Turbomachine Monitoring via Pre-computed Failure Classification Tables
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Solution Overview
Problem
Current methods for evaluating the criticality of failures in aircraft systems overestimate the probability of feared events like Loss of Thrust Control (LOTC) due to neglecting common failure modes and requiring excessive computation resources, leading to premature maintenance and unnecessary flight interruptions.
Innovation Solution
A method that calculates the conditional probability of feared events by modeling a failure tree, identifying repeated events, and applying factorization to simplify the calculation of probabilities, allowing for exact estimation of criticality levels and reduced computing time, thereby triggering maintenance only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional probability calculation methods are used to evaluate degraded configurations, then the probability of feared events can be determined, but the computation resources are excessively consumed and calculation time increases exponentially with the number of failures
Solution Approach 1:
The patent segments the probability calculation process into two distinct phases: an offline phase where classification tables are pre-computed and stored, and an online phase where only table lookup is performed. This segmentation separates the computationally intensive probability calculations from the real-time evaluation, resolving the contradiction between accuracy and efficiency.
Solution Approach 2:
The patent performs preliminary action by pre-calculating and storing classification tables offline before actual operation. The complex probability calculations are executed in advance when computational resources are abundant, and the results are cached for rapid retrieval during runtime, eliminating the need for repeated expensive calculations.
2Device complexity
If failures are considered as independent events in probability algorithms, then the calculation is simplified, but common failure modes are neglected leading to overestimation of the probability of feared events
Solution Approach 1:
The patent uses classification tables as a copy of the complex probability calculation results. Instead of repeatedly performing complex calculations that account for common failure modes, the pre-computed table (a copy of the results) is used for rapid lookup, maintaining accuracy while reducing complexity.
Solution Approach 2:
The patent changes the parameter representation from individual failure probabilities to conditional probabilities stored in classification tables. This parameter transformation allows the system to capture the interdependencies of common failure modes in a compact format that simplifies subsequent calculations.
3Ease of operation
If conservative estimation methods are used for multiple failures, then the calculation is simpler, but the aircraft is required to stop within much shorter delays than actually necessary, leading to premature maintenance
Solution Approach 1:
The patent replaces the conservative estimation approach (mechanical system) with a data-driven classification table lookup (information system). This substitution eliminates the need for overly conservative assumptions while maintaining operational simplicity, as the tables provide precise probability values without requiring complex real-time analysis.
4Measurement precision
If classification tables are computed in real-time for each degraded configuration, then the most accurate probability values are obtained, but the repeated application consumes significant computation resources
Solution Approach 1:
The patent extracts the computationally intensive probability calculation step from the real-time operation and moves it to an offline preprocessing phase. The classification tables are extracted and pre-computed when computational resources are available, and only the lightweight table lookup remains during actual operation, dramatically reducing real-time resource consumption.
Data Source
AI summary
A method for monitoring the operation of a turbomachine controlled by a digital control system including at least one component, includes acquiring operating state information relating to the state of at least one component; determining, depending on the state information acquired, a current degraded configuration in which at least one of the components has failed; determining a classification of the current degraded configuration using at least one classification table stored in a storage device, the classification tables associating with at least one degraded configuration one classification expressing the level of criticality of the degraded configuration, the tables being obtained by calculating a conditional probability of a predefined anticipated event from the probability of occurrence of elementary events relating to a failure of one of the components; and estimating an operating time permitted for the turbomachine depending on the classification determined for the current degraded configuration.