Honeycomb Structure Mask Defect Detection Using Dual-Angle Imaging
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Solution Overview
Problem
The existing methods for detecting mask defects on honeycomb structure end surfaces are inefficient, often resulting in oversight and increased production costs due to reliance on visual observation, which can lead to clogging of cell open portions when mask tape does not stick properly.
Innovation Solution
A method involving the use of two distinct light beams, one at 45° or more and another at 5° or less with the central axis, to capture processing images of the end surface, allowing for the detection of mask tape defects by calculating the ratio of unplugged cells to the entire surface area and comparing it to a threshold value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If visual observation is used to detect mask defects, then the detection process is simple, but the detection precision is low and oversight occurs frequently
Solution Approach 1:
The patent replaces the mechanical/visual observation system with an optical imaging system. A camera captures images of the honeycomb structure end surface, and image processing algorithms automatically detect mask defects. This substitution eliminates human oversight while maintaining operational simplicity through automated image analysis.
Solution Approach 2:
The patent creates a visual copy (image) of the mask tape application state on the honeycomb structure end surface. By capturing and analyzing images, the system can inspect the masking quality without physical contact, enabling precise defect detection while keeping the detection process simple and non-intrusive.
2Productivity
If mask tape is not stuck properly on the end surface, then the application process is faster, but the cell open portions become clogged with bonding material
Solution Approach 1:
The patent implements a feedback mechanism where the imaging system detects the actual mask tape application state, and this information is used to verify whether the masking was successful. The system calculates the ratio of masked to unmasked cell open portions, providing feedback on the quality of the masking operation and enabling correction if defects are detected.
Solution Approach 2:
The patent performs detection of mask defects immediately after the masking operation, before the bonding process begins. This preliminary detection allows for correction of improper masking before it causes clogging, ensuring reliability without sacrificing the speed of the overall process.
3Device complexity
If manual visual inspection is used for mask defects, then the equipment cost is low, but the production cost increases due to oversight and rework
Solution Approach 1:
The patent enables the masking process to self-verify through automated image capture and analysis. The system automatically detects defects without requiring manual inspection, reducing labor costs and improving productivity. The self-service nature of the detection system eliminates human error while maintaining cost-effectiveness through automated rather than manual processes.
4Measurement precision
If two distinct light beams are used to capture images, then the mask defect detection precision is improved, but the device complexity increases
Solution Approach 1:
The patent applies different lighting conditions (two distinct light beams) to different aspects of the detection task. One light beam optimizes for capturing the overall mask tape application, while the other enhances detection of specific defect features. This local optimization of lighting quality improves detection precision without requiring a completely complex imaging 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 method effectively detects mask defects without manual intervention, reducing production costs and preventing clogging by accurately identifying areas where the mask tape is not stuck, thereby ensuring proper bonding and structure integrity.
Implementation Method 1
obtaining a first processing image by, while irradiating an end surface of a honeycomb structure which has undergone a step of sticking a transparent mask tape on the end surface with a first irradiation light beam which forms an angle of 45° or more with a central axis of the honeycomb structure, imaging the entire end surface
Implementation Method 2
obtaining a second processing image by, while irradiating the end surface with a second irradiation light beam which forms an angle of 5° or less with the central axis of the honeycomb structure, imaging the entire end surface
Data Source
Figure 1
AI summary
A method for detecting a mask defect of an end surface of a honeycomb structure includes the steps of: obtaining a first processing image by, while irradiating an end surface 6 of a honeycomb structure 1 which has undergone a step of sticking a transparent mask tape on the end surface 6 with a light beam (first irradiation light beam) 11 which forms an angle of 45° or more with a central axis a of the honeycomb structure 1, imaging the entire end surface 6 from the front side of the end surface 6, obtaining a second processing image by, while irradiating the end surface 6 with a light beam (second irradiation light beam) 12 which forms an angle of 5° or less with the central axis a of the honeycomb structure 1, imaging the entire end surface 6 from the front side of the end surface 6, and detecting a mask defect of the end surface 6 of the honeycomb structure 1 by calculating the ratio of the area of unsealed cells in a portion on which the mask tape is not stuck on the area of the entire end surface with the first processing image and the second processing image. The defect in the mask tape stuck on the end surface of the honeycomb structure can efficiently be detected by the method for detecting the mask defect of the end surface of the honeycomb structure.