On the Mechanical Design of the Weight Exchanger for Automatic Mass Calibration up to 20 kg
Bibliographic record
Abstract
Manual calibrators in mass measurement are widely common in mass technology.However, the process for calibration masses is monotonic and dangerous for heavy masses.This article concerns the main features of designing and controlling a low-cost, highaccuracy 2-axis automatic weight exchanger for mass measurement up to 20 kg with minimum requirements based on design constraint variables.The design variables are the mass and balance dimension, balance range, readability, weight of the masses, and the system's rigidity.Other key operational factors, including stability, motor sizing, and precise PID position control, should be considered and engineered for automated calibration.Lots of modifications are carried out to enhance the calibration process.The cost function generation is carried out to find the maximum number of masses that can calibrated according to the design variables.The weight exchanger has two 2-axis for motion in the Cartesian coordinate X-axis and Y-axis, respectively.The motors' size and speed are selected carefully to verify stability during the measuring process for each case.Experimental tests were conducted on four automatic weight exchangers for automatic mass calibration.Controlling the motion using PID position control for the automatic calibration based on the weight exchanger's maximum weight and the carried masses.The automatic system approves the mechanical design features and controls and performs measurements for masses up to 20 kg.The obtained results prove the feasibility of the proposed weight exchanger from design and control viewpoints.The results show that the automatic weight exchanger can efficiently calibrate 7, 4, 16, and 3 masses ranging from 50 g up to 20 kg based on design variables selection.Moreover, it enhances and reduces the standard deviations of the reading measurement compared to manual work.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".