壤表面粗糙度，且表面粗糙度指数越大，表面粗糙度越大。