Aircraft Fault Diagnosis Using In-Flight Cause Probabilities
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Solution Overview
Problem
Current aircraft maintenance systems require aircraft to be out of service for extended periods, as troubleshooting and repairs can be labor-intensive and costly, and existing diagnostic methods are inefficient in identifying the root cause of faults during flight.
Innovation Solution
A computer-implemented method and apparatus that determine the occurrence probabilities of potential causes of events detected onboard aircraft while in flight, using historical, fleet, and environmental data to provide a graphical user interface displaying the likelihood of each cause, allowing for pre-landing maintenance planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fault diagnosis methods are used, then maintenance personnel can identify faults, but the aircraft must remain out of service for extended periods during troubleshooting and repair
Solution Approach 1:
The system performs preliminary diagnostic analysis while the aircraft is still in service by collecting and analyzing sensor data, fault codes, and operational parameters. Ground-based systems process this data to identify potential causes and prepare maintenance procedures before the aircraft lands, allowing maintenance personnel to be pre-alerted and prepared, thus minimizing the time the aircraft needs to be out of service.
2Measurement precision
If comprehensive fault analysis is performed, then accurate diagnosis can be achieved, but the troubleshooting process becomes labor-intensive and costly
Solution Approach 1:
A ground-based diagnostic system acts as an intermediary between the aircraft's monitoring systems and maintenance personnel. This system automatically collects data from multiple sensors, processes fault codes, analyzes operational parameters, and generates prioritized lists of potential causes with probability rankings. This automated intermediary performs the labor-intensive analysis work, providing accurate diagnoses while freeing maintenance personnel from tedious troubleshooting tasks.
Solution Approach 2:
The patent replaces manual mechanical troubleshooting processes with automated electronic data collection and analysis systems. Sensors continuously monitor aircraft systems and transmit data to ground-based processing systems that use algorithms to analyze fault patterns, eliminating the need for maintenance personnel to manually test and diagnose each component, thus improving productivity while maintaining diagnostic accuracy.
3Reliability
If detailed monitoring and analysis systems are implemented, then fault detection capability improves, but system complexity increases
Solution Approach 1:
The patent introduces a ground-based intermediary system that receives simplified data transmissions from the aircraft and performs the complex analysis work remotely. The aircraft itself only needs to collect and transmit basic sensor data and fault codes, while the computationally intensive processing, pattern recognition, and diagnostic reasoning are performed by the ground-based system, thus improving fault detection capability without significantly increasing the complexity of the onboard monitoring system.
Data Source
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AI summary
The present disclosure relates to health monitoring and maintenance of mobile platforms such as aircraft. In particular, onboard apparatus and methods and also ground-based apparatus and methods that cooperate in assisting with the maintenance of mobile platforms by facilitating diagnosis of events detected onboard mobile platforms while such mobile platforms are in operation (e.g., transit, flight) are disclosed. In various aspects, the present disclosure discloses apparatus and methods for handling and reporting the detection of events onboard mobile platforms, reporting predefined additional information associated with the event upon request from a ground facility, identifying one or more potential causes for the detected event and determining the occurrence probability for each potential cause identified.