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NSTDA 2022 Rotating-Machinery Vibration Dataset
7,650 CSV recordings from the NSTDA rotating-machinery test rig (2022
collection). Single faults, compound faults, and healthy baseline, recorded
at four shaft speeds. Unzip 2022.zip to get a single flat folder 2022/
of CSV files.
Filename convention
UNB_ANG_PAR_LOAD_RPM_IDX.csv e.g. 4301_16_00_00_1200_041.csv
| Field | Meaning | Units / notes |
|---|---|---|
| UNB | Unbalance severity | grams x 10 (4301 = 430.1 g); 0000 = absent |
| ANG | Angular misalignment | mm/100mm (NOT degrees); 00 = absent |
| PAR | Parallel misalignment | mm; 00 = absent |
| LOAD | Load code | 00 throughout this set |
| RPM | Shaft speed | one of 0600 / 0900 / 1200 / 1480 |
| IDX | Recording index | repeat number within the condition |
- Healthy baseline:
0000_00_00_... - Single fault: exactly one of UNB/ANG/PAR nonzero.
- Compound fault: two or three nonzero (e.g.
1961_21_22_...is a triple: Unb 196.1 g + Ang 21 + Par 22).
CSV format
Each file is ~1 second of vibration at 51.2 kHz (delta t = 1.953125e-5 s, ~51,180 samples). Layout:
- Rows 1-3: metadata (
waveformcolumn names,t0timestamp,delta t). - Row 4: blank. Row 5: repeated column header (
time,V2V,V2H,V2A). - Row 6 onward: data. Column 0 = timestamp; columns 1-3 = the signals.
Channels (accelerometer at sensor position 2):
V2V= vertical,V2H= horizontal,V2A= axial.
Load with pandas by skipping the 5 header rows and dropping the time column:
import pandas as pd
df = pd.read_csv("2022/0000_00_00_00_0600_001.csv",
skiprows=5, header=None, usecols=[1, 2, 3])
x = df.to_numpy() # shape (~51180, 3): V2V, V2H, V2A
Gotchas
- ANG is misalignment in mm per 100 mm, not an angle in degrees.
- UNB in the filename is 10x the gram value.
- If you see a
.nstda_cache/folder after processing, it is derived cache, not source data - safe to delete, regenerated on demand.
- Downloads last month
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