Standardized Aircraft Recording Frames for Fault Diagnosis
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Solution Overview
Problem
Current aircraft data recording frame configurations, such as those used in QARs, are optimized for operational purposes and not standardized, making it difficult to diagnose faults and maintain aircraft systems effectively, and require manual reconfiguration efforts for maintenance-focused data analysis.
Innovation Solution
A computer-implemented method and system to determine a standardized maintenance-optimized data frame configuration that prioritizes parameters and sampling rates for fault detection and prognosis, using a data frame configuration system to format and analyze aviation data for maintenance purposes, including a data formatter and health monitoring system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If QAR data frames are configured for operational purposes with traditional parameter selection, then flight safety and operational efficiency are improved, but fault detection and maintenance capabilities deteriorate
Solution Approach 1:
The patent segments the aircraft data parameters into different categories: operational parameters for flight safety and maintenance parameters for fault detection. The system creates separate data frame configurations that can be selectively activated based on the operational context, allowing optimal parameter sets for both operational safety and maintenance purposes without compromising either function.
Solution Approach 2:
The system dynamically configures data frames based on operational mode. During normal operations, the configuration prioritizes flight safety parameters. When maintenance mode is activated, the system automatically reconfigures to prioritize fault detection parameters, enabling the same QAR system to serve both operational and maintenance objectives effectively.
2Productivity
If airline-specific non-standardized data frame configurations are used, then operational objectives are optimized, but analytics portability and maintenance standardization deteriorate
Solution Approach 1:
The patent implements a universal data frame configuration standard that can be applied across different airlines and aircraft types. The standardized framework includes common parameter definitions, consistent data structures, and unified formatting rules that enable analytics portability. Airlines can still customize within the standardized framework to meet their specific operational needs, achieving both standardization and operational optimization.
3Measurement precision
If all available aircraft parameters are recorded, then comprehensive fault diagnosis is improved, but data processing complexity and storage requirements worsen
Solution Approach 1:
The system extracts and prioritizes only the most critical maintenance-related parameters from the complete set of available aircraft parameters. By identifying and selecting key parameters that provide the highest value for fault detection and diagnosis, the system reduces data volume and processing complexity while maintaining diagnostic accuracy. Less critical parameters are excluded from the maintenance-focused data frame configuration.
Solution Approach 2:
The patent applies different quality levels of parameter recording based on their importance for maintenance purposes. Critical parameters are recorded with higher sampling rates and greater detail, while less critical parameters are recorded at lower resolutions or excluded entirely. This differentiated approach optimizes the balance between diagnostic capability and data processing burden.
Data Source
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AI summary
Systems (100) and methods (200) for formatting aviation data (152) for improved aircraft fault detection, diagnosis, and maintenance are provided. One example method (200) includes determining (202) a plurality of available parameters associated with an aircraft. The method includes matching (204) the plurality of available parameters against a plurality of desired parameters to identify a plurality of matched parameters that are both desired and available. The plurality of matched parameters are useful to perform fault diagnosis and prognosis for the aircraft. The method includes determining (210) a priority level for each of the plurality of matched parameters. The method includes creating (212) a standardized maintenance- optimized data frame configuration (150) based at least in part on the plurality of matched parameters and the priority level for each of the plurality of matched parameters.