Automated Borescope Imaging for Adaptive Defect Detection
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Solution Overview
Problem
Existing non-destructive testing (NDT) devices for industrial equipment rely on human operators for defect identification, which is slow, expensive, and prone to errors, and do not easily allow for re-acquisition of inspection images when defects are not adequately identified.
Innovation Solution
An automated system using a borescope with a camera and light source, controlled by a controller, that identifies defects through image interpretation algorithms, determines the need for new images, and adjusts camera and light source positions/orientations to acquire high-resolution, stereoscopic, or 3D images as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators manually identify defects using NDT devices, then defect detection can be performed, but the process is slow, expensive, and prone to errors
Solution Approach 1:
The system enables automated defect identification through image interpretation algorithms that analyze inspection images without human intervention. The controller automatically processes images, identifies defects, and determines whether re-acquisition is needed, making the system self-sufficient and eliminating manual operator dependency.
Solution Approach 2:
The patent replaces the mechanical human operator's visual inspection process with an automated image interpretation algorithm. The controller uses computational algorithms to analyze images, calculate defect probability values, and make determination about re-acquisition, substituting human cognitive functions with automated computational processes.
2Reliability
If human operators manually review inspection images, then defects can be identified, but the process is time-consuming and expensive
Solution Approach 1:
The system performs automated defect identification through image interpretation algorithms that process inspection images without requiring manual human review. The controller automatically analyzes images, calculates defect probability values by comparing with database images, and determines whether re-acquisition is needed, eliminating time-consuming manual operations.
Solution Approach 2:
The automated system enables continuous inspection operations without interruption by human operators. The image interpretation algorithm continuously processes images as they are acquired, and the controller can immediately determine whether re-acquisition is needed and adjust device orientation accordingly, maintaining uninterrupted inspection flow.
3Ease of operation
If the inspection device captures a single image, then the inspection process is simple, but defects may not be adequately identified requiring re-acquisition
Solution Approach 1:
The system implements a feedback mechanism where the controller receives the image, processes it through image interpretation algorithms, calculates a defect probability value, and compares it with a threshold. Based on this feedback, the controller automatically determines whether re-acquisition is needed and adjusts the device orientation if necessary, creating a closed-loop inspection process that improves reliability without increasing operational complexity.
Solution Approach 2:
The inspection process is made dynamic and adaptive rather than static. The controller automatically adjusts the device orientation based on the defect probability value and threshold comparison, allowing the inspection process to adapt to the specific characteristics of each inspection target and improve defect identification confidence.
4Device complexity
If the camera and light source positions are fixed, then the device structure is simple, but high-resolution and stereoscopic images cannot be acquired when needed
Solution Approach 1:
The camera and light source positions are made variable rather than fixed. The controller can adjust the orientation of the camera and light source to optimal positions for acquiring high-resolution images or stereoscopic pairs, allowing the device to adapt its configuration based on the specific inspection requirements and defect characteristics.
Solution Approach 2:
The system transitions from fixed two-dimensional imaging to variable three-dimensional positioning. By enabling adjustment of camera and light source orientations in multiple dimensions, the system can acquire stereoscopic images and high-resolution views from different angles, adding spatial dimensionality to the inspection capability.
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.