Aircraft Component Performance Decline Detection Method
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Solution Overview
Problem
Current aircraft maintenance methods, particularly for scheduling and spare parts management, often result in delays and groundings due to the inability to detect when aircraft components enter a decline period before they fail, leading to unnecessary costs and safety risks.
Innovation Solution
A method that involves obtaining detection parameters reflecting the operation status of aircraft components, comparing these parameters with extreme values, assigning weights based on correlation with failure events, and determining if the component is in a decline period to inform maintenance schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance is performed on a fixed schedule, then the aircraft can avoid delay or grounding to some extent, but the cost is too high and expensive parts may be replaced when their performance is still good
Solution Approach 1:
The system performs preliminary detection of component performance trends before actual failure occurs. By monitoring detection parameters and comparing them with historical data, the system predicts potential failures in advance, allowing maintenance to be scheduled at optimal times rather than following fixed schedules or waiting for actual failures.
Solution Approach 2:
The system establishes a feedback loop by continuously collecting detection parameters from aircraft components, analyzing trends, and using this information to adjust maintenance schedules. The detection results feed back into the maintenance decision-making process, enabling dynamic optimization of maintenance timing based on actual component conditions rather than static schedules.
2Ease of manufacture
If maintenance is performed post-processing after component failure, then the aircraft must be grounded and maintained until problems are resolved, but this causes delay and grounding of the aircraft
Solution Approach 1:
The system performs preliminary detection and prediction of component failures before they actually occur. By identifying components that are entering decline periods based on detection parameter trends, the system enables proactive maintenance scheduling, preventing actual failures and the associated aircraft grounding and delays.
3Productivity
If expensive spare parts are kept in the airport for replacing, then the aircraft can be maintained quickly, but the cost increases due to high price and using up of spare parts
Solution Approach 1:
The system performs preliminary prediction of component failures, allowing airlines to know in advance which components will need replacement and when. This enables optimized spare parts inventory management where parts are ordered and prepared based on predicted needs rather than keeping large stocks of expensive parts on hand, reducing inventory costs while ensuring availability when needed.
Data Source
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AI summary
The present application discloses a method for detecting whether performance of an aircraft component is in a decline period, comprising: obtaining one or more detection parameters reflecting operation status of the aircraft component; comparing data of the one or more detection parameters with respective desired values; and determining whether the performance of the aircraft component is in the decline period based on a comparison result.