Granular Material Quality Grading Criteria Automation
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Solution Overview
Problem
Existing discrimination devices for determining appearance quality grades of granular materials require skilled operators to create quality grade discrimination criteria, making it difficult for non-skilled operators to do so efficiently.
Innovation Solution
A method involving sorting granular materials by quality grade, capturing images, obtaining imaging data, and using machine learning algorithms to create quality grade discrimination criteria, allowing non-skilled operators to create criteria through a structured process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If quality grade discrimination criteria are created by obtaining imaging data of multiple sample grains and specifying quality grades while an operator visually confirms the imaging data, then quality grade discrimination criteria can be created, but it requires proficiency and is not easy to create the criteria
Solution Approach 1:
The discrimination device automatically creates quality grade discrimination criteria by itself without requiring skilled operators to manually specify quality grades. The device obtains imaging data of granular materials, extracts quality grade information automatically, and generates discrimination criteria through automated processing, thereby eliminating the need for operator proficiency in manual grading.
Solution Approach 2:
The manual visual confirmation and specification process by operators is replaced with an automated image processing system. The device uses imaging data and automated algorithms to extract quality grade information and create discrimination criteria, substituting human visual inspection and judgment with mechanical/optical detection and computational processing.
2Measurement precision
If skilled operators manually specify quality grades by visually confirming imaging data, then quality grade discrimination criteria can be created with accuracy, but the process is time-consuming and requires specialized skills
Solution Approach 1:
The discrimination device performs the entire quality grade discrimination criteria creation process automatically without human intervention. It obtains imaging data, extracts quality grade information through automated image processing, and generates discrimination criteria independently, eliminating both the time requirement and the need for skilled operators.
Solution Approach 2:
The automated system allows for continuous processing of imaging data to create quality grade discrimination criteria. Multiple granular materials can be processed sequentially without interruption, and the system can operate continuously to generate comprehensive discrimination criteria from multiple samples, significantly reducing the total time required compared to manual methods.
Data Source
AI summary
A method of creating quality grade discrimination criteria in a discrimination device that determines appearance quality grades of granular materials in accordance with the present invention includes a granular material placement step of sorting the granular materials on a per-quality-grade basis and placing the granular materials on an image-capture surface of the image-capturing unit; an imaging data acquisition step of capturing images of the granular materials placed on the image-capture surface by the image-capturing unit and thereby obtaining imaging data; a quality grade information acquisition step of obtaining, on a per-quality-grade basis, pieces of quality grade information on the respective granular materials on the basis of the imaging data; and a quality grade discrimination criteria creation step of creating quality grade discrimination criteria by using the quality grade information obtained on a per-quality-grade basis.