Rotor Blade Image Tracking for Replacement Position Records
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Solution Overview
Problem
Existing systems for managing rotor blade inspections and repairs in gas turbine engine rotor blades lack efficiency in tracking and recording component replacement data, particularly in identifying replaced rotor blades and their positions.
Innovation Solution
An assembly comprising an imaging device and a processing system that captures and processes image data to identify and record the pre-repair and post-repair positions of rotor blades, allowing for the identification of replaced blades and their indexing in a database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking methods are used for rotor blade replacement data, then system complexity is reduced, but measurement precision and data accuracy deteriorate
Solution Approach 1:
The patent uses image copying technology to create digital replicas of rotor blades with unique identifying features. These image copies are stored in a database and used for automatic identification and tracking of blade positions before and after maintenance, eliminating manual data collection while maintaining high accuracy.
Solution Approach 2:
The patent replaces manual mechanical tracking methods with an automated image processing and pattern recognition system. The system automatically captures images, identifies rotor blades through feature matching, tracks position changes, and records replacement data without human intervention, thereby improving precision while managing complexity through automation.
2Productivity
If automated image processing is implemented, then productivity and data collection speed improve, but device complexity increases
Solution Approach 1:
The system performs self-identification and self-tracking of rotor blades through automated image processing. The pattern recognition algorithms automatically identify blade features, match them against the database, determine positions, and record replacements without requiring external manual operation, thereby improving productivity while the automated nature manages operational complexity.
Solution Approach 2:
The patent establishes a pre-repair baseline by capturing and storing images of all rotor blades with their initial positions before maintenance begins. This preliminary action creates a reference database that enables automatic comparison and identification of replacements during and after the process, improving tracking efficiency while distributing the complexity across multiple automated stages.
3Loss of information
If detailed position tracking is implemented for each rotor blade, then information completeness improves, but loss of time for data processing increases
Solution Approach 1:
The system continuously captures images at critical stages (pre-repair and post-repair) and continuously processes these images through pattern recognition algorithms. This continuous automated action ensures complete position data is captured without interruption, and the rapid processing eliminates time delays, thereby improving information completeness while minimizing time loss.
Solution Approach 2:
The patent replaces time-consuming manual data collection and recording with automated image capture and digital processing. The system instantly captures complete position information for all rotor blades and automatically processes this data through computer algorithms, ensuring full information completeness while dramatically reducing the time required compared to manual methods.
Data Source
AI summary
An assembly for recording rotor blade replacement data for a bladed rotor includes an imaging device and a processing system. The imaging device is configured to capture image data for the bladed rotor including a plurality of rotor blades. The processing system is configured to identify each of the plurality of rotor blades installed on the bladed rotor in pre-repair image data of the captured image data and store a pre-repair position of each of the identified plurality of rotor blades installed on the bladed rotor in the pre-repair image data, identify each of the plurality of rotor blades installed on the bladed rotor in post-repair image data and store a post-repair position of each of the identified plurality of rotor blades installed on the bladed rotor in the post-repair image data, and identify at least one replaced rotor blade installed on the bladed rotor in the post-repair image data using the pre-repair image data and the post-repair image data.


