Forced Response System Identification of Full Aero-Engine Rotordynamic Systems for Prognostics and Diagnostics
Bibliographic record
Abstract
Abstract A first-of-its-kind forced-response system identification approach is introduced to measure rotordynamic damping of shaft modes in a full gas turbine aero-engine. The approach involves forced-response modal analysis in which the rotordynamic system is excited with an external shaker and engine modal characteristics are extracted from rotor shaft response signals. A reduced-order modeling framework capturing full-engine dynamics and coupling between rotor shafts and support static structure was developed and implemented in a Pratt & Whitney Canada PW615 Turbofan engine. The framework was used to guide the design of forced-response system identification experiments. The design study shows that two orthogonal shakers are required to excite both forward- and backward-whirling shaft modes and that excessive forcing amplitudes that produce whirl over 0.4 of journal eccentricity ratio can yield up to 12% lower response magnitudes due to non-linear bearing characteristics. A statistical analysis of virtual experiments under real engine operating conditions demonstrates feasibility and robustness of the approach, measuring rotordynamic damping for key shaft modes with an uncertainty of up to 15%. General applicability of the approach with similar error levels is suggested for multi-spool multi-frame aero-engine architectures. Guidelines for experimental setup, data acquisition and processing are established for full-engine forced-response system identification experiments. The new capability shows promise in supporting aero-engine diagnostics and prognostics to improve the life cycle operation of commercial and military engines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".