Optical Component Self-Diagnosis Using Light Pattern Correlation
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Solution Overview
Problem
Existing automated vision-based sample inspection systems face challenges in accurately detecting defects in optical components such as scratches or dirt particles on lighting and sensors, which can impact inspection accuracy, and manual visual inspection is cumbersome and disruptive.
Innovation Solution
The system uses independently controllable LEDs to generate different light intensity patterns for optical components, comparing captured images to identify defects by analyzing consistent areas between patterns, without requiring additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual visual inspection is used to detect defects in optical components, then inspection capability is provided, but system downtime increases and operational efficiency decreases
Solution Approach 1:
The system performs self-diagnosis by using the existing inspection system components (light panels and sensors) to automatically detect defects in optical components. The control system captures images, processes them through image correlation analysis, and identifies defects without requiring manual intervention, thereby maintaining continuous operation while ensuring quality control.
2Measurement precision
If manual disassembly is performed to inspect optical components, then defect detection is enabled, but system complexity and operational disruption increase
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated optical inspection system. The control system uses image capture devices and image correlation algorithms to detect defects in light panels and sensors while the system remains assembled and operational, eliminating the need for disassembly and maintaining operational continuity.
3Extent of automation
If additional hardware is added to enable autonomous diagnostic verification, then automation capability is improved, but device complexity increases
Solution Approach 1:
The patent makes the existing light panels and sensors serve dual functions: their primary function for sample inspection and a secondary function for self-diagnosis. The control system activates different light patterns and captures images using the same hardware components, enabling autonomous defect detection without adding specialized diagnostic equipment.
Solution Approach 2:
The system creates a digital copy or representation of the optical components by capturing images with the sensor array. These image copies are then processed through correlation analysis to detect defects, allowing virtual inspection of the physical components without physical intervention or additional hardware.
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
Enables autonomous detection of defects in optical components, ensuring system uptime by avoiding manual disassembly and enhancing inspection accuracy through image correlation analysis.
Implementation Method 1
a sensor array, such as an image capture device, can be used to capture a digital image of the light panel
Data Source
Figure 1A
Figure 1B~1C
Figure 2A~2B
AI summary
Methods of autonomous diagnostic verification and detection of defects in the optical components of a vision-based inspection system are provided. The method includes illuminating a light panel with a first light intensity pattern, capturing a first image of the first light intensity pattern with a sensor, illuminating the light panel with a second light intensity pattern different than the first light intensity pattern, capturing a second image of the second light intensity pattern with the sensor, comparing the first image and the second image to generate a comparison of images, and identifying defects in the light panel or the sensor based upon the comparison of images. Systems adapted to carry out the methods are provided as are other aspects.