18524990. MACHINE VISION DETECTION METHOD, DETECTION APPARATUS AND DETECTION SYSTEM THEREOF simplified abstract (CONTEMPORARY AMPEREX TECHNOLOGY CO., LIMITED)
Contents
- 1 MACHINE VISION DETECTION METHOD, DETECTION APPARATUS AND DETECTION SYSTEM THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MACHINE VISION DETECTION METHOD, DETECTION APPARATUS AND DETECTION SYSTEM THEREOF - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does this technology compare to traditional methods of measuring component gaps in manufacturing processes?
- 1.11 What are the potential challenges in implementing this machine vision detection method in real-world industrial settings?
- 1.12 Original Abstract Submitted
MACHINE VISION DETECTION METHOD, DETECTION APPARATUS AND DETECTION SYSTEM THEREOF
Organization Name
CONTEMPORARY AMPEREX TECHNOLOGY CO., LIMITED
Inventor(s)
MACHINE VISION DETECTION METHOD, DETECTION APPARATUS AND DETECTION SYSTEM THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 18524990 titled 'MACHINE VISION DETECTION METHOD, DETECTION APPARATUS AND DETECTION SYSTEM THEREOF
Simplified Explanation
The machine vision detection method described in the abstract involves analyzing a three-dimensional image to determine the gap between two components in a grayscale image. The method includes converting the three-dimensional image into a two-dimensional grayscale image, identifying the boundaries of the components, and calculating the average length of perpendicular lines between the boundaries to determine the gap size.
- Receiving a three-dimensional image from a line laser
- Converting the three-dimensional image into a two-dimensional grayscale image
- Obtaining boundaries of two components in the grayscale image
- Determining perpendicular lines between the boundaries
- Calculating the average length of the perpendicular lines as the gap size
Potential Applications
This technology can be applied in industries such as manufacturing, quality control, and robotics for precise gap detection in components and welding spots.
Problems Solved
This technology solves the problem of accurately measuring the gap between components in a non-contact and efficient manner, improving the quality and reliability of manufacturing processes.
Benefits
The benefits of this technology include increased accuracy in detecting component gaps, improved efficiency in quality control processes, and enhanced productivity in manufacturing operations.
Potential Commercial Applications
- "Precision Gap Detection Technology for Manufacturing Processes"
Possible Prior Art
There may be prior art related to machine vision systems for gap detection in industrial applications, but specific examples are not provided in this context.
Unanswered Questions
How does this technology compare to traditional methods of measuring component gaps in manufacturing processes?
This article does not provide a direct comparison between this technology and traditional methods of measuring component gaps. A comparative study could shed light on the advantages and limitations of this innovative approach.
What are the potential challenges in implementing this machine vision detection method in real-world industrial settings?
The article does not address the potential challenges that may arise in implementing this technology in industrial environments. Factors such as calibration, lighting conditions, and system integration could be critical considerations for successful deployment.
Original Abstract Submitted
A machine vision detection method includes receiving a three-dimensional image from a line laser, converting the three-dimensional image into a two-dimensional grayscale image, obtaining a boundary of a first component and a boundary of a second component in the two-dimensional grayscale image, determining N perpendicular lines between the boundary of the first component and the boundary of the second component, and calculating an average length of the N perpendicular lines as a gap between the first component and the second component. The three-dimensional image includes at least a portion of the boundary of the first component, at least a portion of the boundary of the second component, and a welding spot located on the boundary of the first or second component. N is a positive integer.
