Bearing fault detection public datasets collection.

A simple tool for Condition Monitoring.

A simple tool for Condition Monitoring.

The FP-SNS-DATALOG2 function pack represents an evolution of FP-SNS-DATALOG1 and provides a comprehensive solution for saving data from any combination of sensors and microphones configured up to the maximum sampling rate. Please check st.com where a more recent version of the software might be available.

This github repository contains the sample code and exercises of btp-ai-sustainability-bootcamp, which showcases how to build Intelligence and Sustainability into Your Solutions on SAP Business Technology Platform with SAP AI Core and SAP Analytics Cloud for Planning.

This project uses Explainable AI (XAI) to interpret machine learning models for diagnosing faults in industrial bearings. By applying SVM and kNN models and leveraging SHAP values, it enhances the transparency and reliability of machine learning in industrial condition monitoring.

The FP-IND-DATALOGMC function pack for STEVAL-STWINBX1 and EVLSPIN32G4-ACT is a powerful integrated toolkit for the next generation of smart actuators. It is derived from FP-SNS-DATALOG2 function pack and it allows the collection of heterogeneous data. Please check st.com where a more recent version of the software might be available.

A curated collection of papers, articles and datasets to keep modern industrial engineer up-to-date on new strategies for anticipating failures using sensors historical data.

3D Printed Sensors for Electric Motor Condition Monitoring

Code basis for the paper "Monitoring and Adapting the Physical State of a Camera for Autonomous Vehicles" (2023)

Real-time machine status update using MTConnect and MQTT protocols

The FP-SNS-DATALOG1 function pack provides a comprehensive solution to save data from any combination of sensors and microphones configured up to the maximum sampling rate available on STWIN and SensorTile.box

Tidy multi-material machine tool wear dataset for prognostics and health monitoring.

ViMag: A Visual Vibration Toolbox

Prognostics Strategies: Residual Similarity-Based Models

NodeRED, InfluxDB and Grafana all together and pre-configured, ready to use together with the whole ctrlX Automation ecosystem.

This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.

Vibration analysis tool, Signal processing tool

Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).

Condition monitoring of electrical assets are vital to prevent a developing fault from going unnoticed. This project aims to build anomaly detection models to identify significant changes in asset conditions and allow the operators to conduct timely maintenance.