Aircraft Power Gearbox Failure Detection via Torque and Vibration Analysis
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Solution Overview
Problem
Power gearboxes, particularly epicyclic gearboxes in gas turbine engines, face challenges in detecting mechanical failures such as planet bearing failures due to high mechanical loads and long maintenance intervals, which can lead to unnoticed damage and increased risk of engine failure.
Innovation Solution
A method and system that measure operational parameters like torque, speed, and vibrations across the gearbox, comparing them to baseline data to detect deviations and trends indicative of mechanical failures, allowing for early detection and prevention of further damage through signal processing and control protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If power gearboxes operate for long time without maintenance to increase productivity, then maintenance intervals are extended, but mechanical failures such as planet bearing failures occur unnoticed leading to increased risk of engine failure
Solution Approach 1:
The system performs preliminary detection of mechanical failures by continuously monitoring operational parameters (vibrations, torque, speed) and comparing them against baseline data. This allows early identification of deviations indicating planet bearing failures or other mechanical issues before they lead to engine failure, enabling maintenance to be scheduled proactively rather than reactively.
Solution Approach 2:
The system establishes a feedback loop where operational data from the power gearbox is continuously collected, analyzed, and compared against baseline values. When deviations exceed thresholds, the system generates alerts and trend data that feed back to maintenance scheduling systems, enabling dynamic adjustment of maintenance intervals based on actual condition rather than fixed schedules.
2Difficulty of detecting and measuring
If traditional vibration monitoring methods are used to detect gearbox failures, then detection capability is provided, but early detection of planet bearing failures is insufficient due to high mechanical loads masking the signals
Solution Approach 1:
The system merges multiple monitoring approaches by combining traditional vibration analysis with torque and speed parameter monitoring. By analyzing the combined dataset and looking for correlated deviations across all parameters, the system can distinguish genuine planet bearing failure signals from noise caused by high mechanical loads, improving early detection precision.
Solution Approach 2:
The system adds new dimensions to failure detection by incorporating torque and speed parameter analysis alongside traditional vibration monitoring. This multi-dimensional approach allows the system to detect planet bearing failures through parameter correlations that would be invisible in single-dimensional vibration analysis, effectively detecting failures in the early stages before they become apparent through conventional methods.
Data Source
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AI summary
The invention relates to a method and system for detecting a functional failure in a power gearbox, in particular an epicyclic gearbox (30) in an aircraft gas turbine engine (10) comprising a) measuring operational data (101) in the gas turbine engine (10) of least two operational parameters dependent on the power generation and / or power consumption of the gas turbine engine (10) and / or the power gearbox, in particular the epicyclic gearbox (30), b) obtaining analyzed operational data (102) comprising time data, angular data of a rotation, frequency data and / or phase data from the measured operational data (102), c) using the analyzed operational data (102) in a comparison with stored baseline operational data (103) to determine deviation data (104) from the baseline operational data (103), d) determining time dependent trend data (105) from the deviation data (104), and e) generating a signal and / or a protocol (106) for controlling the power gearbox, in particular the epicyclic gearbox (30) and / or the gas turbine engine (10) based on the time dependent trend data (105), in particular if a predetermined condition or threshold is exceeded.