Reciprocating Compressor Condition Monitoring.
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
Technology for reciprocating compressor condition monitoring has been around since the 1950's, however until the last 20 years or so it seemed that only the pipeline companies spent much effort on this activity.Technology has advanced, and there are very effective approaches to monitoring and protecting reciprocating compressors on the market today.While pipeline operations are pulling out their reciprocating compressors, this machine is still the workhorse of refineries, chemical plants, and oil production facilities.As a result a new generation of interest has developed in effective condition monitoring of reciprocating compressors.This paper will discuss risk based decision making in regard to measurements and protective functions, online versus periodic monitoring, proven and effective measurement techniques, along with a review of both mechanical and performance based measurements for assessing machine condition.Case histories will also be presented to demonstrate some of the concepts.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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