A TEST RIG FOR EXPERIMENTATION ON FAULT TOLERANT CONTROL AND CONDITION MONITORING ALGORITHMS IN FLUID POWER SYSTEMS: FROM DESIGN THROUGH IMPLEMENTATION
Bibliographic record
Abstract
This paper reports the relevant aspects of a novel experimental test facility for research on fault tolerant control design and condition monitoring of fluid power systems recently constructed at the University of Manitoba. Common faults and their effects on the operation of valve controlled hydraulic actuators, such as those found in aerospace applications, are summarized first. The manuscript then presents the main features of the test rig and the modifications made to simulate various faults. The design also incorporates techniques to easily simulate load conditions from viscous forces to complex dynamic loads. The significance of the test rig in the development of advanced condition monitoring and fault tolerant control strategies is also illustrated by the presentation of the results of some recent research work conducted using the test facility. By sharing their experience with other investigators in this active area of fluid power research, the authors hope to establish a national benchmark test facility for the objective evaluation of state-of-the-art monitoring and control strategies for fluid power systems.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".