Turboshaft Module Efficiency Diagnosis Using Simulated Performance Maps
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Solution Overview
Problem
Current methods for determining defects in aircraft turbine engines are imprecise and require additional sensors, which are costly and fragile, making it difficult to precisely identify the defective module and its cause without extensive installation and maintenance.
Innovation Solution
A method that determines the efficiency of each turbine engine module by creating an estimated real map from flight data, using a mathematical model learned from parameter measurements, and comparing it to simulated maps to identify performance deviations without adding sensors, utilizing computer learning for accurate and efficient analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensors are integrated into all modules of the turbine engine to characterize each module independently, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent creates a virtual model (performance map) of the turbine engine that replicates the behavior and performance characteristics of the physical system. This digital copy allows for precise module efficiency determination through software analysis rather than physical sensor installation in each module, thereby maintaining measurement precision while avoiding the complexity and cost of additional hardware sensors.
Solution Approach 2:
The patent replaces the mechanical/physical sensor-based measurement system with a computational/software-based system. Instead of using physical sensors to directly measure module parameters, the system uses computer learning algorithms to analyze existing flight data and infer module efficiency, substituting mechanical measurement with intelligent data processing.
2Measurement precision
If additional sensors are installed in critical environments (high temperature and high pressure), then measurement precision is improved, but reliability decreases due to sensor fragility and cost
Solution Approach 1:
The patent creates a virtual model (performance map) of the turbine engine that replicates the behavior and performance characteristics of the physical system. This digital copy allows for precise module efficiency determination through software analysis rather than physical sensor installation in each module, thereby maintaining measurement precision while avoiding the complexity and cost of additional hardware sensors.
Solution Approach 2:
The patent replaces the mechanical/physical sensor-based measurement system with a computational/software-based system. Instead of using physical sensors to directly measure module parameters, the system uses computer learning algorithms to analyze existing flight data and infer module efficiency, substituting mechanical measurement with intelligent data processing.
3Device complexity
If existing flight data is used without additional sensors, then device complexity is reduced, but measurement precision deteriorates due to inability to characterize each module independently
Solution Approach 1:
The patent replaces the mechanical/physical sensor-based measurement system with a computational/software-based system. Instead of using physical sensors to directly measure module parameters, the system uses computer learning algorithms to analyze existing flight data and infer module efficiency, substituting mechanical measurement with intelligent data processing.
Solution Approach 2:
The patent transforms the approach by changing from direct physical measurement parameters to derived computational parameters. By using computer learning to extract and analyze performance parameters from existing flight data, the system achieves module-level precision without additional sensors, effectively changing the measurement paradigm from hardware-based to software-based parameter extraction.
4Ease of operation
If a database comparison method is used for fault determination, then ease of operation is improved, but measurement precision deteriorates due to complex and imprecise diagnoses
Solution Approach 1:
The patent replaces the mechanical/physical sensor-based measurement system with a computational/software-based system. Instead of using physical sensors to directly measure module parameters, the system uses computer learning algorithms to analyze existing flight data and infer module efficiency, substituting mechanical measurement with intelligent data processing.
Solution Approach 2:
The patent transforms the approach by changing from direct physical measurement parameters to derived computational parameters. By using computer learning to extract and analyze performance parameters from existing flight data, the system achieves module-level precision without additional sensors, effectively changing the measurement paradigm from hardware-based to software-based parameter extraction.
Data Source
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AI summary
The invention relates to a method for determining an efficiency fault (R11-R15) of at least one module (11-15) of a turboshaft engine (T) of an aircraft (A), the method for determining comprising: • A step of determining an estimated real mapping (CARE), • A step of determining real indicators (IRE) from the estimated real mapping (CARE), • A step of determining (E3) a plurality of simulated mappings from a simulation of a theoretical model of the turboshaft engine (T) for different efficiency configurations, • A step of determining (E4) simulated indicators (ISx) for each simulated mapping (CARSx), • A step of training (E5) a mathematical model (CLASS) by coupling the simulated indicators (ISx) with efficiency configurations (CR), and • A step of applying (E6) said mathematical model (CLASS) to the real indicators (IRE) so as to deduce therefrom a real efficiency configuration (CR).