Gas Turbine Blade Reflection Sensing for In-Operation Damage Detection
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Solution Overview
Problem
Existing methods for detecting abnormalities in gas turbine engine blades are limited to offline inspections and cannot detect damage during operation, and existing debris monitoring systems only detect foreign objects, not blade damage.
Innovation Solution
A method and system that projects light onto rotating blades during operation, using sensors and processing circuitry to analyze reflections for abnormalities, potentially with machine learning, enabling real-time detection of blade damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used to detect blade abnormalities, then inspection accuracy can be maintained, but the engine must be shut down and removed from service
Solution Approach 1:
The patent replaces manual mechanical inspection with an optical detection system using light sources and sensors to detect blade abnormalities. The system uses light reflection patterns captured by sensors to identify blade defects without requiring physical contact or engine shutdown, thereby maintaining detection accuracy while enabling continuous operation.
Solution Approach 2:
The patent introduces light as an intermediary medium to detect blade abnormalities. Light sources project light onto rotating blades, and sensors capture the reflected light patterns. This intermediary optical approach allows non-contact detection during engine operation, resolving the contradiction between accurate detection and engine availability.
2Adaptability or versatility
If inlet debris monitoring systems are used, then debris detection capability is provided, but blade abnormalities cannot be detected at all
Solution Approach 1:
The patent creates a multi-functional detection system that can detect both debris and blade abnormalities using the same optical infrastructure. The light sources and sensors are positioned to capture reflections from both incoming debris and rotating blades, allowing a single system to perform multiple detection functions simultaneously.
Solution Approach 2:
The patent transitions from static debris monitoring to dynamic blade inspection by detecting light reflections from rotating blades during engine operation. The system captures time-varying reflection patterns as blades rotate through the illumination zone, enabling abnormality detection while the engine is running rather than requiring static inspection conditions.
3Object-affected harmful factors
If manual inspection is performed when the engine is not operating, then safety can be ensured, but inspection time and engine downtime increase
Solution Approach 1:
The patent enables continuous blade inspection during engine operation rather than requiring periodic shutdowns. The optical detection system operates continuously as blades rotate through the illumination zone, maintaining inspection capability without interrupting engine function, thereby eliminating inspection-related downtime while safety is maintained through non-contact optical methods.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time detection of blade abnormalities during operation, reducing the need for offline inspections and improving safety by identifying damage without requiring the engine to be shut down.
Implementation Method 1
utilizing a sensor to record data of at least one reflection of the projected light from a blade
Data Source
Figure 1
Figure 2~2A
Figure 3A
AI summary
A method of inspecting blades of a gas turbine engine (20) for abnormalities includes projecting light from a light source (60) into an illumination area (64); utilizing a sensor (66) to record data of at least one reflection of the projected light from a blade (43) that is part of a gas turbine engine (20) and is disposed in the illumination area (64); determining, based on the recorded data, whether the blade (43) is abnormal; and based on the determining indicating that the blade (43) is abnormal, providing a blade abnormality notification. A gas turbine engine (20) is also disclosed.