Harry Dankowicz, MechSE professor and Cannon Faculty Scholar, was recently issued a patent for a new technology that will aid in agricultural methods and processes. The invention is a method for self-calibration of a mass flow sensing system on a combine that will allow for more accurate readings of yield and mass flow sensing.
The invention will read these data under varying conditions, such as when changes are made to harvested grains and as elevator paddles age. The method is based in physics concepts and related to grain dynamics and interaction with the grain elevator.
“The realization that estimation of the mass flow rate through the combine can be accomplished simultaneously with calibration of model parameters was a breakthrough in this research project,” Dankowicz said. “It allows the farmer to make more effective use of the yield-mapping features of commercial harvesters, resulting in long-term cost reductions and increased production.”
The design of the invention relies on impact sensors and impact force because of collisions made by solid particles against each other while they flow through the sensor system. Yield measurement monitors and the calibrating of solid particles through mass-flow sensors is important, but existing methods produce many errors. This new technology will allow for the calibration of solid particles, such as grain, and will monitor their yield accurately and proficiently.
Dankowicz said the invention was made possible through various tests and models, and is a “unique technology with wide scope.” The research leading up to it was funded with help from John Deere, an American manufacturing company involved with the construction of agricultural devices. With the funding, Dankowicz was able to invent a very useful technique for farmers.
“The opportunity to work with Deere on applications of immediate relevance to their technology and business needs was very gratifying,” he said. “The relationship extended beyond the mass-flow sensor work to a series of assignments for the students in my research group. These expanded their understanding of the impact that mechanical engineering and computational modeling continues to have in traditional areas of application, such as agriculture.”