Parametric fault diagnosis for electrohydraulic cylinder drive units
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A novel model-based methodology for fault diagnosis (FD) of nonlinear hydraulic drive systems is presented in this paper. Due to its linear dependence upon parameters, a second-truncated Volterra nonlinear model is first used to characterize such systems. The versatile order-recursive estimation scheme is employed to determine the values of parameters in the Volterra model. The scheme also avoids separate determination of the model order; thus, the complexity of the search process is reduced. Next, it is shown that the estimated parameters, representing different states of the system, normal as well as faulty conditions, can be used to detect and isolate system faults in a geometric domain. Very promising results are exhibited via simulations as well as laboratory experiments. It is concluded that the developed parametric FD technique has potential to provide efficient condition monitoring and/or preventive maintenance in hydraulic actuator circuits.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it