Datasets
Standard Dataset
4- and 2- inch PM dataset and Test 20.6-million-pose LUT
- Citation Author(s):
- Submitted by:
- Yang Wang
- Last updated:
- Mon, 11/04/2024 - 14:34
- DOI:
- 10.21227/09en-qt48
- Data Format:
- License:
- Categories:
- Keywords:
Abstract
The 4-inch and 2-inch dataset are generated using random mover poses with single square coils. The sample sizes are 8 million and 9.6 million for the 4-inch and 2-inch datasets, respectively. The input and label data are min-max normalized to range between zero and one. The 20.6 million dataset file is created using the same wrench model (GT model), which has infeasible mover poses. The infeasible mover poses are scruntinized for the 4-inch and 2-inch dataset to make sure the PM is above the top surface of the coil. The wrench results for the infeasible locations produced large results due to zero-divide-zero operation. The issue are fixed using another numerical method which is slower than the GT used in the study.
See attached instruction files for the revert scaling of the dataset.
The LUT is a 7-D cell, the first two dimensions are 6,1. The rest are Ry, Rx, z, theta, rho. The results are in the first quadrant of the operating range. rho in 0 to 255 mm. theta in 0 to 90 deg. z in 7 to 70 mm. Rx, Ry in -40 to 40 deg.
Dataset Files
- 4-inch dataset 8 million random mover poses. four_inch_dataset_rand_norm.csv (1.27 GB)
- 2-inch dataset 9.6 million random mover poses. two_inch_dataset_rand_norm_96.csv (1.53 GB)
- 7-D LUT for 4-inch mover in the first quadrant. test_poses_rs_method_20mil_clean.mat (8.04 GB)
Documentation
Attachment | Size |
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For the two dataset. | 1.17 KB |