Borescope Inspection Scheduling via FOD Probability Estimation
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Solution Overview
Problem
Engine borescope inspections for gas turbine engines are time-consuming and costly, with the risk of increased maintenance costs due to frequent Foreign Object Detection (FOD) events, especially when false alarms occur, leading to operational inefficiencies and increased maintenance frequencies.
Innovation Solution
A system that monitors engine conditions, processes data to estimate FOD probabilities, and schedules borescope inspections based on accumulated and predicted probabilities, using a combination of sensors and software modules to determine the optimal inspection timeframe, thereby reducing unnecessary inspections and maintaining operational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If borescope inspection intervals are extended to improve operational efficiency, then maintenance costs are reduced, but the risk of FOD events increases
Solution Approach 1:
The system performs preliminary monitoring and probability estimation before FOD events occur, enabling proactive inspection scheduling. By continuously accumulating FOD probability data and predicting future risks, the system allows extended inspection intervals while maintaining safety through advance warning capabilities.
Solution Approach 2:
The system implements continuous feedback loops where monitoring data is processed to update FOD probability estimates, which then feed back into inspection scheduling decisions. This closed-loop approach enables dynamic adjustment of inspection intervals based on actual risk levels, resolving the contradiction between extended intervals and risk management.
2Reliability
If FOD detection sensitivity is increased to improve safety, then more FOD events are detected, but false alarms increase leading to decreased operational efficiency
Solution Approach 1:
The system changes the parameter of detection from binary (detected/not detected) to probabilistic (FOD probability estimation). By processing multiple features and combining them into a cumulative probability score, the system distinguishes between true FOD events and false alarms, maintaining high detection sensitivity while reducing unnecessary inspections.
Solution Approach 2:
The system applies partial action by not triggering inspections for every detected anomaly. Instead, it accumulates probability evidence and only schedules inspections when the cumulative FOD probability exceeds thresholds, filtering out false alarms while maintaining sensitivity to genuine FOD events.
3Reliability
If borescope inspections are performed frequently to reduce FOD risk, then safety is improved, but maintenance costs and operational disruptions increase
Solution Approach 1:
The system makes inspection intervals dynamic rather than static. By continuously updating FOD probability estimates based on accumulated monitoring data, the system adjusts inspection timing to match actual risk levels, performing inspections more frequently when risk is high and less frequently when risk is low, thereby optimizing both safety and operational efficiency.
Data Source
AI summary
A system for identifying timeframes for borescope inspections for a gas turbine engine, having: monitoring systems monitor engine conditions, derive engine condition information and communicate such information to processors; feature interpreter module electronically communicates (i) with processors to process engine condition information, and (ii) feature interpreter information to processors, such information defines a probability of a FOD event; accumulator module electronically communicates (i) with processors to processes feature interpreter information, stored information since a last borescope inspection, and (ii) accumulator information to processors, such information defines an accumulated probability of a FOD event; and predictor and inspection planner module electronically communicates (i) with processors to processes accumulator information and stored information defines a threshold limits for a probability of a FOD event, and (ii) predictor and inspection planner information to processors, such information identifies a timeframe for a next borescope inspections predicted to occur before a FOD event.