Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea.
Convergence Agricultural Machinery Group, Korea Institute of Industrial Technology (KITECH), Gimje 54325, Korea.
Sensors (Basel). 2020 Feb 8;20(3):912. doi: 10.3390/s20030912.
The objectives of this study were to develop a real-time tillage depth measurement system for agricultural tractor performance analysis and then to validate these configured systems through soil non-penetration tests and field experiment during plow tillage. The real-time tillage depth measurement system was developed by using a sensor fusion method, consisting of a linear potentiometer, inclinometer, and optical distance sensor to measure the vertical penetration depth of the attached implement. In addition, a draft force measurement system was developed using six-component load cells, and an accuracy of 98.9% was verified through a static load test. As a result of the soil non-penetration tests, it was confirmed that sensor fusion type A, consisting of a linear potentiometer and inclinometer, was 6.34-11.76% more accurate than sensor fusion type B, consisting of an optical distance sensor and inclinometer. Therefore, sensor fusion type A was used during field testing as it was found to be more suitable for use in severe working environments. To verify the accuracy of the real-time tillage depth measurement system, a linear regression analysis was performed between the measured draft and the predicted values calculated using the American Society of Agricultural and Biological Engineers (ASABE) standards-based equation. Experimental data such as traveling speed and draft force showed that it was significantly affected by tillage depth, and the coefficient of determination value at M3-Low was 0.847, which is relatively higher than M3-High. In addition, the regression analysis of the integrated data showed an R-square value of 0.715, which is an improvement compared to the accuracy of the ASABE standard prediction formula. In conclusion, the effect of tillage depth on draft force of agricultural tractors during plow tillage was analyzed by the simultaneous operation of the proposed real-time tillage depth measurement system and draft force measurement system. In addition, system accuracy is higher than the predicted accuracy of ±40% based on the ASABE standard equation, which is considered to be useful for various agricultural machinery research fields. In future studies, real-time tillage depth measurement systems can be used in tractor power train design and to ensure component reliability, in accordance with agricultural working conditions, by predicting draft force and axle loads depending on the tillage depth during tillage operations.
本研究的目的是开发一种用于农业拖拉机性能分析的实时耕作深度测量系统，然后通过土壤未穿透测试和犁耕田间试验对这些配置系统进行验证。实时耕作深度测量系统是通过使用传感器融合方法开发的，该方法由线性电位计、倾斜计和光学距离传感器组成，用于测量附着农具的垂直穿透深度。此外，还使用六分量称重传感器开发了一个牵引力量测系统，并通过静态负载测试验证了 98.9%的精度。通过土壤未穿透测试，证实由线性电位计和倾斜计组成的传感器融合类型 A 比由光学距离传感器和倾斜计组成的传感器融合类型 B 更精确，精度高 6.34-11.76%。因此，在田间测试中使用了传感器融合类型 A，因为它被发现更适合在恶劣的工作环境中使用。为了验证实时耕作深度测量系统的准确性，对测量的牵引和使用美国农业工程学会（ASABE）标准方程计算的预测值之间进行了线性回归分析。实验数据（如行驶速度和牵引）表明，耕作深度对其有显著影响，M3-Low 的决定系数值为 0.847，相对较高，而 M3-High 的决定系数值为 0.752。此外，综合数据的回归分析显示 R 平方值为 0.715，与 ASABE 标准预测公式的准确性相比有所提高。总之，通过同时操作提出的实时耕作深度测量系统和牵引力量测系统，分析了农业拖拉机在犁耕过程中耕作深度对牵引的影响。此外，系统精度高于基于 ASABE 标准方程的±40%的预测精度，这被认为对各种农业机械研究领域都很有用。在未来的研究中，可以根据耕作深度实时测量系统来设计拖拉机动力传动系统，并确保部件可靠性，预测耕作过程中的牵引和轴载，以适应农业工作条件。
