FaultGuard: A Generative Approach to Resilient Fault Prediction in Smart Electrical Grids
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Updated
May 31, 2024 - Jupyter Notebook
FaultGuard: A Generative Approach to Resilient Fault Prediction in Smart Electrical Grids
Inspired by the idea of transfer learning, a combined approach is proposed. In the method, Deep Convolutional Neural Networks with Wide First-layer Kernel is used to extract features to classify the health conditions.
Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.
Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.
Code repository for the book 'Machine Learning in Python for Process and Equipment Condition Monitoring, and Predictive Maintenance'
Machine Learning Engineering Spring 2024 Project
Fault Detection Diagnostics (FDD) for HVAC datasets
Gearbox Fault Detection
Repository associated with the paper "Failure Detection and Fault Tolerant Control of a Jet-Powered Flying Humanoid Robot", published in IEEE ICRA 2023.
Inspection of Power Line Assets Dataset (InsPLAD)
ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification
Datasets from a fluid catalytic cracking unit to evaluate FDD techniques
Chemical Engineering final-year project simulating a copper solvent extraction process with control valve faults using PCA and statistical classification to identify when the process enters a fault state
Fault Bearing Classification Analysis dashboard to explore, diagnose and highlight potential factors to predict the fault class based on bearing statistical manufacturing data.
A predictive TinyML model to run classification task on edge MCUs.
This problem statement involved predicting fault impacts on Radio Access Networks KPIs and prioritizing issues that affect data rates—a critical step toward enhancing network performance and preventing customer churn in the telecommunication space.
A framework for Inter-turn fault detection in transformers using wavelet analysis and deep learning
Benchmarking fault detection and diagnosis methods
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