Method to Allocate Vehicle Health Management Analytics to Subsystems for Maintenance Credit
Bibliographic record
Abstract
Airworthiness Approval of a Health and Usage Monitoring System as described in Miscellaneous Guidance 15 of the FAA's Advisory Circular 27-1B requires emphasis be placed on the certification requirements and their relationship to the design solution as it matures during the systems development process. A candidate Integrated Vehicle Health Management (IVHM) System-of-Systems (SoS) architecture is proposed in which the vertical lift segment and automated information systems are integrated with the sustainment processes. Next generation ground and support processes are introduced and methods used to substantiate reliability, availability, maintainability, and cost (RAM-C) using discrete event simulations based on market specific design reference missions are examined. A step-by-step system design process, including techniques to allocate data manipulation, condition monitoring, health assessments, and prognostics functionality to on-board and off-board system segments from concept design through sustainment with emphasis on certification is presented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".