Online state and parameter estimation of an electrohydraulic valve for intelligent monitoring
Bibliographic record
Abstract
Summary form only given. A novel nonlinear state-space model for a two-stage proportional directional servovalve is proposed, that has all physical states and coefficients necessary for an online model-based condition monitoring and fault diagnosis algorithm which tracks abrupt or gradual changes in a number of key parameters and states. Extended Kalman filtering has enabled us to simultaneously reconstruct the system "hard-to-measure" states and estimate physical coefficients using only a few basic measurements. One of those crucial states is the instantaneous amount of fluid passing through a variable orifice valve. Using a simulation example, the flow rate has been accurately predicted through a novel model that lets the orifice effective area be an initially unknown function of the spool displacement. The area and also the size of spool deadband, both embedded in the function, are then automatically revealed during the online estimation process, while the switching between the open-to-supply and open-to-tank port models is internally made.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".