Hyperspectral Windrow Measurement Under Variable Ambient Light
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Solution Overview
Problem
Existing mower implements face challenges in accurately estimating windrow width and volumetric spread under varying ambient light conditions, affecting the quality and efficiency of crop drying and harvesting.
Innovation Solution
Incorporation of a hyperspectral sensor to detect light beyond the visible spectrum, coupled with a controller to analyze light spectrums and adjust the width and volumetric spread of windrows using actuators and drivetrain components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If an RGB camera is used to capture windrow images, then the operator can view the windrow through a display, but the image quality and contrast are affected by varying ambient light conditions
Solution Approach 1:
The patent replaces the RGB camera system with a hyperspectral sensor that detects light in the near-infrared spectrum rather than relying on visible light captured by standard camera sensors. This substitution of the detection mechanism allows measurement of windrow properties independent of ambient visible light conditions, resolving the contradiction between illumination intensity variations and measurement precision
2Measurement precision
If a hyperspectral sensor is used to detect windrow properties, then the accuracy of windrow width and volumetric spread estimation is improved, but the device complexity increases
Solution Approach 1:
The patent extracts and utilizes only the near-infrared portion of the hyperspectral data (specifically wavelengths around 800-900 nm) that are most relevant for measuring windrow width and volumetric spread. By focusing on this specific spectral region rather than processing the entire hyperspectral range, the system achieves high measurement precision while reducing computational complexity and data processing requirements
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
Enhances the accuracy of windrow width and volumetric spread estimation, improving crop drying and harvesting efficiency by adapting to different light conditions and environmental factors.
Implementation Method 1
The hyperspectral sensor is configured for hyperspectral sensing, which detects the light beyond the visible spectrum and reflected from a target area behind the mower implement
Data Source
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AI summary
A mower implement comprising may include a main frame, a cutter assembly, a hyperspectral sensor, and a controller. The hyperspectral sensor is coupled to the main frame, receives reflectance from a target area disposed rearward of the cutter assembly and including the windrow, and generates a signal indicative of light spectrums of the target area. The controller has a processor and a memory having a windrow distribution algorithm stored therein. The processor is operable to execute the windrow distribution algorithm to: receive the signal indicative of the light spectrums of the target area from the hyperspectral sensor; calculate a normalized difference index based on the signal indicative of the light spectrums of the target area; estimate a volumetric spread of the windrow; and control a machine system based on the volumetric spread. The machine system includes one of a display, an actuator, and a drivetrain component.