Autonomous underwater vehicle fault diagnosis dataset | |
Ji DX(冀大雄)1,2; Yao, Xin1,2; Li S(李硕)3; Tang YG(唐元贵)3; Tian Y(田宇)3 | |
刊名 | Data in Brief |
2021 | |
卷号 | 39页码:1-6 |
关键词 | Autonomous underwater vehicles (AUV) Fault diagnosis Fault type Model-free State data |
ISSN号 | 2352-3409 |
产权排序 | 3 |
英文摘要 | The dataset contains 1225 data samples for 5 fault types (labels). We divided the dataset into the training set and the test set through random stratified sampling. The test set accounted for 20% of the total dataset. Our experimental subject is ‘Haizhe’, which is a small quadrotor AUV developed in the laboratory. For each fault type, ‘Haizhe’ was tested several times. For each time, ‘Haizhe’ ran the same program and sailed underwater for 10–20 s to ensure that state data was long enough. The state data recorded in each test were then used as a data sample, and the corresponding fault type was the true label of the data sample. The dataset was used to validate a model-free fault diagnosis method proposed in our paper [1] and the complete dynamic model of ‘Haizhe’ AUV was reported in [2]. |
语种 | 英语 |
资助机构 | Basic Public Welfare Research Plan of Zhejiang Province (LGF 20E090 0 04 ). |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/29796] |
专题 | 沈阳自动化研究所_水下机器人研究室 |
通讯作者 | Ji DX(冀大雄) |
作者单位 | 1.The Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province, The Institute of Marine Electronic and Intelligent System, Ocean College, Zhejiang University, China 2.The Engineering Research Center of Oceanic Sensing Technology and Equipment, Ministry of Education, Zhoushan, 316000, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China |
推荐引用方式 GB/T 7714 | Ji DX,Yao, Xin,Li S,et al. Autonomous underwater vehicle fault diagnosis dataset[J]. Data in Brief,2021,39:1-6. |
APA | Ji DX,Yao, Xin,Li S,Tang YG,&Tian Y.(2021).Autonomous underwater vehicle fault diagnosis dataset.Data in Brief,39,1-6. |
MLA | Ji DX,et al."Autonomous underwater vehicle fault diagnosis dataset".Data in Brief 39(2021):1-6. |
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