This study analyzed the lateral overturning and backward rollover characteristics of a multi-purpose agricultural machine recently developed in South Korea. Free body diagrams for theoretical analysis and a three-dimensional model for dynamic simulation were created by reflecting the actual dimensions and material properties of the multi-purpose agricultural machine. The simulation model was verified using the minimum turning radius and angle of static falling down sidelong derived through the certified performance test. The lateral overturning and backward rollover characteristics of the multi-purpose agricultural machine were analyzed using a verified simulation model and theoretical equations derived through literature review. In the lateral overturning analysis, the critical traveling speed at which lateral overturning occurs was derived according to the inner steering angle of the front wheels under steady-state turning conditions. In the backward rollover analysis, the critical angular velocity and theoretical traveling speed of the main body at which backward rollover occurs were derived according to lifting angle of the front wheels. There was no significant difference between the theoretical analysis and simulation results at 5% significance level, and we derived the appropriate traveling speed conditions of the multi-purpose agricultural machine that do not cause lateral overturning and backward rollover.

The effects of the slope of the ground and the obstacle conditions on the lateral overturning/backward rollover of a tractor with an implement were analyzed through dynamic simulation. The tractor and implement’s 3D simulation model was constructed. As for simulation conditions, four heights and three shapes were set for obstacles, and eight slopes were set for the ground to be traveled by the implemented tractor. Under each condition, the critical speed at which the tractor begins to overturn and roll over was derived, and factors that caused the overturn and rollover were analyzed. As a result of instability types, backward rollover happens when the ground slope is low and lateral overturning happens at a specific slope or higher regardless of the obstacle conditions. In the case of the tractor and implement under study, the tendency changed at a slope of 25°. As the obstacle height increased, overturning and rollover safety decreased. In the case of the obstacle shape, safety was lowest for the rectangular obstacle and highest for the right-side triangular obstacle. The driving safety of the tractor with the implement was lower than that of the tractor with no implement. This appears to be mainly due to the change in the position of the center of gravity caused by the attached implement. The critical speed of the tractor with the implement was 3.26 times lower than that of the tractor with no implement on average. It is judged that the safety of the implemented tractor can be identified by using this study.

This study proposes a method to construct a dynamic simulation model to implement the lateral overturning and backward rollover characteristics of an actual tractor. Based on theoretical analysis, factors affecting these characteristics are identified, which include tractor weight, track width, wheelbase, location of mass center, weight distribution, heights of front and rear axles, and geometric shapes. The location of the mass center of the actual tractor is measured based on the standard test procedure set by the International Organization for Standardization, and the remaining influencing factors are derived through measurements. A three-dimensional (3D) model of the tractor is constructed to reflect all these factors. Additionally, a simulation model utilizing this 3D model is developed using a commercial dynamic simulation software program. The ability of the model to simulate the overturning and rollover characteristics of the actual tractor is verified by comparing the static sidelong falling angle and minimum turning radius with those of the actual tractor. The errors between the characteristics of the actual tractor and those of the 3D model and dynamic simulations are shown to be less than 5%, thus indicating that the proposed method can effectively simulate the overturning and rollover characteristics of the actual tractor.

In this study, we developed a monitoring system to accurately track the seeding rate and to identify the locations where the mechanical pot-seeding machine failed to sow seeds correctly. The monitoring system employs diverse image processing techniques, including the Hough transform, hue–saturation–value color space conversion, image morphology techniques, and Gaussian blur, to accurately pinpoint the seeding rate and the locations where seeds are missing. To determine the optimal operating conditions for the seeding rate monitoring system, a factorial experiment was conducted by varying the brightness and saturation values of the image data. When the derived optimal operating conditions were applied, the system consistently achieved a 100% seed recognition rate across various seeding conditions. The monitoring system developed in this study has the potential to significantly reduce the labor required for supplementary planting by enabling the real-time identification of locations where seeds were not sown during pot-seeding operations.