Fault_Diagnosis_for_AUV

Published: 28-06-2021| Version 1 | DOI: 10.17632/4328wcmy8m.1
Contributor:
Yao XIN

Description

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 seconds 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 (DOI:https://doi.org/10.1016/j.oceaneng.2021.108874)

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