Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)
condition-monitoring fault-data rolling-element-bearings prognostics rotating-machinery-fault-diagnosis femto-st mfpt
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condition-monitoring
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Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
machine-learning deep-learning pytorch manufacturing weibull remaining-useful-life condition-monitoring bearing-fault-diagnosis ims-bearing-data-set prognostics-health-management pronostia-dataset knowledge-informed-machine-learning
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This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.
machine-learning deep-learning cwru condition-monitoring bearing-fault-diagnosis fault-diagnosis machinery-condition-monitoring
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Bearing fault detection public datasets collection.
cwru condition-monitoring bearing-fault-diagnosis rolling-element-bearings prognostics vibration-analysis
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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.
sample machine-learning sustainability computer-vision deep-learning image-segmentation sample-code predictive-maintenance condition-monitoring sound-classification defect-detection sap-analytics-cloud sap-ai-core sap-ai-launchpad sac-planning
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Deep Learning applied to predictive maintenance use cases
pytorch lstm classification sensors attention-mechanism multi-task time-series-analysis predictive-maintenance condition-monitoring fault-types
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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
survival-analysis pdm predictive-maintenance rul remaining-useful-life condition-monitoring cbm failure-prediction condition-based-maintenance prognostics phm rul-prediction remaining-life-estimation residual-useful-life degradation-models run-to-failure-models prognostics-health-management
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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.
signal-processing iiot predictive-analytics anomaly-detection asset-management envelope-analysis predictive-maintenance condition-monitoring machine-failure bearing-fault-diagnosis industrial-iot fault-diagnosis vibration-analysis claude-ai industry-4-0 model-context-protocol mcp-server fastmcp iso10816 claude-agents
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- Python
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.
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Tidy multi-material machine tool wear dataset for prognostics and health monitoring.
machine-learning opendata dataset industrial milling predictive-maintenance condition-monitoring prognostics tool-wear
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An implementation of Dissolved Gas Analysis (DGA) assessment algorithms and guidelines in the form of Excel Add-ins.
diagnosis dga asset-management dissolved-gas-analysis power-transformers oil-analysis condition-monitoring condition-assessment duval-triangle duval-triangle-excel duval-pentagon-excel duval-pentagon iec-60599
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ViMag: A Visual Vibration Toolbox
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Vibration analysis tool, Signal processing tool
python fft netcdf4 gearbox condition-monitoring plotly-dash vibrational-analysis bearing-fault-diagnosis
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Code basis for the paper "Monitoring and Adapting the Physical State of a Camera for Autonomous Vehicles" (2023)
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Showcase how machine learning can help plant operator monitor equipment condition through correctly analyzing measurement data collected from many sensors.
pca autoencoder anomaly-detection mahalanobis-distance predictive-maintenance condition-monitoring bearing-fault-diagnosis
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- Jupyter Notebook
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
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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.
svm knn shapely condition-monitoring explainable-ai bearing-fault-diagnosis rotating-machinery-fault-diagnosis shap-values
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An AI-driven Prognostics and Health Management (PHM) system for predictive maintenance. This project features a FastAPI for real-time condition monitoring, advanced models for fault detection, and Remaining Useful Life (RUL) prediction. It integrates digital twin concepts and Explainable AI (XAI) for transparent and reliable industrial asset manage
cookiecutter health-management predictive-maintenance remaining-useful-life condition-monitoring explainable-ai digital-twin machine-learning-projects fastapi industrial-iot prognostics fault-detection-and-diagnosis
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- Python
The STDATALOG_PYSDK is a comprehensive Python framework designed to facilitate the capture, processing, and visualization of data from a wide range of sources. It was formerly known as HSDPython_SDK, previously distributed in FP-SNS-DATALOG2 and FP-IND-DATALOGMC function packs.
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- CSS
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