Borescope Image Repositioning for Automated Defect Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video inspection devices for industrial machines require manual analysis by human operators, which is slow, expensive, and prone to errors, and do not facilitate easy acquisition of new images if the initial inspection region image is inadequate for defect identification.
Innovation Solution
An automated system using a borescope with a camera and light source, controlled by a controller, that identifies defects, determines the need for new images, and adjusts camera and light source positions/orientations to acquire high-resolution, stereoscopic, or 3D images for accurate defect detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis by human operators is used, then defect identification can be performed, but the process is slow, expensive, and prone to errors
Solution Approach 1:
The inspection system performs self-service by automatically analyzing captured images to identify defects, eliminating the need for human operator intervention. The processor automatically processes images from the camera, compares them against stored reference images, and identifies defects without human assistance, thereby improving both speed and consistency of inspection.
Solution Approach 2:
The patent replaces the mechanical/human inspection system with an automated electronic system. Instead of human operators visually inspecting components, the system uses a camera to capture images, a processor to analyze them, and automated comparison algorithms to identify defects, substituting human cognitive processing with electronic computation.
2Reliability
If manual analysis by human operators is used, then defect identification can be performed, but operational costs are high
Solution Approach 1:
The inspection system performs self-service by automatically analyzing captured images to identify defects, eliminating the need for human operator intervention. The processor automatically processes images from the camera, compares them against stored reference images, and identifies defects without human assistance, thereby improving both speed and consistency of inspection.
Solution Approach 2:
The patent replaces the mechanical/human inspection system with an automated electronic system. Instead of human operators visually inspecting components, the system uses a camera to capture images, a processor to analyze them, and automated comparison algorithms to identify defects, substituting human cognitive processing with electronic computation.
3Measurement precision
If the initial inspection region image is inadequate for defect identification, then re-inspection is required, but acquiring new images is cumbersome
Solution Approach 1:
The system incorporates feedback by automatically evaluating the quality of captured images and determining whether re-inspection is needed. The processor compares captured images against stored reference images and automatically identifies when the initial image is inadequate, triggering automated re-positioning and re-capture without manual intervention, thus reducing time loss.
Solution Approach 2:
The system performs preliminary actions by pre-positioning the camera and light source at optimal locations before inspection begins. The system captures multiple reference images at different positions and orientations in advance, storing them in a database for rapid comparison during actual inspection, thereby reducing the time needed for re-inspection when initial images are inadequate.
4Measurement precision
If multiple images are captured from different positions and orientations, then defect identification accuracy improves, but the complexity of the inspection process increases
Solution Approach 1:
The inspection process is segmented into distinct automated steps: the camera captures images at specific positions, the processor compares captured images against stored reference images, and the system automatically determines when re-inspection is needed. This segmentation of the inspection process into automated sub-tasks reduces overall complexity despite capturing multiple images from different positions and orientations.
Data Source
AI summary
A method of nondestructive testing includes receiving data characterizing an image of an inspection region of an industrial machine acquired by an inspection device configured to inspect the inspection region. The inspection device includes a camera and a light source. The camera has a first position and a first orientation and the light source has a second position and a second orientation when the image is acquired. The method also includes identifying a defect in the inspection region of the industrial machine based on the received data characterizing the image of the inspection region. The method further includes determining that a new image of the inspection region needs to be acquired. The method also includes varying one or more of position of the camera, orientation of the camera, position of the light source and orientation of the light source.