The use of thermography in the diagnosis of ship piston internal combustion engines
Bibliographic record
Abstract
The intensity of infrared radiation emitted by objects depends mainly on their temperature. One of the diagnostic signals may be the temperature field. In infrared thermography, this quantity is used as an indicator of the technical condition of marine objects. The article presents an overview of the use of infrared thermography for the diagnosis mainly of marine piston floating objects and various types of reciprocating internal combustion engines as well as examples of own research results. A general introduction to infrared thermography and common procedures for temperature measurement and non-destructive testing are presented. Experimental research was carried out both in laboratory conditions and in the operating conditions of sea-going vessels. Experimental studies consisted of the presentation of photographs of the same objects made in visible light and the use of infrared thermography. The same objects were also compared, but for different cylinders of the tested internal combustion engines as well as for the up state and fault state. The characteristics of the temperature values at selected points were taken depending on the engine load along with the approximation mathematical models of these dependencies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".