Multi-Channel Lighting Optimization for Edge and Defect Inspection
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Solution Overview
Problem
Existing machine vision inspection systems face challenges in effectively inspecting workpieces due to variations in surface types and inspection operations, requiring improvements for enhanced precision and adaptability.
Innovation Solution
A system comprising a lens, camera, lighting configuration, processors, and memory that allows for selecting lighting optimization modes and adjusting lighting settings for multiple channels simultaneously, enabling improved edge detection, defect detection, and points from focus processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple lighting channels are used to illuminate the workpiece, then the quality of inspection images is improved, but the complexity of controlling and adjusting lighting settings increases
Solution Approach 1:
The lighting system is divided into multiple independently controllable channels, each capable of being adjusted separately to optimize illumination for different workpiece features or inspection requirements. This segmentation allows precise control over lighting characteristics while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The lighting channels are made dynamically adjustable, allowing real-time modification of lighting settings based on the specific inspection task and workpiece characteristics. This dynamic capability enables optimization of image quality without requiring complex hardware, as the control complexity is managed through software-based adjustment mechanisms.
2Measurement precision
If lighting settings are adjusted individually for each channel, then optimal illumination can be achieved, but the time required for setup and adjustment increases
Solution Approach 1:
Multiple lighting channels are grouped into controllable sets or presets that can be adjusted simultaneously. This merging approach allows operators to optimize illumination for entire groups of channels at once rather than individually, significantly reducing setup time while maintaining the ability to achieve optimal illumination for each specific inspection requirement.
Solution Approach 2:
Lighting configurations are pre-optimized for common inspection scenarios and stored as presets. This preliminary action eliminates the need for time-consuming setup adjustments during actual inspection tasks, as operators can simply select pre-optimized lighting settings that match the workpiece type and inspection requirements.
3Adaptability or versatility
If the system is designed to handle various workpiece surfaces and inspection operations, then adaptability is improved, but the difficulty of detecting and measuring different features increases
Solution Approach 1:
The lighting system provides localized illumination control, allowing different regions or channels to be optimized for specific workpiece features or surfaces. This enables the system to adapt to various inspection requirements by selectively adjusting lighting characteristics for specific areas, making feature detection easier rather than more difficult.
Solution Approach 2:
The system incorporates feedback mechanisms that automatically adjust lighting settings based on captured images and inspection results. This feedback loop simplifies the detection and measurement of different features by continuously optimizing lighting conditions, reducing the manual intervention required and making the system more adaptable to various workpiece surfaces and inspection operations.
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
Enhances the precision and adaptability of machine vision inspection systems by optimizing lighting for various workpiece surfaces and inspection types, improving edge detection, defect detection, and metrology operations.
Implementation Method 1
The lens (e.g., an objective lens) is configured to input image light arising from a workpiece, wherein the lens is configured to transmit the image light along an imaging optical path
Implementation Method 2
The lighting configuration comprises lighting channels configured to illuminate the workpiece for producing the image light
Data Source
AI summary
A system is provided including a lens, a camera, a lighting configuration, one or more processors, and a memory. The lens is configured to input image light arising from a workpiece and to transmit the image light along an imaging optical path. The camera is configured to receive the image light and to provide images of the workpiece. The lighting configuration comprises lighting channels configured to illuminate the workpiece for producing the image light. In various implementations, an option is provided for selecting a lighting optimization mode that that is at least one of an edge detection lighting optimization mode, a defect detection lighting optimization mode or a points from focus lighting optimization mode. A lighting optimization process may be performed based on the selected lighting optimization mode, and determines lighting for illuminating the workpiece for which the determined lighting comprises settings for the lighting channels of the lighting configuration.