Avionic Diagnostic System with Likelihood Ranking
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Solution Overview
Problem
Current avionic system diagnostic processes often fail to provide a high-level relevance in identifying defective functional units, leading to prolonged repair times as they require maintenance operators to perform preliminary actions to isolate breakdowns.
Innovation Solution
A process and device that acquire diagnostics from surveillance units, construct possible diagnostics, determine a likelihood criterion for each based on associated functional units, and select the most likely diagnostic, directly indicating the defective unit without the need for preliminary isolation actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional surveillance units are used to monitor functional units, then the system can detect breakdowns, but the diagnostic precision is low and multiple unitary diagnostics are emitted without clearly identifying the defective unit
Solution Approach 1:
The patent changes the diagnostic parameter from simple unitary diagnostics to a composite likelihood criterion that incorporates multiple factors including surveillance unit reliability, detection probability, and diagnostic consistency. This transforms the diagnostic output from ambiguous multiple possibilities to a ranked list with identified most probable defective units.
Solution Approach 2:
The patent introduces an intermediary processing layer between the surveillance units and the maintenance operator. This layer correlates diagnostics from multiple surveillance units, evaluates likelihood criteria, and produces a refined diagnostic result that identifies the most probable defective functional unit, thereby reducing information loss.
2Reliability
If multiple unitary diagnostics are emitted to cover all possible failures, then the diagnostic coverage is comprehensive, but the repair time increases due to the need for preliminary isolation actions
Solution Approach 1:
The patent performs preliminary correlation and likelihood evaluation of all possible diagnostics before presenting results to the maintenance operator. By pre-processing the diagnostic data to identify the most probable defective units based on likelihood criteria, the system eliminates the need for time-consuming preliminary isolation actions in the field.
Solution Approach 2:
The patent replaces the mechanical/manual process of isolating breakdowns with an automated information processing system that correlates diagnostics and calculates likelihood criteria. This substitution of manual isolation procedures with automated diagnostic processing significantly reduces repair time while maintaining comprehensive diagnostic coverage.
3Extent of automation
If traditional diagnostic correlation methods are used, then the system can process multiple surveillance unit outputs, but the diagnostic relevance is low and does not directly indicate the defective unit
Solution Approach 1:
The patent changes the output parameter from generic correlated diagnostics to a likelihood-ranked list that explicitly identifies the most probable defective functional units. This parameter transformation maintains automated processing while significantly improving diagnostic relevance by providing actionable information that directly points to defective units.
Data Source
AI summary
The invention relates to a process for determining a diagnostic for a breakdown of an avionic system, the avionic system comprising a plurality of functional units and surveillance units, each capable of performing surveillance of at least one functional unit, characterized in that it comprises the following steps: acquisition of diagnostics from at least one surveillance unit, a diagnostic emitted by one surveillance unit relating to the said at least one functional unit subjected to surveillance by the surveillance unit, construction of possible diagnostics on the basis of the acquired diagnostics, determination of a likelihood criterion for each constructed possible diagnostic, the likelihood criterion for a possible diagnostic being determined on the basis of a unitary criterion determined for each functional unit associated with the possible diagnostic, selection of the possible diagnostic among the possible diagnostics according to the likelihood criterion.