Automated Defect Detection in Engine Blades Using Multi-Camera Mosaicing
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Solution Overview
Problem
Current automated inspection techniques for images captured by borescopes, such as those used in aircraft engine blade inspection, are prone to errors due to human inattention and struggle to detect defects outside pre-defined classes, necessitating an improved method for automated defect detection that minimizes human intervention and categorization.
Innovation Solution
The system employs multiple image capture devices to capture and transmit images, determining feature correspondence, creating mosaiced images through frame-to-frame and frame-to-mosaic registration, and performing automated analysis using Robust Principal Component Analysis to detect defects in engine blades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If human inspectors manually examine images for defect detection, then flexibility in detecting various defect types is maintained, but detection accuracy deteriorates due to human inattention and errors
Solution Approach 1:
The patent replaces the mechanical human inspection system with an automated computer-based inspection system that uses image processing algorithms to detect defects. This substitution eliminates human inattention and errors while maintaining the ability to detect various defect types through programmable analysis methods.
Solution Approach 2:
The inspection system performs self-analysis of images using automated algorithms that independently identify and classify defects without requiring human intervention. The system processes images, detects anomalies, and generates inspection results autonomously, thereby eliminating human error while maintaining versatility in defect detection.
2Productivity
If automated inspection techniques categorize defects into pre-defined classes, then detection speed is improved, but detection capability deteriorates for defects outside pre-defined classes
Solution Approach 1:
The patent implements a universal defect detection system that can identify multiple types of defects including leading edge defects, erosion, nicks, cracks, and cuts within a single automated framework. The system uses comprehensive image processing algorithms that can detect and classify various defect types without requiring separate specialized procedures for each defect class.
Solution Approach 2:
The inspection system dynamically adjusts analysis parameters and thresholds based on the specific image characteristics and detected anomaly types. This allows the system to maintain high detection speed while adapting to different defect types, effectively expanding its versatility without sacrificing productivity.
3Area of stationary object
If multiple image capture devices are used to capture images from different locations, then inspection coverage is improved, but system complexity increases due to image alignment and mosaicing requirements
Solution Approach 1:
The patent merges images captured by multiple image capture devices into a single comprehensive mosaiced image. By aligning and combining images from different locations and angles, the system achieves complete coverage of the inspection area while managing complexity through automated image registration and stitching algorithms.
Solution Approach 2:
The system uses feature correspondence as an intermediary mechanism to align images from multiple capture devices. By identifying and matching common features across images, the system automatically determines transformation parameters and seamlessly integrates multiple images into a unified mosaiced view, reducing processing complexity.
Data Source
AI summary
A system and method for performing automated defect detection using multiple image capture devices is disclosed. The system and method may include providing a plurality of image capture devices, the plurality of image capture devices capturing and transmitting a plurality of images of an object. The system and method may further include determining a feature correspondence between the plurality of images of the plurality of image capture devices, creating mosaiced images of the plurality of images if the feature correspondence is found or known and performing at least of an automated analysis and a manual inspection on the mosaiced images to find any defects in the object.