Aircraft Component Testing Using Pattern Recognition
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Solution Overview
Problem
Current methods for testing aircraft component parts, such as power supplies, are limited by the need to evaluate numerous test parameters, making comprehensive testing time- and cost-intensive, and often result in invalid test results due to the complexity of parameter combinations and the dependency on tester experience.
Innovation Solution
A method utilizing a pattern recognition system to establish correlations between test parameters and values, allowing for the selection of optimized test parameters that reduce the number of necessary tests by defining second test parameters based on inner correlations, thereby improving test validity and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive test protocols with numerous test parameters are used to ensure functional capacity and safety, then test result validity is improved, but test time and cost increase significantly
Solution Approach 1:
The patent extracts only the most relevant test parameters from the complete set of possible parameters. The system identifies and selects a subset of test parameters that are most critical for detecting faults, thereby reducing the number of tests required while maintaining test validity. This is achieved through automated analysis of parameter relevance and impact on system functionality.
Solution Approach 2:
The patent dynamically adjusts test parameters based on system characteristics, fault types, and test objectives. Rather than using a fixed comprehensive set of parameters, the system modifies which parameters are tested and at what values, optimizing the test protocol for each specific testing scenario to reduce unnecessary tests while maintaining reliability.
2Reliability
If all possible test parameter combinations are evaluated to rule out potential faults, then test completeness is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent segments the complete test parameter space into meaningful groups and categories. By dividing parameters into relevant and irrelevant groups, the system can focus testing efforts on critical parameter combinations without evaluating all possible combinations. This segmentation approach maintains test completeness for critical areas while avoiding unnecessary complexity in less critical areas.
Solution Approach 2:
The patent applies partial action by testing only the most critical parameter combinations rather than all possible combinations. The system identifies a subset of parameter combinations that provide sufficient fault detection coverage, accepting that not every possible combination is tested while maintaining adequate reliability through targeted testing of high-impact parameters.
3Adaptability or versatility
If step-by-step testing with manual determination of step increments is used, then test adaptability is improved, but productivity decreases due to dependency on tester experience
Solution Approach 1:
The patent implements automated feedback mechanisms where test results from previous iterations inform the selection of subsequent test parameters. The system automatically adjusts test parameters based on feedback from measured values, eliminating the need for manual determination of step increments while maintaining adaptability. This automated feedback loop preserves test flexibility while significantly improving productivity.
Solution Approach 2:
The testing system performs self-adjustment of test parameters without requiring manual intervention. The automated system independently determines optimal test parameters, step increments, and test sequences based on system characteristics and test objectives, replacing manual tester expertise with automated decision-making capabilities that maintain adaptability while improving efficiency.
4Ease of operation
If random generation of test parameters is used, then ease of operation is improved, but test result validity decreases
Solution Approach 1:
The patent replaces manual parameter selection (mechanical approach) with automated computer-based selection. Rather than relying on tester expertise or purely random generation, the system uses automated algorithms to select test parameters based on system characteristics, fault models, and test objectives. This substitution maintains ease of operation while significantly improving test validity through intelligent, data-driven parameter selection.
Data Source
AI summary
A method for testing a component part of an aircraft comprises the steps of determining at least one first test value of the component part of the aircraft and/or at least one first test value of a comparable component part of a further aircraft for at least one test parameter, inputting the first test parameter and the first test value into a pattern recognition system, which produces an inner correlation between the first test parameter and the first test value. The method further comprises the steps of defining at least one second test parameter, inputting the second test parameter into the pattern recognition system in order to determine a second test value by means of the inner correlation, checking whether the second test value falls within the predefined value range, and determining a third test value of the component part of the aircraft for the second test parameter if the second test value falls within the predefined value range. The invention further relates to a device for testing a component part of an aircraft.