alidi24/deep-learning-fault-diagnosis
A deep learning fault classification model for wind turbine drivetrain bearings using combined PCA-CNN approach
This project helps wind farm operators and maintenance engineers detect bearing faults in wind turbine drivetrains. By inputting vibration data from specific sensors, it outputs a classification indicating if and where a fault exists in the main, low-speed, or high-speed shaft bearings. This allows for proactive maintenance and reduces downtime.
No commits in the last 6 months.
Use this if you need an automated way to classify specific bearing faults in wind turbine drivetrains using vibration data.
Not ideal if you need to diagnose issues other than drivetrain bearing faults or if you don't have access to the specified vibration sensor data.
Stars
7
Forks
—
Language
Python
License
MIT
Category
Last pushed
Feb 27, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/alidi24/deep-learning-fault-diagnosis"
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....