Tube Bending Angle Detection Using ROI Image Fitting
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Solution Overview
Problem
Existing tube bending processes face inaccuracies due to material springback, leading to unstable product quality and high unqualified rates, with existing detection methods being inefficient, costly, and lacking universality.
Innovation Solution
A method and system for detecting bending angles using image processing, involving binarization and extraction of region of interest (ROI) from tube images, followed by linear fitting to calculate the bending angle, integrated with an online detection system for real-time feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If three-dimensional laser scanners are used to measure bending angles, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces complex mechanical measurement systems (laser scanners, IMU sensors) with a simplified optical imaging system using ordinary cameras. The bending angle is measured by capturing images of the tube and processing them through image recognition algorithms, substituting mechanical/physical measurement mechanisms with optical-electric-conversion and computational methods.
Solution Approach 2:
The patent creates a digital copy (image) of the physical tube and performs measurements on this copy through image processing. Instead of directly measuring the physical tube with complex equipment, the system captures visual information and extracts bending angle data from the image representation, simplifying the measurement process.
2Device complexity
If offline quality control procedures are used, then device complexity is reduced, but productivity and detection efficiency deteriorate
Solution Approach 1:
The patent implements continuous online detection during the tube bending process rather than intermittent offline inspection. The imaging system continuously captures images of the bending tube, and the processing system continuously analyzes these images to provide real-time bending angle data, ensuring uninterrupted quality monitoring throughout production.
Solution Approach 2:
The system performs self-detection and self-adjustment by automatically capturing images, processing them through recognition algorithms, and using the results to control the bending process. The detection system is integrated with the processing system, enabling automatic feedback control without requiring separate manual inspection steps.
3Measurement precision
If mandrel-based IMU embedding is used for springback measurement, then measurement precision is improved, but adaptability deteriorates as it is only applicable to mandrel-based tube bending
Solution Approach 1:
The patent develops a universal detection method based on optical imaging that can measure bending angles for various tube bending techniques including mandrel-based, roller-based, and other methods. The image processing algorithm identifies key geometric features of the bent tube regardless of the specific bending mechanism used, making the system broadly applicable across different tube bending processes.
Data Source
AI summary
The present disclosure discloses a bending angle detection method for tube bending. The detection method includes the following steps: binarizing a to-be-recognized image and extracting a region of interest (ROI) to obtain binary images of two linear segment regions, where the to-be-recognized image is an image of a bent tube; and calculating a bending angle according to the binary images of the two linear segment regions. The present disclosure provides an online method and system for measuring a bending angle based on images, which is cost-effective and has high efficiency and strong universality.