conditions, including normal mode and many open-circuit fault scenarios.
This dataset is designed for:
✔ Machine Learning (ML) & Deep Learning (DL)
✔ Fault detection and classification
✔ Power electronics research
✔ Predictive maintenance
✔ University courses & academic projects
✔ Digital Twin modeling
If you work in electronics, energy systems, AI, or embedded systems, this dataset will save you weeks or months of data collection and signal processing.
📦 What’s Included
When you purchase the full version, you receive:
Format: CSV
6 columns:Time, Voltage, Signal1, Signal2, Signal3, Class
12 labeled classes
Multi-channel time-series
Cleaned and formatted for immediate use
Dataset description
System architecture
Plots & class distribution
Sample time-series signals
12,000 samples
1,000 rows per class
Perfect for testing
📊 Dataset Characteristics
Samples: 264,000
Classes: 12
Channels: 4 signals
Type: Time-series
Use cases: AI, ML, Power Electronics
File Type: CSV
🧠 Applications
You can use A3RC-12 to train:
CNN, LSTM, Transformers
Anomaly detection models
Fault classification systems
Digital Twins
Condition monitoring algorithms
Perfect for research, development, and industrial prototypes.
💼 Who Uses This Dataset?
Researchers & graduate students
University laboratories
AI engineers
Power electronics developers
Inverter/UPS/solar companies
Industrial monitoring teams
🤖 Class List (12 fault conditions)
Normal Condition (Data_N)
Multiple open-circuit faults (S1, S2, S3, S4, S5, S6, etc.)
Combined fault scenarios