Integrated Hybrid Structural Management System (IHSMS) - Aircraft Impact Monitoring
Bibliographic record
Abstract
The Future Naval Capabilities Integrated Hybrid Structural Management System (IHSMS) program is developing Structural Health Management (SHM) capabilities for rotorcraft to move from conventional flight-hour based maintenance to reliability-based maintenance. A key element of IHSMS is to develop automated methods for impact detection, localization, and characterization. By their nature, impacts to rotor and airframe are random events that can trigger extensive inspections based solely on vague descriptions of the event by the aircraft crew. Operators must rely on numerous inspections to determine condition and ensure airworthiness, resulting in significant maintenance burden, both scheduled and unscheduled. The IHSMS program matured research originating at the Purdue Center for Systems Integrity (PCSI) at Purdue University and continued by the Laboratory for Systems Integrity and Reliability (LASIR) at Vanderbilt University, which uses a combination of physical sensors (accelerometers) and an algorithm to identify the location and estimate the force of impacts for both main rotor blade and airframe applications. This paper focuses on the outcomes of full-scale CH-53K main rotor blade and CH-53E airframe demonstration tests.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".