Grease Particle Detection via AI Image Recognition
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Solution Overview
Problem
Conventional methods for determining the status of lubricating grease require specialized equipment and lengthy detection times, making it difficult to quickly and accurately assess grease contamination levels in machinery.
Innovation Solution
A method using image recognition by artificial intelligence to determine the status of grease containing particles, involving sampling, spreading the grease on a filter membrane, and recording images with a microscope, followed by analysis to determine particle content and grease contamination levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional detection methods are used to determine grease status, then measurement accuracy can be maintained, but detection time becomes excessively long and equipment complexity increases
Solution Approach 1:
The patent replaces complex mechanical detection equipment with an optical imaging system combined with image processing algorithms. A microscope captures images of grease samples on filter membranes, and image processing methods automatically analyze particle content, eliminating the need for specialized laboratory equipment while dramatically reducing detection time from hours to minutes
Solution Approach 2:
The patent creates visual copies (images) of the grease sample on a filter membrane, which can then be analyzed without manipulating the actual grease. These images serve as replicas that contain all necessary information for status determination, allowing rapid analysis while preserving the original sample and enabling multiple analyses of the same sample
2Measurement precision
If conventional detection methods are used, then comprehensive grease analysis can be achieved, but the detection time and operational complexity increase significantly
Solution Approach 1:
The patent changes the measurement parameter from direct grease analysis to particle content analysis on a filter membrane. By filtering grease through a membrane and analyzing the retained particles visually, the method transforms a complex chemical/physical analysis into a simpler optical measurement that can be processed rapidly while maintaining accuracy in determining grease contamination status
Solution Approach 2:
The filter membrane serves as an intermediary between the grease sample and the imaging system. It concentrates and displays particles in a standardized format that is optimal for image capture and analysis, enabling rapid and accurate status determination without requiring direct analysis of the grease itself
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 method allows for quick and accurate determination of grease status at the site of the device, enabling timely maintenance and reducing the risk of equipment damage and increased maintenance costs.
Implementation Method 1
setting a magnification of the microscope, setting a distance of a lens of the microscope to the filter membrane
Implementation Method 2
making particles in the grease appear black with polarized light
Data Source
AI summary
A method for determining the status of grease containing particles by image recognition. The method may include sampling the grease and spreading the grease on a filter membrane. The method may also include image recording of the sampled grease by a microscope, which may include: setting a magnification of the microscope, setting a distance of a lens of the microscope to the filter membrane, and/or recording an image of the sampled grease by the microscope. The method may also include performing image recognition in the image by artificial intelligence and determining a particle content in the grease. The method may also include determining the status of the grease based on the particle content.