Horizontal Stabilizer Fault Prediction via Pitch Data Analysis
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Solution Overview
Problem
Current aircraft systems rely on manual and discretionary methods to identify and record faults in horizontal stabilizer systems, which are inefficient and do not allow for predictive maintenance, leading to potential operational issues and increased maintenance costs.
Innovation Solution
A method that involves receiving and analyzing data on aircraft pitch characteristics during flight, comparing it to reference values, and predicting faults in the horizontal stabilizer system, providing an indication of potential issues before they occur, using sensors and a controller connected to a database with historical data and communication systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual and discretionary methods are used to identify and record faults, then the system is simple to operate, but the maintenance efficiency is low and faults cannot be predicted
Solution Approach 1:
The system performs preliminary analysis of pitch characteristic data during flight operations to predict potential horizontal stabilizer faults before they occur. By continuously monitoring and comparing pitch data against reference values, the system identifies trends and anomalies that indicate developing faults, enabling proactive maintenance scheduling and avoiding unplanned groundings.
Solution Approach 2:
The system establishes a feedback loop where pitch characteristic data is continuously collected, analyzed, and compared against reference values. When deviations are detected, the system generates maintenance alerts that feed back to maintenance personnel, creating a closed-loop system that continuously improves maintenance effectiveness based on actual operational data.
2Reliability
If automated fault prediction systems are implemented, then maintenance costs are reduced and aircraft downtime is minimized, but the device complexity increases
Solution Approach 1:
The system utilizes the existing aircraft pitch sensing and flight control systems for dual purposes: normal flight control and fault prediction. By leveraging existing sensors and data infrastructure, the system avoids requiring entirely new hardware while achieving predictive maintenance capabilities, thus improving reliability without proportionally increasing complexity.
Solution Approach 2:
The system performs self-diagnosis by automatically monitoring its own operational parameters (pitch characteristics) and identifying faults without requiring external inspection. This self-monitoring capability enables the aircraft to detect and report its own issues, improving reliability while minimizing the need for additional external diagnostic equipment.
3Measurement precision
If continuous monitoring of pitch characteristics is performed, then fault detection accuracy is improved, but the energy consumption increases
Solution Approach 1:
The system applies partial monitoring by focusing analysis on specific pitch characteristic parameters most indicative of horizontal stabilizer faults, rather than continuously analyzing all flight parameters. This selective monitoring approach maintains high fault detection accuracy for the target system while minimizing unnecessary energy consumption from comprehensive continuous analysis of all aircraft systems.
Data Source
AI summary
A method of predicting a horizontal stabilizer system fault in an aircraft, where the method includes receiving data relevant to a characteristic of the pitch of the aircraft during flight, comparing the received data to a reference pitch characteristic, predicting a fault in the horizontal stabilizer system based on the comparison, and providing an indication of the predicted fault.