VivaKitTransmission-Line Fault Detection, Classification & Localization
Physics-based protective relaying and transmission line diagnostic engine for 400 kV extra-high-voltage power networks. Models transient 3-phase voltage and current waveforms under steady-state and faulted conditions using electromagnetic differential equations and Fortescue symmetrical components (Zero, Positive, Negative sequence networks). Extracts 18 protective relaying features (apparent impedance, sequence ratios, RMS) to classify 5 fault regimes (LG, LL, LLG, LLL, Normal) with microsecond response times and estimate fault distance along the line for automated Zone 1 and Zone 2 trip decisions.
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Our honest results
| Fault Classification Accuracy (synthetic) | 100.0% (Held-out test split, 1,000 synthetic events) |
| Classification Macro-F1 (synthetic) | 1.000 (LG, LL, LLG, LLL, Normal balanced) |
| Distance Estimation MAE (synthetic) | 5.06 km (Across 100 km 400 kV transmission line) |
| Distance Regression R² (synthetic) | 0.930 (Evaluated across varying arc resistance & noise) |
Evaluated on 1,000 held-out synthetic fault cycles generated with varying inception angles (0°–180°), arc resistance (0.1–50 Ω), and measurement noise (25–45 dB SNR). Includes interactive 3-phase oscilloscope, Gradio 6 console, automated pytest suite, and 15 electrical engineering viva voce questions with symmetrical component math.
What's included
- Readable source codeSmall, commented modules you can explain line by line in your viva.
- Demo appA local web app to show your examiners - runs offline on your laptop.
- Trained model + reference resultsSo you can compare your own runs fairly.
- Learning guide with viva Q&ABackground, design choices explained, limitations and extension ideas.
- One-click setup & testsWindows setup script and tests that prove it works on your PC.
- Dataset download scriptFetches the public data from its original source, with the citation.
Dataset credit
In-house electromagnetic differential equation 3-phase power transmission simulator developed by VivaKit, parameterized according to IEEE/CIGRE 400 kV benchmarks.
Academic integrity
We sell code and teaching, not finished projects. You must understand, extend and write up the work yourself, acknowledge the kit and cite the dataset. No ready-made reports.