Performance Assessment and Design of Quadratic Alarm Filters
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
Alarm filtering is a structurally simple, easy to implement, and effective method to improve industrial alarm systems. Owing to these advantages, alarm filters are widely used in industrial applications. Linear and quadratic are the main types of alarm filters. Although a linear filter can detect mean changes, it can not be used to detect variation changes. However, a quadratic filter can be used to detect both types of changes. Although this remarkable feature of quadratic filters has been addressed in the literature, no explicit performance analysis is performed yet. So, deriving an analytical solution for quadratic filters is of paramount importance. To this aim, we propose an analytical method for performance assessment and design of quadratic filters. On the other side, in industrial applications, many process variables are acquired. So one challenge is to identify the process variable that provides the best alarm performance after filtering. We will derive an analytical solution to this problem. Furthermore, we will prove that this optimal solution is a function of the statistical feature of historical data and alarm filter structure.
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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 | 0.000 |
| 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 it