Application of TRIZ Theory in Noise Improvement of Vertical Refrigerated Display Cabinet
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
This paper takes the air-cooled vertical refrigerated display cabinet as the research object, analyzes and improves the noise problem of the vertical refrigerated display cabinet by using TRIZ theory. Firstly, the noise problem of vertical refrigerated display cabinet is clearly defined and the main noise sources are determined;secondly, the product noise problem is transformed into TRIZ problem model, and the problem model is determined to be a technical contradiction; secondly, the idealization level of each component is analyzed to determine the useful and harmful functions; finally, the invention is determined by using archishure general engineering parameters and contradiction matrix Principle and find a specific solution, effectively reduce the noise of vertical refrigerated display cabinet.
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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 | 0.002 | 0.002 |
| 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 | 0.000 |
| 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