Bibliographic record
Abstract
In recent years there is a growing trend on integrating Computer Aid Design (CAD), Computer Aid Manufacturing (CAM) and Computer Aided Inspection (CAI). This thesis presents a new shape adaptive motion control system that integrates part measurement with motion control. The proposed system consists of five blocks: surface measurement; surface reconstruction; tool trajectory planning; axis motion control and part alignment In this thesis, the key technology used in surface measurement and surface reconstruction is spatial spectral analysis. In the surface measurement block, a new special spectrum comparison method is proposed to find out an optimal digitizing frequency. In the surface reconstruction block, different interpolation methods are compared in the spatial spectral domain. A spatial spectral B-Spline method is presented. In the tool trajectory planning block, a method is developed to select the motion profile first and then determine the tool locations according to the reconstructed surface in order to improve the accuracy of the planned path. In the part alignment, a three-point alignment method is presented to align the part coordinates with the machine coordinates. Based on the proposed methods, a software package is developed and implemented on the polishing robot constructed at Ryerson University. The effectiveness of the proposed system has been demonstrated by the experiment on edge polishing. In this experiment, the shape of the part edges is measured first, and then constructed as a wire-frame CAD model, based on which tool trajectory is planned to control the tool to polish the edges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".