Component Wear Detection via Manmade Feature Masking
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Solution Overview
Problem
Current methods for detecting subsurface defects in industrial components, such as corrosion and cracking, are inaccurate due to variations in parts and mischaracterization of manmade features as defects, leading to unreliable predictions of component life and maintenance schedules.
Innovation Solution
A monitoring system that includes a processor and memory device configured to receive component images, detect manmade structural features, adjust images to mask them out, and compare the adjusted images with a reference model to determine potential defect areas, analyzing these areas to output their state to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If visual inspection methods are used to detect surface issues, then the inspection process is simple and quick, but the detection accuracy is low and only qualitative measures are provided
Solution Approach 1:
The patent replaces manual visual inspection with an automated image processing system that uses computational algorithms to analyze component images. The system automatically detects, segments, and quantifies defects such as corrosion and cracking, transforming subjective visual assessment into objective digital measurement with higher precision and reproducibility.
Solution Approach 2:
The patent introduces image processing technology as an intermediary between the component and the inspector. By capturing images and processing them through specialized algorithms, the system creates an intermediate digital representation that enhances the detection capability beyond direct human vision, enabling both rapid processing and high-precision measurement.
2Measurement precision
If CT scans and X-rays are used to detect subsurface defects, then subsurface features can be visualized, but variations in different parts cause accuracy problems and manmade features are mischaracterized as defects
Solution Approach 1:
The patent applies preliminary processing steps including image normalization, enhancement, and pre-segmentation before the main defect detection algorithm. This preliminary action prepares the images by reducing variations and highlighting relevant features, making the subsequent analysis more accurate and reliable while distinguishing manmade features from actual defects.
Solution Approach 2:
The patent applies different processing and analysis methods to different regions of the component images. By adapting the detection algorithms to local characteristics and using region-specific thresholds, the system maintains high accuracy across varying parts while reducing false positives from manmade features that have different local patterns.
3Measurement precision
If automated image processing is implemented to improve detection accuracy, then measurement precision increases, but system complexity increases
Solution Approach 1:
The patent segments the image processing task into distinct modular stages: image acquisition, preprocessing, defect segmentation, analysis, and reporting. Each module performs a specific function and can be independently optimized or replaced, reducing overall system complexity while maintaining high measurement precision through specialized processing at each stage.
Data Source
AI summary
A monitoring system for determining component wear is provided. The monitoring system includes a memory device configured to store a reference model of a component and a component wear monitoring (CWM) device configured to receive a component image of a first component being inspected, detect a plurality of manmade structural features in the received component image, adjust the component image to mask out at least some of the plurality of manmade structural features from the received component image, compare the adjusted component image with the reference model to determine one or more potential defect areas in the first component, analyze each of the one or more defect areas to determine a state of the potential defect areas, and output the state of the one or more potential defect areas to a user.