SSFs dataset: Self-supervised features dataset of the ultrasonic signals of two-phase flow in an S-shaped riser
收藏DataCite Commons2023-09-15 更新2025-04-09 收录
下载链接:
https://cord.cranfield.ac.uk/articles/dataset/SSFs_dataset_Self-supervised_features_dataset_of_the_ultrasonic_signals_of_two-phase_flow_in_an_S-shaped_riser/22241530/1
下载链接
链接失效反馈官方服务:
资源简介:
Title: SSFs dataset: Self-supervised features dataset of the ultrasonic signals of two-phase flow in an S-shaped riser Author: Boyu Kuang, neiil.kuang@cranfiel.ac.uk Time: 09th March 2023 Description: The source data of the proposed SSFs dataset comes from: https://doi.org/10.17862/cranfield.rd.11369379.v1 The Self-supervised features (SSFs) dataset is opened to the community along with our latest journal paper entitled: "Self-supervised learning-based two-phase flow regimen identification using ultrasonic sensors in an S-shape riser". NOTE: the journal DOI will be provided after the acceptance. This dataset is produced using the settings in TABLE I. Here are some details, and please contact me if you got any issues with using the dataset: SSFs_dataset: "the root directory of the dataset" | | -- ex: "the SSFs from the experiment group (ex)" | | | | | -- train: "the training set (70%)" | | | | | -- test: "the testing set (15%)" | | | | | -- valid: "the validation set (the rest)" | | -- ctr-A: "the SSFs from the control group (ctr-A)" | | | | | -- train: "the training set (70%)" | | | | | -- test: "the testing set (15%)" | | | |
提供机构:
Cranfield Online Research Data (CORD)
创建时间:
2023-03-09



