Frequency Occurrence Plots for Motor Fault Diagnosis based on Image Recognition

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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.

Instructions: 

Please see read_me file for detailed documentation. Anyone can use image processing techniques for motor fault diagnosis using these dataset.

Comments

Hello! My graduation thesis is about motor fault diagnosis. May I use your data? Thank you very much!

Submitted by lu Z on Wed, 05/03/2023 - 03:48

Hello, I'm studying engine problems. Is it possible to use your data? Thanks.

Submitted by Angelo Cesar Co... on Thu, 11/02/2023 - 12:45

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Submitted by Pranali Borigidde on Sun, 10/06/2024 - 23:49

Documentation

AttachmentSize
File read_me.txt1.03 KB