Harvester Yield Signal Correction for Dynamic Event Timing
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Solution Overview
Problem
Agricultural harvesting machines, such as combine harvesters, face inaccuracies in yield sensing due to dynamic events like changes in speed, orientation, and grain flow dynamics, leading to significant variability in sensor signals, which affect the accuracy of yield and loss measurements.
Innovation Solution
A dynamic event detection system identifies and corrects for these events by determining the magnitude and timing of dynamic effects on sensor signals, applying a correction value to the yield signal to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a delay time is applied to sensed yield values to account for processing delays, then the geographic location accuracy of yield values is improved, but the real-time responsiveness of the yield data is worsened
Solution Approach 1:
The system pre-calculates and stores correction factors for different dynamic conditions (acceleration, deceleration, turning) before they occur during harvesting. When a dynamic event is detected, the appropriate pre-prepared correction factor is immediately applied, eliminating the need for time-consuming real-time calculations while maintaining accuracy
Solution Approach 2:
The patent replaces the traditional time-based delay correction method with a model-based computational approach. Instead of simply delaying yield values to match processing time, the system uses a harvester model that calculates expected yield values based on current sensor inputs and dynamic conditions, then applies appropriate correction factors to achieve accurate real-time geographic mapping
2Measurement precision
If dynamic event correction is applied to sensor signals, then the measurement precision of yield and loss data is improved, but the device complexity increases
Solution Approach 1:
The correction system is divided into independent modular components: a dynamic event detector that identifies specific events (acceleration, deceleration, turning), a harvester model that processes sensor inputs, and a correction factor applicator that adjusts yield values. Each module performs a specific function, making the overall complex system manageable and maintainable
Solution Approach 2:
The patent introduces an intermediary harvester model that acts as a mediator between raw sensor inputs and final yield corrections. This model synthesizes information from multiple sensors (yield, loss, speed, orientation) and generates correction factors that are then applied to the final measurements, simplifying the correction process while improving accuracy
3Reliability
If multiple sensors are used to detect dynamic events, then the reliability of dynamic event detection is improved, but the device complexity and cost increase
Solution Approach 1:
The system uses existing multi-functional sensors already present on modern harvesters (GPS receivers for position and speed, inertial measurement units for orientation, yield sensors for material flow) and leverages their multiple capabilities for both primary harvesting measurements and dynamic event detection, avoiding the need for additional dedicated sensors
Solution Approach 2:
The system continuously monitors sensor inputs and provides feedback to the harvester model, which adjusts correction factors in real-time based on detected dynamic conditions. This closed-loop feedback mechanism ensures reliable detection and correction of dynamic events while using existing sensor infrastructure
Data Source
AI summary
A dynamic event detection system detects dynamic events, based on a sensor signal, on a mobile harvester. A dynamic event correction system identifies a correction magnitude, corresponding to the detected dynamic event, and a correction timing. The dynamic event correction system applies a correction, using the correction magnitude and correction timing, to a performance metric value generated from a performance metric sensor.