A Load Cell-Free Solution for Weighing

Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems.Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical models and dynamic torque monitoring techniques to estimate the weight of bales immediately after the bale wrap process, before the bale is dropped onto the field.With the capability to function effectively in off-road conditions and diverse terrains, this system represents a substantial technological advancement that addresses the evolving challenges of modern agriculture. By demonstrating the potential of this design, the paper illustrates how advanced engineering solutions can enhance resource allocation, optimize feed management and distribution, support long-term planning, and contribute to the sustainability of agricultural practices without incurring additional costs.The weight of each bale can be used by farmers to analyze the current harvest based on bale weight variability and to make improvements before the next harvest. It also aids in key decision-making processes such as bale handling, transportation, sales and storage for future seasons. This advancement has significant advantages for scalability and profitability, allowing for optimized decision-making processes in agricultural operations.