相关数据集
Intelligent bearing fault diagnosis dataset
Fault detection, Swarm decomposition, optimized compensation distance evaluation
kaggle2021-11-22 更新400
Bearing parameters.
Hidden Markov Models (HMMs) have become an immensely popular tool for health assessment and fault diagnosis of rolling element bearings. The advantages of an HMM include its simplicity, robustness, an
NIAID Data Ecosystem20
Traditional single fractal dimension (i.e., box-counting dimension) of a random chosen sample from bearing normal condition and different fault conditions with fault size 7mils
Traditional single fractal dimension (i.e., box-counting dimension) of a random chosen sample from bearing normal condition and different fault conditions with fault size 7mils
NIAID Data Ecosystem10
Bearing run-to-failure datasets of UNSW
The run-to-failure experiments data were collected at the University of New South Wales in 2019-2020, regarding the development of bearing fault severity assessment methods. The following journal pape
Mendeley Data40
