Datasets
Standard Dataset
Frequency Occurrence Plots for Motor Fault Diagnosis based on Image Recognition
- Citation Author(s):
- Submitted by:
- EDUARDO JR PIEDAD
- Last updated:
- Fri, 05/24/2019 - 22:27
- DOI:
- 10.21227/77da-c563
- Data Format:
- License:
Abstract
The dataset has 150 three-second sampling motor current signals from each synthetically-prepared motors. There are five motors with respective fault condition - bearing axis deviation (F1), stator coil inter-turn short circuit (F2), rotor broken strip (F3), outer bearing ring damage (F4), and healthy (H). The motors are run under five coupling loads - 0, 25, 50, 75, and 100%. The sampling signals are collected and processed into frequency occurrence plots (FOPs). Each image has a label, for example F2_L50_130, where F2 is the fault condition, L50 is the coupling load condition. and 130 is the index of motor current signal. A total of 3,750 FOPs which can be used for motor fault diagnosis through image recognition problem.
Please see read_me file for detailed documentation. Anyone can use image processing techniques for motor fault diagnosis using these dataset.
Documentation
Attachment | Size |
---|---|
read_me.txt | 1.03 KB |
Comments
Hello! My graduation thesis is about motor fault diagnosis. May I use your data? Thank you very much!
Hello, I'm studying engine problems. Is it possible to use your data? Thanks.
-