Forage Harvester Grain Size Control via Image Analysis
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Solution Overview
Problem
Conventional forage harvesters face challenges in producing chopped material that is energy-efficient and finely ground enough for biogas production or animal feed, with difficulties in assessing the optimal degree of comminution and distinguishing between necessary and excessive shredding, leading to inefficient energy use.
Innovation Solution
A method that uses image analysis to determine the thickness of grain fractions by counting or weighing particles, allowing for a more precise assessment of comminution quality, independent of grain proportions, and automatically adjusts the after-treatment device settings based on target distributions for optimal grain size adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the cracker gap is narrowed or the speed difference between rollers is increased to reduce intact grains, then the proportion of intact grains decreases, but the drive energy consumption increases
Solution Approach 1:
The patent employs a camera-based detection system that captures images of the chopped material and uses image analysis to determine the proportion of intact grains. This real-time feedback is transmitted to a control unit that automatically adjusts the cracker gap width or roller speed difference, enabling closed-loop control to maintain optimal grain comminution while minimizing energy consumption.
Solution Approach 2:
The control system dynamically adjusts physical parameters of the post-treatment device, specifically the cracker gap width and/or the speed difference between rollers, based on detected grain proportions. This allows the system to optimize the mechanical action on grains adaptively, achieving effective comminution only when necessary and reducing energy expenditure when grain breakdown is already sufficient.
2Manufacturing precision
If the degree of shredding is increased to reduce intact grains, then the grain size becomes finer, but it becomes difficult to distinguish optimal shredding from unnecessarily fine shredding
Solution Approach 1:
The patent replaces manual or mechanical assessment methods with an optical measurement system. A camera captures images of the chopped material, and image analysis algorithms automatically determine grain size distribution and comminution quality. This substitution enables precise, objective measurement of shredding degree without relying on subjective visual assessment or complex mechanical gauges.
Solution Approach 2:
The patent introduces an intermediary evaluation step where image analysis determines the thickness or size distribution of grain fractions before this information is used for control decisions. This intermediary layer translates complex visual information about grain comminution into quantifiable metrics that can be directly compared against target values, simplifying the control process.
3Measurement precision
If image analysis is used to assess grain proportions, then the assessment becomes more accurate, but the processing effort increases
Solution Approach 1:
The patent performs preliminary classification of particles into grain-like and non-grain-like categories based on image analysis. By pre-sorting particles into these categories before detailed measurement, the system reduces the computational burden of full image processing. Only grain-like particles require precise thickness measurement and comparison against target distributions, significantly reducing overall processing effort.
Solution Approach 2:
The image analysis process is segmented into distinct steps: first identifying and sorting grain-like particles from non-grain particles, then measuring thickness of identified grains, and finally comparing against target distributions. This segmentation allows the system to apply different processing intensities to different particle types, reducing unnecessary computation on non-grain material while maintaining accurate grain assessment.
Data Source
Figure 1~2
Figure 3
AI summary
Method for operating a forage harvester (1) comprising the steps a) recording (S1) images of chopped material produced in the forage harvester (1) with a camera (16) , b) identifying (S2) images of granular particles (22-25) in the images, c) sorting the images of the granular particles (22-25) into at least two size fractions (S3-S5), and d) determining (S6) the thickness of the size fractions.