Aircraft Engine Particle Impact Prediction for Maintenance Scheduling
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Solution Overview
Problem
Turbine engines, particularly gas turbine engines, face reduced operational time and component lifespan due to particle contamination such as dirt, dust, and volcanic ash, which clog and obstruct flow passages and surfaces, leading to inefficiencies and reduced maintenance intervals.
Innovation Solution
A method and system for evaluating and modeling the effect of particles on aircraft engines, including a dust load estimator and maintenance scheduling system, which uses user input, sensor data, and geographic information to predict particle impact and adjust maintenance and flight schedules accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If turbine engines operate in environments with airborne particles, then productivity and operational time are improved, but particle contamination causes component lifespan to deteriorate
Solution Approach 1:
The system performs preliminary assessment of particle conditions in the operating environment and predicts their impact on engine components before significant damage occurs. This enables proactive maintenance scheduling that prevents component lifespan deterioration while maintaining productivity
Solution Approach 2:
The system continuously monitors engine parameters and particle conditions, using feedback loops to adjust maintenance schedules based on actual particle impact. This dynamic feedback mechanism optimizes the balance between operational time and component lifespan by scheduling maintenance when particle accumulation reaches critical thresholds
2Duration of action of stationary object
If maintenance intervals are reduced to address particle contamination, then component lifespan is improved, but loss of time and operational efficiency deteriorate
Solution Approach 1:
The system changes the parameter of maintenance scheduling from fixed time intervals to condition-based intervals determined by particle accumulation rates and engine response. This allows extending maintenance intervals when particle conditions are favorable while intensifying maintenance when particle impact accelerates, optimizing both component lifespan and operational time
Solution Approach 2:
The system predicts particle impact and schedules maintenance in advance before component degradation becomes critical, allowing maintenance to be performed during planned downtime rather than unscheduled outages. This preliminary scheduling reduces unexpected downtime while ensuring component lifespan is maintained
3Measurement precision
If sensors and monitoring systems are added to detect particles, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system uses existing multi-functional sensors that serve both primary engine monitoring functions and particle detection functions. By making sensors universal, the system achieves precise particle measurement without adding dedicated particle detection hardware, thus avoiding increased device complexity
Solution Approach 2:
The system merges particle detection capabilities with existing engine monitoring and control systems. By combining particle sensing with traditional engine parameters monitoring, the system achieves precise particle measurement while integrating functionality into existing infrastructure, minimizing additional complexity
Data Source
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AI summary
A system and method including a processor (112) coupled to the non-volatile memory (114) and a non-transitory medium connected to the processor (112) wherein the processor (112) is configured to select one of a flight path between two points or a point of departure and frequency of departure in the flight path from the point for an aircraft, wherein the flight path has at least two phases and a flight along the flight path or a departure constitutes one cycle.