Combine Harvester Image Control for Threshing Loss Detection
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Solution Overview
Problem
Existing combine harvesters face imprecise evaluation of threshing quality, leading to inaccurate assessment of processing losses due to unthreshed harvested material, which affects grain quality and efficiency.
Innovation Solution
Implement a camera system and image evaluation device using machine learning algorithms to analyze the flow of harvested material, determining indicators of processing losses, and a driver assistance system to adjust working units for improved threshing quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensor-based methods are used to evaluate threshing quality, then the device complexity is low, but the measurement precision is insufficient leading to inaccurate assessment of processing losses
Solution Approach 1:
The patent replaces traditional mechanical sensor-based detection systems with an optical camera system combined with machine learning algorithms. The camera captures images of the transferred harvested material flow, and image evaluation devices analyze these images to determine processing loss indicators, achieving higher measurement precision while reducing mechanical complexity.
Solution Approach 2:
The patent introduces an intermediary image evaluation device that acts as a mediator between the camera system and the driver assistance system. This intermediary processes images and extracts meaningful information about processing losses, enabling accurate assessment without direct mechanical contact with the harvested material.
2Measurement precision
If image evaluation devices with machine learning algorithms are implemented, then the measurement precision of threshing quality improves, but the device complexity increases
Solution Approach 1:
The image evaluation device with machine learning algorithms performs self-service by automatically analyzing images and determining processing loss indicators without requiring manual intervention. The system self-adjusts and optimizes its evaluation criteria, reducing the need for complex external control mechanisms.
Solution Approach 2:
The patent implements a feedback loop where the image evaluation device continuously monitors the transferred harvested material flow and provides real-time information to the driver assistance system. This feedback enables dynamic adjustment of threshing parameters to optimize processing quality.
3Productivity
If the driver assistance system automatically controls working units based on image analysis, then the productivity increases through optimized operation, but the extent of automation increases system complexity
Solution Approach 1:
The driver assistance system uses feedback from the image evaluation device to automatically adjust working unit parameters. The system continuously monitors processing quality and makes real-time adjustments to optimize harvesting efficiency, creating a closed-loop control system that improves productivity through intelligent automation.
Solution Approach 2:
The patent replaces manual operation and simple mechanical control systems with an automated optical-digital-control system. The camera-based image analysis combined with machine learning algorithms enables sophisticated automatic control of working units, achieving high productivity through intelligent automation rather than mechanical complexity.
Data Source
AI summary
A combine harvester and a method for operating a combine harvester. The combine harvester includes a threshing device and a separating device as working units which process harvested material collected for separating grain and transfer a flow of harvested material containing substantially the grain to a cleaning device, which is another working unit. The cleaning device supplies a flow of harvested material containing unthreshed harvested material to the threshing device for rethreshing using a transfer device and supplies a cleaned flow of harvested material to a grain tank using a conveyor device. The combine harvester includes a camera system to recording images of the flow of material to be transferred and an image evaluation device to evaluate the images. A driver assistance system controls the working units based on indicators, determined by the image evaluation device evaluating the images, of processing losses caused by the working units.