Optical Sensor Grain Loss Detection for Harvesting Headers
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Solution Overview
Problem
Current methods for assessing the working quality of agricultural harvesting headers are unreliable, as they often misinterpret stubble quality, leading to incorrect adjustments and increased crop losses, especially in normal operating conditions, while ignoring losses occurring at the harvesting header that do not enter the machine.
Innovation Solution
Implementing a software-supported image evaluation using optical sensors to determine the number of lost grains in image data sets, which provides a more accurate assessment of the harvesting header's efficiency and allows for real-time adjustments of the harvesting machine's speed and component settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If stubble quality is used as the basis for assessing working quality, then the assessment can be performed based on visual inspection of the cut area, but the assessment becomes unreliable and leads to incorrect adjustments
Solution Approach 1:
The patent replaces manual visual assessment of stubble quality with an automated optical sensor system that captures images and uses software-supported evaluation to count lost grains. This substitution of mechanical/visual inspection with optical detection and image processing resolves the contradiction by providing both ease of operation (automated assessment) and high reliability (objective grain counting).
Solution Approach 2:
The patent introduces an intermediary system consisting of optical sensors and evaluation electronics that mediate between the harvested area and the assessment process. This intermediary captures image data sets and processes them to determine the number of lost grains, providing a reliable bridge between the physical harvesting process and the quality assessment, thereby resolving the unreliability of direct visual inspection.
2Measurement precision
If the number of lost grains is determined through software-supported image evaluation, then the measurement precision of grain losses improves, but the device complexity increases due to additional optical sensors and processing electronics
Solution Approach 1:
The patent extracts only the essential information needed for assessment - the number of lost grains - from the complex task of evaluating overall harvesting quality. By using optical sensors to capture images and software to specifically count lost grains rather than进行全面 quality assessment, the system achieves high measurement precision while managing device complexity through focused data extraction.
Solution Approach 2:
The patent creates an optical copy (image data set) of the harvested area that can be processed and analyzed without physically interfering with the harvesting process. This copying approach allows for precise grain loss measurement through image analysis while keeping the physical sensor system relatively simple, as the complexity is shifted to software processing of the optical copy rather than complex mechanical sensing.
3Productivity
If real-time image evaluation is performed to determine lost grains, then the productivity of the harvesting process improves through optimized settings, but the use of energy increases due to continuous operation of optical sensors and processing systems
Solution Approach 1:
The patent implements continuous image evaluation during the harvesting process, with optical sensors continuously capturing image data sets and the evaluation electronics continuously processing this data to determine lost grains. This continuous operation enables real-time optimization of harvesting parameters, maintaining high productivity while managing energy consumption through efficient continuous processing rather than intermittent measurements.
Solution Approach 2:
The patent establishes a feedback loop where image evaluation results regarding lost grains are used to adjust harvesting parameters in real-time. This feedback mechanism allows the system to optimize productivity by continuously adapting harvesting settings based on actual grain loss measurements, while the energy consumption is justified by the productivity gains achieved through this closed-loop control system.
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 approach enables statistically reliable determination of grain losses, allowing for optimized settings of the harvesting header and machine, reducing overall crop losses and improving operational efficiency by accurately assessing the loss level and adjusting the forward speed based on real-time data.
Implementation Method 1
optical sensor (6) directed to an area (12) worked by the harvesting header (4)
Data Source
AI summary
The present invention relates to a method for determining operating parameters of an agricultural harvesting header device (4) by way of software-aided image evaluation (10) of image datasets (100) from an optical sensor (6) in evaluation electronics (8) aimed at an area (12) cultivated by the harvesting header device (4). The invention also relates to a harvester having a data processing device and to a computer program product. In order to develop a method in which an operating parameter is acquired and evaluated and which is better suited to assessing the operating quality of the agricultural harvesting header device and to optimizing the settings of the components thereof, it is proposed for the image evaluation (10) of the image datasets (100) generated by the optical sensor (6) to be aimed at at least approximately determining a value (102) of the number of lost grains (22) able to be identified in the image dataset (100) as operating parameter.