3D Vision Polarity Detection for Stacked IC Components
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Solution Overview
Problem
Existing polarity detection methods for IC components fail to accurately detect stacked components and often result in component damage due to fixed lowering depth during manipulation, lacking flexibility and precision in handling diverse packaging types and shapes.
Innovation Solution
A method and apparatus utilizing three-dimensional machine vision technology to acquire and analyze images of stacked electronic components, calculating three-dimensional coordinates, and moving components to a polarity detection region for precise polarity recognition, avoiding damage by using a manipulator with adjustable depth based on calculated coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional two-dimensional visual positioning is used for loading and unloading, then the system is simple and easy to operate, but it cannot detect depth positions of stacked components causing damage and deformation
Solution Approach 1:
The patent transitions from two-dimensional visual positioning to three-dimensional machine vision by introducing depth detection capabilities. The system uses multiple cameras or structured light to capture depth information, enabling accurate positioning of stacked components in the Z-direction while maintaining system feasibility through integrated hardware-software solutions.
2Adaptability or versatility
If fixed lowering depth is used by manipulator, then the operation process is simple, but it causes damage and deformation of IC components due to inability to adapt to stacked components
Solution Approach 1:
The manipulator's lowering depth is changed from a fixed static value to a dynamic value that is automatically adjusted based on real-time depth detection. The system continuously receives depth information from the vision system and adjusts the manipulator's Z-position accordingly, enabling adaptive handling of stacked components without manual intervention.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where the vision system continuously monitors component positions and feeds depth information back to the manipulator control system. This feedback loop enables automatic adjustment of lowering depth to match the actual stack height, preventing damage while maintaining simple operation.
3Adaptability or versatility
If traditional two-dimensional visual loading and unloading is used, then the system structure is simple, but it lacks flexibility for different packaging types and shapes requiring manual setting
Solution Approach 1:
The system enables self-service operation by automatically recognizing different packaging types and shapes through three-dimensional vision, and autonomously adjusting loading/unloading parameters without manual intervention. The vision system captures depth information and the control algorithm automatically determines the optimal handling approach for each component type.
Solution Approach 2:
The system dynamically changes operational parameters such as lowering depth, gripper position, and approach angle based on the detected packaging type and shape. By automatically adjusting these parameters according to real-time depth detection data, the system adapts to different component configurations without requiring manual reconfiguration.
4Measurement precision
If polarity detection is performed without accurate depth detection, then the detection process is simple, but stacked components cannot be accurately identified leading to incorrect polarity recognition
Solution Approach 1:
The polarity detection system is enhanced by adding depth detection capability to the traditional two-dimensional vision system. By incorporating Z-axis information through stereoscopic vision or structured light, the system can accurately identify which component in a stack is the target and detect its polarity markings without interference from overlaid components.
Data Source
AI summary
The application relates to a polarity discrimination detection method and apparatus for multiple stacked electronic components and a device, and the method comprises the steps of: acquiring a collected image of a to-be-detected electronic component, and matching and positioning the collected image to obtain a positioning image; acquiring parameter data of a camera device, and carrying out stereo matching and image segmentation on the positioning image according to the parameter data to obtain three-dimensional coordinates; the to-be-detected electronic component to a polarity detection region through a manipulator according to the three-dimensional coordinates to acquire a detection image; analyzing the detection image to obtain polarity circle coordinates; and comparing the polarity circle coordinates with polarity circle standard coordinates arranged on the polarity detection region to obtain a polarity discrimination result.