Design and Construction
N. Loveimi; A. Azizi; A. Kaab; A. Neisi
Abstract
IntroductionSubsoiling is a critical tillage operation for many crops, particularly sugarcane, due to the impact of agricultural machinery traffic and its significance in managing heavy-textured and compacted soils. Given the extensive size of sugarcane fields and the time-intensive nature of subsoiling ...
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IntroductionSubsoiling is a critical tillage operation for many crops, particularly sugarcane, due to the impact of agricultural machinery traffic and its significance in managing heavy-textured and compacted soils. Given the extensive size of sugarcane fields and the time-intensive nature of subsoiling operations, the application of intelligent control techniques for monitoring and managing these processes is of considerable importance. Currently, subsoiling operations are monitored using manual gauges. This approach involves collecting a limited number of samples per hectare, typically after the operation is completed, which makes it nearly impossible to implement real-time corrections. To address this limitation, the development and implementation of a depth measurement system offer a promising solution. Such a system enables real-time observation of working depth by both the operator, via an on-screen display, and by a remote observer through an online platform. This capability allows for immediate adjustments during the operation, ensuring greater precision and efficiency. Furthermore, by integrating recorded depth data with geospatial information, it becomes possible to generate detailed maps illustrating depth variations across the field. These maps can serve as valuable tools for further evaluations, such as performance monitoring in areas where subsoiling depth deviates from the desired range, either being too shallow or excessively deep. This technological advancement has the potential to significantly enhance the accuracy and effectiveness of subsoiling operations in modern agricultural practices.Materials and MethodsThis study focused on the design, development, and evaluation of a depth measurement system for a subsoiler attached to a track-type tractor, specifically tailored for sugarcane fields. The system not only provided real-time depth display but also recorded the location and transmitted it online. The research employed three distinct depth measurement techniques and was conducted using a randomized complete block design with split plots. The main plots are the three depth measurement techniques: based on the angles of the driving profiles of the subsoiler shanks (T1), the laser distance measurement method (T2), and the ultrasonic distance measurement method (T3), and sub-plots are depth ranges at three levels: 0-30 cm (R1: surface range), 30-60 cm (R2: mid-range), and 60-90 cm (R3: deep range). Initially, we calculated the absolute difference between the depths recorded by the system and those measured manually with a rod at each location. Following this, we analyzed key statistical indicators, including the average, standard deviation, and the minimum and maximum of errors, for comparison.Results and DiscussionThe results showed that the depth measurement error was significantly influenced by the technique employed. The angle technique yielded the lowest average error of 1.91 cm, while the ultrasonic technique resulted in the highest average error of 3.83 cm. Across all depth ranges, statistical indicators for depth error were significant. Specifically, within these ranges, the deep range exhibited an average depth error of 2.33 cm, and the surface range had an average error of 3.65 cm. Statistical analysis revealed that only indices related to minimum and maximum errors for interactions between factors were significant. The lowest minimum error value (0.05 cm) was observed with the angle technique at deeper depths, whereas the highest minimum error (0.34 cm) occurred with ultrasonic measurements at shallower depths on surfaces. Similarly, maximum errors followed this trend: The lowest maximum error (3.21 cm) was associated with angle measurements at deeper depths, while ultrasonic measurements on surfaces yielded a higher maximum error (8.63 cm). Both laser and ultrasonic techniques consistently demonstrated greater errors across all three depth ranges compared to angle-based methods. This discrepancy may be attributed to inaccuracies inherent in rangefinders when their beams encounter obstacles like clods or pits during field operations. Notably, as working depths increased across all measurement techniques, errors in depth measurement decreased significantly due to reduced vibrations from subsoiler devices at greater depths, thereby minimizing vibration-related inaccuracies.ConclusionThe results indicate that the depth measurement technique based on the angles of the driving profiles of subsoiler shanks exhibits superior accuracy in determining the working depth of subsoilers mounted on tractors, particularly during sugarcane field operations. The laser distance meter technique ranked second in terms of accuracy, while the ultrasonic distance meter method demonstrated the least precision. Notably, as working depths increased, reduced vibrations during operation were observed, leading to enhanced accuracy in depth calculations across all techniques. This improvement is attributed to decreased mechanical disturbances at greater depths. Overall, measurements within deeper ranges achieved higher levels of accuracy compared to those at shallower surface ranges. This trend suggests that operational conditions and device stability play significant roles in optimizing measurement accuracy.
