biswajitsahoo1111/cbm_codes_open
This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.
This helps operations engineers and maintenance professionals analyze sensor data from industrial machinery to detect potential faults early. It takes in historical machine sensor readings and provides clear diagnostic results indicating normal operation or specific fault conditions. Use this to improve predictive maintenance strategies and reduce unexpected downtime.
No commits in the last 6 months.
Use this if you need to automatically identify common machinery faults from sensor data to prevent breakdowns and optimize maintenance schedules.
Not ideal if you need a real-time, production-ready fault detection system that integrates directly with complex industrial control systems.
Stars
96
Forks
36
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 05, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/biswajitsahoo1111/cbm_codes_open"
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....