Hydraulic Actuator Internal Leakage Detection Using Cross-Correlation Time Series Analysis
Bibliographic record
Abstract
As a hydraulic actuator is used over time, the piston seal that closes the gap between the moveable piston and the cylinder wall wears. This results in the fluid to eventually being able to flow across the piston and between the cylinder chambers. Although no fluid is lost from the circuit, the dynamic performance of the system is affected since only a portion of the flow delivered to the actuator is available to move the piston against the load. Leakage across the piston introduces a flow deadband, which can lead to servoing errors. This paper presents an approach based on the cross-correlation time-series analysis to determine the health of hydraulic actuator internal seals. Pressure signals obtained directly from routine operations are analyzed using the cross-correlation function. The method presented in this paper is shown to be capable of detecting leakages as small as 0.069 l/min.
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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".