Grain Separation Automation with 360-Degree Vision and Weighing
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Solution Overview
Problem
Current grain classification processes in agriculture rely heavily on human intervention, leading to errors and inconsistencies due to human factors, and existing automated systems only partially automate the process, lacking comprehensive 360-degree analysis and weighing capabilities.
Innovation Solution
A comprehensive equipment system that automates the separation, identification, classification, and quantification of grains by using a combination of imaging, robotic arms, and weighing mechanisms to analyze grains from all sides, with a 360-degree vision system and laser depth identification, allowing for precise classification and quantification of grain types and impurities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human action is used for grain classification, then the process can be performed with simple equipment, but errors and inconsistencies occur due to human factors
Solution Approach 1:
The patent replaces the manual mechanical classification system with an automated optical-mechanical system. A vision system captures images of grains, a processor analyzes them using algorithms to identify defects, and a robotic arm executes separation actions, eliminating human subjectivity and error while maintaining classification accuracy
Solution Approach 2:
The system enables self-service classification by equipping the grain inspection system with autonomous capabilities. The vision system automatically detects grain characteristics, the processor independently makes classification decisions based on predefined criteria, and the robotic arm autonomously separates grains without human intervention, making the system self-sufficient in the classification task
2Extent of automation
If existing automated equipment is used, then some operations are automated, but the system only analyzes the top of grains and does not provide weighing capabilities
Solution Approach 1:
The patent transitions from two-dimensional top-view imaging to three-dimensional analysis by incorporating a robotic arm that positions the imaging system to view grains from multiple angles including side and bottom perspectives. This multi-dimensional approach enables complete grain inspection, detecting defects on all surfaces that single-angle systems miss
Solution Approach 2:
The system merges multiple previously separate functions into a single integrated platform: the vision system for imaging, the processor for analysis, the robotic arm for manipulation, and the weighing mechanism for quantification. This consolidation enables simultaneous execution of inspection, classification, separation, and weighing operations, providing comprehensive grain analysis capability
3Productivity
If manual grain classification is performed, then equipment complexity is low, but productivity and consistency are limited by human capacity
Solution Approach 1:
The patent segments the grain classification task into distinct functional modules: grain feeding mechanism, multi-angle imaging system, image processing and analysis module, robotic arm control system, and weighing mechanism. Each module performs a specific function, allowing independent optimization and maintenance while working together to achieve high-speed automated classification with enhanced productivity
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
The system significantly reduces human error by enabling full automation of grain classification and quantification, providing accurate 360-degree analysis and precise weighing, ensuring consistent quality control and compliance with international standards.
Implementation Method 1
a laser system identifies the good and bad grains
Implementation Method 2
a laser system identifies the good and bad grains
Implementation Method 3
a vision system makes images of all grains
Data Source
AI summary
The present application is related to the process of automation of separation by identification, classification and quantification of grains and their possible pertinent materials through equipment that performs such events, aiming at the automation of the whole chain of separation, identification and classification. grain, thus eliminating the human action of the process and thus avoiding errors related to human interaction in the process. This process has 4 steps, as follows: grain and impurities entering the equipment; separation of impurities and grains: grain processing and qualitative and quantitative identification of grains and impurities. The process and equipment can be applied to the separation by identification, classification and quantification of grains such as soybeans, corn, among others, and their possible pertinent materials.