Automated Optical Inspection for Gas Turbine Blade Defect Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual inspection of gas turbine engine components for defects is time-consuming, expensive, and prone to human error, leading to potential customer dissatisfaction, revenue loss, and engine failure due to missed defects.
Innovation Solution
An automated optical inspection system using sensors and processors to capture and analyze data, separating it into normal and abnormal categories, employing techniques like Robust Principal Components Analysis (RPCA) and dynamic models to detect defects in turbine blades, disks, and gears with high spatial resolution and depth of field imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection is used to detect defects in turbine components, then human inspectors can identify defects through visual examination, but the inspection process becomes time-consuming and expensive
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated optical inspection system using sensors, cameras, and image processing algorithms. The system captures images of turbine components and uses automated defect detection algorithms to identify defects, eliminating the need for manual visual inspection by human inspectors while maintaining high detection accuracy and significantly reducing inspection time.
2Reliability
If human inspectors manually examine components for defects, then defect detection can be performed, but inspector fatigue and distraction lead to missed defects
Solution Approach 1:
The patent replaces human inspectors with an automated optical inspection system that uses sensors, image capture devices, and computer-based defect detection algorithms. This automation eliminates inspector fatigue and distraction, ensuring consistent and reliable defect detection without the human errors that occur during prolonged manual inspection tasks.
3Productivity
If automated optical inspection systems are implemented, then inspection time and human error are reduced, but the system complexity and initial cost increase
Solution Approach 1:
The patent implements an automated optical inspection system that uses sensors, image capture devices, and computer-based processing to replace manual inspection methods. While this increases automation and productivity, it also introduces system complexity. The patent addresses this by using standard optical components and software-based defect detection algorithms that can be integrated into existing manufacturing workflows.
4Measurement precision
If high-resolution imaging is used to detect small defects, then measurement precision improves, but the inspection system becomes more complex and expensive
Solution Approach 1:
The patent applies local quality by using high-resolution imaging specifically at critical defect-prone areas of turbine components rather than uniformly across entire components. The optical inspection system focuses imaging resources on regions where defects are most likely to occur, such as blade leading edges and disk surfaces, thereby achieving high measurement precision for defect detection without unnecessarily increasing system complexity throughout the entire inspection apparatus.
Data Source
AI summary
A system for component inspection comprising at least one sensor configured to capture sensor data of the component; and a processor coupled to the at least one sensor, the processor comprising at least one model configured to separate the sensor data into a normal category and an abnormal category.