Metal Wire Crack Detection Using Dark-Field Image Processing
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Solution Overview
Problem
Existing methods for detecting crack defects in electrical circuits, particularly in metal wires of electronic products, suffer from low accuracy and inefficiency due to micro-cracks not causing short circuits early on and complex environmental backgrounds.
Innovation Solution
An image processing method involving high-angle dark-field lighting, binarization, boundary sharpening, and image recognition using a large target surface industrial camera and industrial telecentric lens to enhance crack feature capture and reduce background interference, followed by image recognition with models like convolutional neural networks to detect cracks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrical continuity measurement is used to detect crack defects, then the detection method is simple, but the detection accuracy is low because micro-cracks do not cause short circuits in early stages
Solution Approach 1:
The patent replaces electrical measurement methods with optical imaging methods. Instead of measuring electrical continuity to detect cracks, the system uses industrial cameras, telecentric lenses, and image processing algorithms to visually capture and analyze crack features on metal wire surfaces, thereby achieving high-precision detection of micro-cracks without relying on electrical property changes
Solution Approach 2:
The patent creates an optical copy (image) of the metal wire surface and processes this copy to detect cracks. The imaging system captures the surface morphology, and image processing algorithms analyze the captured images to identify crack defects, allowing non-contact, high-precision detection without altering the original object
2Productivity
If manual visual inspection is used to detect cracks, then the detection accuracy can be high, but the detection efficiency is low
Solution Approach 1:
The patent implements an automated detection system that performs inspection without human intervention. The imaging system automatically captures images, and the image processing algorithm automatically analyzes the images to detect cracks, eliminating the need for manual visual inspection while maintaining high detection accuracy and significantly improving productivity
Solution Approach 2:
The patent replaces manual visual inspection with an automated optical inspection system. The system uses industrial cameras, telecentric lenses, and computer-based image processing to automatically detect cracks, substituting human operators with automated equipment that provides both high efficiency and consistent accuracy
3Measurement precision
If conventional imaging methods are used, then the imaging system is simple, but the ability to capture crack features and reduce background interference is insufficient
Solution Approach 1:
The patent applies telecentric lens technology to achieve uniform magnification and eliminate perspective distortion across the entire field of view. This ensures that crack features at different positions in the image maintain consistent size and clarity, enhancing the ability to capture and measure crack dimensions accurately
Solution Approach 2:
The patent employs asymmetric lighting configuration with light sources positioned at specific angles to create directional illumination that highlights crack features while suppressing background reflections. The lighting geometry is optimized to cast shadows that enhance the visibility of surface defects against the metallic background
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
Improves the accuracy and efficiency of crack defect detection by directly identifying cracks through image processing, overcoming the limitations of electrical continuity measurement and manual visual inspection.
Implementation Method 1
as shown in the schematic diagram of the optical path, the light source is incident between the industrial telecentric lens and the metal wire surface to be detected
Data Source
AI summary
Method for processing an image, a computer-readable storage medium, and an electronic device. The method includes: acquiring a mark area in an original wiring image, and determining a first to-be-detected region of the original wiring image based on the mark area; performing boundary sharpening on the first to-be-detected region to determine a second to-be-detected region, and generating a target detection image based on the first to-be-detected region and the second to-be-detected region; and performing image recognition on the target detection image to detect a crack defect included in the original wiring image.