Component Lifespan Prediction Using Grain Structure and Stress Maps
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Solution Overview
Problem
Existing methods for monitoring component lifespan, particularly in turbomachines, are inefficient and costly due to the need for precise positioning of strain sensors, leading to inconsistencies in deformation analysis and potential errors.
Innovation Solution
A method and system that utilize image processing and computer analysis to detect grain structures on components, compare them with stress maps, and determine predicted lifespan based on grain structure localization and stress directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If strain sensors are configured on components to monitor creep, then component lifespan can be predicted, but the positioning of analysis apparatus must be precise which is time-consuming and costly
Solution Approach 1:
The patent uses digital images of the component surface as copies to analyze grain structure and detect creep deformation. Instead of requiring precise physical positioning of analysis apparatus, the system captures images from fixed positions and processes them computationally to identify deformation patterns, thereby eliminating time-consuming positioning requirements while maintaining measurement precision
Solution Approach 2:
The patent replaces the mechanical positioning system with a computational image processing system. Rather than physically positioning analysis apparatus to maintain consistent viewing angles, the system uses computer vision algorithms to automatically detect and measure grain structure changes and deformation from fixed image positions, substituting mechanical precision with computational analysis
2Reliability
If strain sensors are configured on components to monitor creep, then component lifespan can be predicted, but the positioning requirements introduce errors in deformation analysis
Solution Approach 1:
The patent creates digital copies of the component surface through imaging to analyze grain structure and deformation. This copying approach eliminates the errors introduced by physical positioning variations, as the same image can be processed multiple times without requiring repeated precise positioning, thereby improving both reliability and measurement precision
Solution Approach 2:
The system uses image processing to detect grain structure changes and provides feedback about creep deformation and predicted lifespan. This feedback mechanism allows for continuous monitoring and adjustment of maintenance schedules, improving reliability by providing accurate, repeatable measurements without the positioning errors that plague traditional strain sensor methods
Data Source
AI summary
Systems and methods for determining component predicted lifespan are provided. A method includes processing, by a computing system comprising one or more processors, an image of the component to detect a grain structure on the component. The method further includes comparing, by the computing system, the detected grain structure with a stress map of the component. The method further includes determining, by the computing system, based on a localization of the detected grain structure and the stress map, a predicted lifespan of the component.