Yield Allocation System Travel Time Compensation
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Solution Overview
Problem
Existing aggregate yield sensing systems for harvesters often provide inaccurate data due to variations in travel times of crops from different portions of the harvester head to the sensor, leading to inconsistent allocation of yield to geo-referenced regions.
Innovation Solution
An aggregate yield allocation system that accounts for the travel times of crops from different portions of the harvester head to the sensor, using a geo-referencing system and yield allocation module to accurately allocate yield to specific geo-referenced regions based on the time taken for crops to reach the sensor, and applies weightings based on plant characteristics and other factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If aggregate yield sensing is implemented without accounting for travel time variations, then yield data collection is simplified, but yield allocation accuracy deteriorates
Solution Approach 1:
The system performs preliminary actions by calculating travel times for crop material from different header portions to the sensor before the yield sensing measurement is taken. This allows the system to compensate for travel time variations and accurately allocate yield to the correct geo-referenced regions, resolving the contradiction between system simplicity and measurement accuracy.
Solution Approach 2:
The system introduces an intermediary computational process that acts as a mediator between the raw sensor data and the final yield allocation. By calculating travel times and using these as intermediate variables, the system can accurately map yield data to the correct spatial locations without requiring direct measurement at each location, thus maintaining simplicity while improving accuracy.
2Measurement precision
If travel time compensation is implemented, then yield allocation accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary calculations of travel times based on known header geometry and crop flow characteristics before yield measurement. This preliminary action enables accurate yield allocation without requiring complex real-time measurements, thus improving precision while keeping the overall system complexity manageable.
Solution Approach 2:
The system uses readily available information about header geometry and operational parameters to calculate travel times, rather than requiring additional complex sensors or measurement devices. This self-service approach allows the system to improve yield allocation accuracy using existing system characteristics, minimizing the increase in overall complexity.
3Productivity
If yield data is collected without temporal adjustment, then data collection speed is maintained, but yield mapping precision deteriorates
Solution Approach 1:
The system performs preliminary calculations of travel times and temporal adjustments before yield data is finalized. This allows the system to maintain high data collection speed while applying precise temporal adjustments to ensure accurate yield mapping, as the computational adjustments are based on pre-calculated parameters rather than requiring real-time complex processing.
Solution Approach 2:
The system implements a feedback mechanism where travel time calculations inform the temporal adjustment of yield data. This feedback loop ensures that yield data is accurately mapped to the correct time and location without requiring slowing down the data collection process, thus maintaining productivity while improving mapping precision.
Data Source
AI summary
A method and apparatus estimate yield. A first signal is received that an aggregate yield measured by an aggregate yield sensor during a measurement interval. A second signal is received that indicates a plurality of geo-referenced regions across which a harvester has traveled prior to the measurement interval. The method and apparatus allocate, to each of at least two geo-referenced regions, an aggregate yield portion allocation based upon different travel times for crops to the aggregate yield sensor Visual-Infrared Vegetative Index data derived from sensing of plants in selected portions of the electromagnetic spectrum at a time other than harvest. The aggregate yield portion allocations are output.