Aircraft Gas Turbine Engine Diagnosis via Deviation Pattern Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for diagnosing aircraft gas turbine engines are inefficient in detecting damage early and initiating appropriate maintenance or repairs, as they rely on manual analysis of parameter values and lack automated systems for identifying deviations and damage patterns.
Innovation Solution
A method and system for partially automated diagnosis that detects actual parameter values, determines deviations from theoretical values, and identifies damage probability patterns based on similarity to known patterns, allowing for timely maintenance recommendations, using a thermodynamic model calibrated for each operational segment to filter and smooth data for precise diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis of parameter values is used for diagnosis, then diagnostic capability is maintained, but diagnostic efficiency and early damage detection capability deteriorate
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computer-based diagnostic system that uses algorithms to analyze parameter values, determine deviations, and identify damage patterns automatically, thereby improving both efficiency and reliability of early damage detection
Solution Approach 2:
The diagnostic system enables the engine monitoring process to serve itself by automatically detecting parameter values, comparing them against theoretical models, identifying deviations, and generating damage probability patterns without requiring continuous manual intervention
2Reliability
If automated diagnosis system is implemented, then diagnostic efficiency and early damage detection are improved, but system complexity increases
Solution Approach 1:
The diagnostic system is divided into distinct functional modules: a parameter value detection module, a deviation determination module, and a damage pattern identification module. This segmentation allows each module to perform a specific function, making the overall complex system more manageable and maintainable
Solution Approach 2:
The patent introduces a computer as an intermediary that mediates between the engine parameters and the diagnostic analysis, automatically processing data and comparing it against stored damage patterns to reduce the complexity of direct human analysis
3Measurement precision
If deviation analysis is performed without pattern matching, then processing speed is maintained, but diagnostic accuracy and reduction of erroneous diagnoses deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-storing multiple damage patterns and their characteristic deviation signatures in the computer. When analyzing actual parameter deviations, the system can quickly compare against these pre-prepared patterns, avoiding time-consuming manual analysis while maintaining high diagnostic accuracy
Solution Approach 2:
The patent creates copies of known damage patterns and their associated deviation characteristics, storing them in the computer for comparison. This allows the system to match actual deviations against multiple pattern copies simultaneously, improving both accuracy and processing efficiency
Data Source
AI summary
A method for the at least partially automated diagnosis of aircraft gas turbine engines includes the steps of: 1) detecting actual parameter values of an aircraft gas turbine engine for several operational segments 2) determining deviations, of these actual parameter values from theoretical parameter values; and 3) determining damage pattern probabilities based on a similarity of at least one determined deviation, particularly based on a change between determined deviations, to deviation patterns of different known damage patterns.