Awais-Asghar/Early-Fault-Detection-for-Induction-Motor-Using-ML
An integrated MATLAB–ML system for early fault detection in induction motors. Detects six faults broken rotor bars, stator short, ground fault, overloading, eccentricity, and voltage imbalance using KNN and Decision Tree models for accurate, unified, and reliable predictive maintenance.
Stars
4
Forks
1
Language
MATLAB
License
MIT
Category
Last pushed
Oct 27, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Awais-Asghar/Early-Fault-Detection-for-Induction-Motor-Using-ML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
petrobras/BibMon
Python package that provides predictive models for fault detection, soft sensing, and process...
hustcxl/Deep-learning-in-PHM
Deep learning in PHM，Deep learning in fault diagnosis，Deep learning in remaining useful life prediction
kokikwbt/predictive-maintenance
Datasets for Predictive Maintenance
biswajitsahoo1111/rul_codes_open
This repository contains code that implement common machine learning algorithms for remaining...
tvhahn/weibull-knowledge-informed-ml
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets....