Aircraft System Testing with Classifier-Based Difference Detection
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Solution Overview
Problem
Aircraft systems are complex and difficult to test effectively, often requiring extensive time and resources to identify and address differences between desired and actual operations, especially due to limitations in existing testing methods that may not account for user preferences and real-world scenarios.
Innovation Solution
A test apparatus and method using a trained classifier to compare actual aircraft system operations with a modeled operation, generating signals for differences, and allowing for continuous training based on user feedback and data from various sources, including aircraft users, to adapt to changing preferences and improve system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional testing methods are used for aircraft systems, then testing can be performed, but it requires extensive time and resources to identify differences between desired and actual operations
Solution Approach 1:
The patent creates a virtual copy of the aircraft system through a trained classifier that models the desired operation. This virtual model processes input values and generates expected output values, which are then compared against actual system outputs. The copying approach eliminates the need for extensive physical testing while maintaining high measurement precision in identifying operational differences.
Solution Approach 2:
The classifier is trained in advance using training data that represents desired system operations. This preliminary training phase establishes the expected behavior model before actual testing begins. By performing the learning and model establishment beforehand, the system can quickly identify differences during operation without requiring extensive real-time testing resources.
2Reliability
If traditional testing methods are used for aircraft systems, then testing can be performed, but it requires considerable resources and extensive testing procedures
Solution Approach 1:
The patent replaces traditional mechanical and manual testing procedures with an automated computational system. The trained classifier automatically processes input values, generates expected outputs, and compares them with actual system outputs. This substitution of automated information processing for manual testing significantly improves productivity while maintaining or enhancing the reliability of system operation assessment.
Solution Approach 2:
The system performs self-testing and self-evaluation by automatically comparing its own output against the trained classifier's expected output. The apparatus can independently identify operational differences without requiring external testing equipment or extensive manual intervention, thereby improving both productivity and reliability through automated self-verification.
3Adaptability or versatility
If existing testing methods are used, then system operation can be checked, but they may not account for user preferences and real-world scenarios
Solution Approach 1:
The patent incorporates feedback mechanisms where the comparison between actual and expected outputs provides information about system performance relative to desired operations. This feedback loop allows the system to adapt to user preferences and real-world scenarios by learning from discrepancies. The trained classifier can be retrained with new data that reflects evolving user preferences, enhancing adaptability without requiring complete system redesign.
Data Source
AI summary
A test apparatus (100) for testing at least part of an aircraft system. The test apparatus (100) is configured to obtain first data (210) including a plurality of input values and process the input values using a classifier (230) configured to model an operation of the at least part of an aircraft system (220). Second data is obtained, including a set of output values (240b). The output values (240b) from the second data are processed with output values (240a) generated by the classifier to identify differences between operation of the at least part of an aircraft system (220) and the operation as modelled by the classifier (230).