AI-FAULTGEN: Physics-Informed Generative AI for Electrical Fault Open Data Generation

A Physics-Informed Generative AI for Electrical Fault Analysis and Open Data Generation
Advanced short-circuit fault detection and measurement with support for high voltage (up to 200V) - Based on empirical research by the OpenFaultDynamics Team

Advanced Physics Principle. Short circuit fault quantities exhibit system-dependent behavior where higher input voltages lead to disproportionately higher short circuit currents and more complex transient patterns. Our enhanced AI model captures these nonlinear relationships across the entire voltage spectrum (2.5V to 200V) with near-perfect accuracy.

Enhanced Faults Datasets

Enhanced Dataset Overview

198 dataset files loaded from 4 voltage configurations (2.5V, 5.0V, 10V, High Voltage up to 200V) with 19,314 total data points. These enhanced datasets train our AI model for near-perfect fault prediction accuracy across the entire voltage spectrum.

2.5V External Input Fault Datasets

Files: 72
Estimated Rows: 6,998
Memory Estimate: 1.4 MB
Last Modified: 2025-11-25 02:28:38
Sampling Rates:
100ms: 24 10ms: 24 50ms: 24
Phases:
No phase data available

5.0V External Input Fault Datasets

Files: 72
Estimated Rows: 7,000
Memory Estimate: 1.4 MB
Last Modified: 2025-11-25 02:51:36
Sampling Rates:
100ms: 24 10ms: 24 50ms: 24
Phases:
No phase data available

10V External Input Fault Datasets

Files: 54
Estimated Rows: 5,316
Memory Estimate: 1.2 MB
Last Modified: 2025-11-25 02:46:14
Sampling Rates:
100ms: 18 10ms: 18 50ms: 18
Phases:
No phase data available

The Enhanced Physics-Informed AI System Status

AI Model
ENHANCED
Trained on 800 samples
Accuracy
98.0%
Excellent
Training Data
800
Enhanced samples from all sources
Voltage Range
2.5V-200V
Extended high voltage support

High Voltage (up to 200V) Support

High Voltage Physics

Our enhanced AI model incorporates advanced high voltage physics principles:

  • Non-linear arc resistance increases with voltage due to plasma dynamics
  • Enhanced energy dissipation models for high power fault conditions
  • Voltage-dependent time constants for transient response
  • System dependency scaling for accurate fault current prediction

For high voltage conditions (V > 100V):

\[ I_{sc} = k_1 \cdot V_{initial}^\gamma \cdot e^{-k_2 \cdot t \cdot V_{initial}^\beta} + k_3 \cdot V_{initial}^\delta \]

\[ V_{sc} = V_{initial} \cdot (1 - \alpha \cdot V_{initial}^\varepsilon) \cdot e^{-\lambda \cdot t \cdot V_{initial}^\zeta} \]

where the coefficients scale non-linearly with voltage.

High Voltage Patterns

The AI model recognizes distinct patterns at different voltage levels:

Voltage Range Characteristic Pattern AI Confidence
2.5V - 10V Linear resistance decay 98%
10V - 50V Exponential current surge 96%
50V - 100V Complex transient oscillations 94%
100V - 200V Multi-stage arc formation 92%
Research Insight: At higher voltages, fault currents exhibit more complex transient behavior due to electromagnetic effects and plasma formation, which our enhanced AI model accurately captures.

Most Recent Reading - Updated Every 60 Seconds

Latest Reading

1
Reading ID

Timestamp

11:05:25
2026-07-20

Experiment

5.0V - After Short Circuit
After Short Circuit

Resistance Method

Modified Ohm's Law
R = R₀ + V/(I·k)
Voltage
4.600000 V
Updated: 11:05:25
Current
12.500000 A
Updated: 11:05:25
Resistance
0.370000 Ω
Modified Ohm's Law
Power
57.500000 W
P = V × I
Before Short Circuit Resistance

Standard Ohm's Law:

\[ R = \frac{V}{I} \] \[ P = V \times I \]
Where R = resistance (Ω), V = voltage (V), I = current (A), P = power (W)
After Short Circuit Resistance

Modified Ohm's Law:

\[ R = R_0 + \frac{V}{I \cdot k} \] \[ P = V \times I \]
Where R₀ = 0.1Ω (minimum resistance), k = system dependency factor = log(1 + Vinput/5.0)
The Modified Ohm's Law formulation suggests that resistance does not entirely diminish to zero during a short circuit, implying that voltage cannot be zero.

Enhanced AI Fault Data Generator

Fault Open Data Configuration Parameters

2.5V 50V 100V 150V 200V
Input voltage for simulation - higher voltages produce more severe fault conditions with complex transient patterns
Fault Open Data Access Parameters
Number of synthetic data points to generate (max 200,000) - Larger datasets provide better pattern recognition

Enhanced Physics-Informed AI Architecture

System-Dependent Physics Model v6.0-Enhanced
  • Core Physics Principle Enhanced System-Dependent Fault Dynamics
  • Voltage-Current Relationship Nonlinear Power Law: I ∝ V^1.6
  • Energy Dissipation P_loss = I²R ∝ V^3.2
  • Arc Resistance Dynamics R_arc ∝ 1/V^0.8
  • High Voltage Support Up to 200V with enhanced patterns
  • Pattern Recognition Advanced AI learning from datasets
Enhanced Mathematical Foundation:

\[ I_{sc} = k_1 \cdot V_{initial}^\gamma \cdot e^{-k_2 \cdot t \cdot V_{initial}^\beta} + k_3 \cdot V_{initial}^\delta \]

\[ V_{sc} = V_{initial} \cdot (1 - \alpha \cdot V_{initial}^\varepsilon) \cdot e^{-\lambda \cdot t \cdot V_{initial}^\zeta} \]

\[ P_{sc} = V_{sc} \times I_{sc} \]

Enhanced Physics Insight.

Our enhanced model demonstrates that fault quantities exhibit complex system-dependent behavior across the entire voltage spectrum. Higher input voltages create more severe fault conditions with disproportionately higher short circuit currents, complex transient patterns, and enhanced energy dissipation in the arc plasma. The AI learns from multiple datasets to recognize these patterns with near-perfect accuracy.

Data Quality Assurance.

All generated data undergoes automatic validation to ensure: No zero values, No NaN values, and Physically realistic patterns based on learned behavior from experimental datasets.

Live Sensor Status and Phase Detection

AI-FAULTGEN Enhanced Database Cluster: Offline

No active databases found. Please check database configuration.

Cluster Offline

Enhanced Database Cluster Connection Required

Please check your database configuration in conn.php and ensure all 12 enhanced databases are properly created and accessible.

Required databases include: 2.5V, 5V, 10V, 50V, 100V, and 200V configurations for both before and after short circuit conditions