Dynamic Grain Component Table for Combine Harvesters
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Solution Overview
Problem
Existing grain moisture content measuring systems in combines use pre-registered working curves that are not accurate for varying regional and yearly conditions, leading to inadequate calculation of grain component values, which is inconvenient for reliable farming management.
Innovation Solution
A grain management system that includes a combine equipped with a grain measurer and a management server, where the combine transmits measured values and field identification information to the server, which determines an optimal measured value-grain component value table based on the field information, allowing for accurate grain component value calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a pre-registered working curve is used for each type and breed of crop, then the measurement system is simple and easy to operate, but the grain component values cannot be accurately calculated due to regional and yearly variations
Solution Approach 1:
The patent implements dynamic updating of working curves by receiving correction values from external devices (smartphones, tablets, or other combines) and automatically adjusting the stored working curves in the ROM. This allows the measurement system to adapt to regional and yearly variations without requiring manual recalibration, resolving the contradiction between maintaining simplicity and improving accuracy.
Solution Approach 2:
The system incorporates a feedback mechanism where actual grain component values (obtained through laboratory analysis or other measurement methods) are used to calculate correction values. These correction values are transmitted back to the combine and applied to adjust the working curves, creating a continuous improvement loop that enhances measurement precision while maintaining system simplicity.
2Measurement precision
If the working curve is updated frequently to account for regional and yearly variations, then grain component value accuracy improves, but the system becomes more complex and harder to operate
Solution Approach 1:
The system performs automatic updates of working curves without requiring operator intervention. The correction values are received and applied automatically by the control unit, and the system maintains the updated curves in memory for continuous use. This self-service approach ensures accuracy improvements while preserving ease of operation.
Solution Approach 2:
The system pre-stores multiple working curves for different types and breeds of crops in the ROM. When a specific crop type is selected, the corresponding pre-prepared working curve is automatically loaded and can be further adjusted using correction values. This preliminary preparation eliminates the need for operators to perform complex calibration procedures during operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system enables accurate and reliable farming management by using the latest measured value-grain component value tables that consider regional and yearly variations, providing real-time grain component values such as moisture content and protein levels.
Implementation Method 1
a moisture sensor for crushing grains flowing from a grain supply opening that leads to the grain tank, between rotating electrode rollers, and detecting an electrical resistance value of the grains in a crushed state
Data Source
AI summary
A grain management system includes a combine and a management server. The combine includes a grain measurer for outputting a measured value related to a component of harvested grains supplied to a grain tank, and a data transmitter for transmitting the measured value and field identification information for specifying the field to the management server via a communication line. The management server includes a receiver for receiving the field identification information and the measured value from the combine, a table manager for determining a measured value-grain component value table for deriving a grain component value using the measured value based on the field identification information, and a grain component value computer for obtaining the grain component value based on the measured value, using the measured value-grain component value table that is determined by the table manager.