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The agricultural industry continues to be one of the most dangerous career fields in the United States of America with compact agricultural equipment being a common source for casualties in the industry. The primary focus of this work is to develop new technology that improves operational safety of compact agricultural equipment through the use of low-cost embedded electronics. This work presents the design of three systems in alignment with this goal.
The first system aims to integrate electrical intelligence and passive safety monitoring into the power distribution system of a small piece of agricultural equipment. The system known as the intelligent power distribution module introduces a microcontroller, an inertial measurement unit, electronic circuit control, supervised safety interlocks, current sensing, CAN communication, and data logging capabilities into the fuse block of the vehicle. A printed circuit board prototype of the system was designed and manufactured. In-lab performance and validation testing was conducted to prove the system concept as an effective safety-focused solution and identify areas of improvement.
The second system introduces a concept of scaling the accomplishments of the first system into a decentralized, modular package. A design for a distributed intelligent power distribution module which maintained power distribution, current monitoring, and data logging capabilities of original system while requiring a substantially smaller physical footprint was presented. A prototype of the system was produced and validation testing in a lab setting was conducted. Testing results validated the concept as a feasible method implementing the successes of the original intelligent power distribution module in distributed manner while also revealing areas for improvement in future iterations.
Finally, the third system provides the foundation for orientation monitoring of compact agricultural equipment through the use of low-cost inertial measurement units. Two variations of the system were developed, and multiple rounds of testing were conducted to validate the feasibility of the system as well as continually refine the orientation estimation algorithm of the system. Statistical analysis of the final testing results provided validation of the concept while also highlighting necessary improvements to calibration methodology and system architecture to improve system reliability and performance.