A New Method for Estimation and Control of Temperature Profile over a Sheet in Thermoforming Process
Bibliographic record
Abstract
This paper presents a new method for the estimation of surface temperature of a sheet using temperature sensors at different positions of the sheet. The proposed method is developed and designed in such a way that it can estimate the temperature profile over the entire sheet through its spatial harmonics and control the spatial harmonics to obtain the desired temperature profile. Computational cost is also considered during the development of the proposed method. A PI controller is used to control each spatial harmonic to achieve the desired temperature profile over the sheet. The proposed estimation method of the temperature profile is based on the two-dimensional FFT. Each component of the two-dimensional space temperature harmonics is controlled by adjusting the heater temperatures. The performance of the proposed temperature estimation technique is tested in simulation for different desired temperature profile to compare with a simple method of temperature estimation based on the weighted average temperature of the sensors surrounding the location of interest. Thereafter, the performance of the proposed temperature control technique based on the spatial harmonics is compared with the conventional control technique in simulation. The superiority of the proposed method for the estimation of temperatures and hence the accuracy of the developed controller and its prospective real-time application is evidenced by the results.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".