Stator Winding Weld Inspection Using 3D Blob-Derivative Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional quality control methods for welding joints in inductive windings of stators rely on human operators, which are time-consuming, costly, and prone to inaccuracies due to subjective measurements and the complexity of analyzing welding joints from limited viewpoints.
Innovation Solution
A method utilizing a computer to perform a 3D reconstruction of the welding joint, extract 2D grayscale blob areas, convert them into a distance-dependent function, calculate first and second derivatives, and identify instability peaks to objectively determine the base and height of the welding joint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators perform visual inspection of welding joints, then quality control can be conducted, but the process becomes time-consuming and costly
Solution Approach 1:
The patent replaces the mechanical visual inspection process performed by human operators with an automated optical measurement system. The system uses a camera to capture images of welding joints and processes these images through computational algorithms to automatically determine quality parameters such as reinforcement height and joint geometry, eliminating the need for manual measurement while maintaining or improving accuracy.
Solution Approach 2:
The patent introduces an intermediary computational processing stage between image capture and quality assessment. The system extracts geometric features from images, calculates derived parameters through mathematical operations, and uses these intermediate calculations to objectively determine welding quality, thereby automating the inspection process and reducing both time and human involvement.
2Reliability
If human operators measure welding joint parameters, then quality assessment is possible, but measurement accuracy deteriorates due to subjectivity
Solution Approach 1:
The patent replaces subjective human measurement with objective computational measurement. The system uses image processing algorithms to automatically calculate welding joint parameters such as reinforcement height, joint width, and geometry based on captured images, eliminating human subjectivity and measurement variability while improving consistency and accuracy.
Solution Approach 2:
The patent creates a digital copy of the welding joint through image capture and processing. Instead of direct physical measurement by human operators, the system generates a digital representation of the joint geometry and performs measurements on this copy, ensuring objectivity and repeatability while preserving all geometric information.
3Productivity
If automated optical measurement is implemented, then inspection speed increases, but system complexity increases
Solution Approach 1:
The patent replaces complex manual measurement procedures with a standardized optical measurement system. By using a camera to capture images and automated algorithms to process them, the system achieves high inspection speed while managing complexity through software-based solutions rather than mechanical complexity.
Solution Approach 2:
The patent creates a universal measurement system that can assess multiple welding joint parameters from a single image capture. The system extracts various geometric features and quality metrics simultaneously, making the system highly productive while the complexity is amortized across multiple measurement functions.
Data Source
AI summary
A method for quality control of a welding joint between a pair of ends of conducting elements of an inductive winding of a stator, the method being performed by a computer and comprising the steps of:acquiring a 3D reconstruction of the welding joint;extracting a plurality of 2D grayscale blob areas from the 3D reconstruction of the welding joint;converting the plurality of 2D grayscale blob areas to a function of 2D grayscale blob areas which depends on a distance from a peak of the welding joint with respect to each 2D grayscale blob area;calculating a respective first derivative of the function of 2D grayscale blob areas;calculating a respective second derivative of the function of 2D grayscale blob areas; andseeking instability peaks in a trend of the second derivative of the function of 2D grayscale blob areas.