Autonomous underwater vehicle fault diagnosis dataset.

The dataset contains 1225 data samples for 5 (labels). We divided the dataset into the training set and the test set through random stratified sampling. The test set accounted for of the total dataset. Our experimental subject is 'Haizhe', which is a small quadrotor AUV developed in the laboratory. For each , 'Haizhe' was tested several times. For each time, 'Haizhe' ran the same program and sailed underwater for 10-20 s to ensure that was long enough. The recorded in each test were then used as a data sample, and the corresponding 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].