Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)

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

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

Bearing fault detection public datasets collection.

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.

AI-Powered Predictive Maintenance & Fault Diagnosis through Model Context Protocol. An open-source framework for integrating Large Language Models with predictive maintenance and fault diagnosis workflows.

Deep Learning applied to predictive maintenance use cases

remaining useful life, residual useful life, remaining life estimation, survival analysis, degradation models, run-to-failure models, condition-based maintenance, CBM, predictive maintenance, PdM, prognostics health management, PHM

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

ViMag: A Visual Vibration Toolbox

An implementation of Dissolved Gas Analysis (DGA) assessment algorithms and guidelines in the form of Excel Add-ins.

A comprehensive benchmark of 16 Deep Learning models (including ResNet, LSTM, Transformer, DenseNet) for CWRU Bearing Fault Diagnosis using PyTorch.

Audio-based machine fault recognition with a lightweight PyTorch CNN using PCEN log-mel features, section-aware splits, and Dockerized inference

Vibration analysis tool, Signal processing tool

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

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

Showcase how machine learning can help plant operator monitor equipment condition through correctly analyzing measurement data collected from many sensors.

MCP server for Motor Current Signature Analysis (MCSA) — spectral analysis and fault detection in electric motors in natural language through LLMs