An inspection strategy for randomly failing systems subjected to random shocks
Bibliographic record
Abstract
This paper is motivated by the study of randomly failing systems whose state is only known through inspection and for which high availability is required. Security and alarm systems such as power system protective relays and environmental censoring equipment are typical examples of such systems. The deterioration process of these systems is generally governed by electromechanical transient shocks which occur randomly over time and whose magnitude is also random. These shocks damage the system cumulatively. Under the proposed inspection strategy, the system is inspected at predetermined times T/sub 1/, T/sub 2/, ... . If failure is detected then the system is replaced by a new one, otherwise it is kept operating. The expression of the system time-stationary availability is presented and an algorithm has been developed to generate the inspection sequence which insures a certain availability level. In cases where limited resources restrict the user to predetermined inspection period, the computer program generates the optimal design and operating parameters which will provide the targeted system availability level. A test case is analyzed and potential applications related to automotive industries are mentioned.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".