Database

Database description 

This database contains experimental data acquired from an inverter-fed induction motor under variable speed and load conditions. The dataset is composed of two groups based on signal duration: 15-second experiments and 32-second experiments. Multiple operating conditions, including healthy and faulted states, are provided. All signals were sampled at 10.24 kHz.

Measured Signals - The following quantities were measured simultaneously during all experiments: Three-phase line currents, Three-phase line voltages, Radial leakage (stray) flux, Axial leakage (stray) flux, Air-gap flux

The 15-second datasets follow the naming convention :  (Condition)_15s_file1.mat, (Condition)_15s_file2.mat. In both cases, the supply frequency is varied from 40 Hz to 60 Hz. file1 : Load follows a U-pattern profile during the experiment.  file2 : Load varies arbitrarily within 75% of the rated load.

The 32-second datasets follow the naming convention :  (Condition)_32s_file1.mat, (Condition)_32s_file2.mat, (Condition)_32s_file3.mat, (Condition)_32s_file4.mat. 

file1:  Speed varies from 40 Hz to 60 Hz and back to 40 Hz, Load follows a W-pattern profile. file2: Speed varies from 40 Hz to 60 Hz and back to 40 Hz,  Load is fixed at 75% of the rated load. file3 : Speed varies from 40 Hz to 60 Hz and back to 40 Hz,  Load follows an M-pattern profile. file4:  Speed is fixed at 60 Hz,  Load follows a W-pattern profile.

Condition labels

HLY denotes the healthy operating condition.

BRB denotes the broken rotor bar fault condition.

ECC denotes the dynamic eccentricity fault condition (30%). 

Each MATLAB .mat file includes: Raw time-domain measurement signals, Predefined variables for direct analysis and visualization. MATLAB scripts for plotting the time-domain signals are also provided.

MATLAB Data files and code file for plotting the time-domain signals.

Database description for IEEE TIE Journal Paper, Under Review 

The database contains the measurements acquired using sensors as described in the paper. Five different fault conditions were emulated under changing load and frequency levels. The frequency changes from 40 Hz to 60 Hz for each data acquisition, while the load changes arbitrarily. During the experiments, line currents and voltages, 3-axis vibrations, leakage flux, and airgap flux signals were measured.

The file naming system follows the format: (Condition)_15s_(Measurement No.).mat. For example, the filename "HLY_15s_1" denotes data gathered for the healthy condition. 

The signal length for each data point is 15 seconds, at 10240 samples/sec. MATLAB files are included for plotting the time-domain signals. For a more detailed explanation of fault emulation, detection, and identification, please refer to the "Fault Monitoring for Inverter-fed Induction Motors under Variable Load and Speed Conditions" paper.

MATLAB Data files and code file for plotting the time-domain signals.

Database description for IEEE Sensors Journal Paper, DOI: 10.1109/JSEN.2024.3447869 

The database contains more than 200 measurements acquired using prototype and conventional sensors. Six different fault conditions were emulated under various loading levels during the start-up and steady-state operation. Both direct on-line and inverter-fed power supplies were used for 60 Hz, 40 Hz, and 20 Hz speed operations. During the experiments, 3-phase currents and voltages, 3-axis vibrations, leakage flux, and airgap flux signals were measured using both sensor types.

The file naming system follows the format: (Fault type & level)_(Power supply & frequency)_(Loading %)_(Measured signal type). For example, the filename "Bearing06_VFD60hz_100_vol3" denotes a bearing fault of 0.6 mm, inverter-fed power supply at 60 Hz, 100% loading, and voltage signal measurement on phase 3.

The signal lengths for steady-state conditions are 6 and 50 seconds for prototype and conventional sensors, respectively, and 10 seconds for the starting transient signal. MATLAB files are included for plotting the time-domain signals. For a more detailed explanation of fault emulation, detection, and identification, please refer to the "MEMS Accelerometer and Hall Sensor based Identification of Electrical and Mechanical Defects in Induction Motors and Driven Systems" paper.

MATLAB files for plotting the time-domain signals.