GitHub topics: prognostics-health-management

Repositories

nasa/progpy

The NASA Prognostic Python Packages is a Python framework focused on defining and building models and algorit for prognostics (computation of remaining useful life) of engineering systems, and provides a set of models and algorithms for select components developed within this framework, suitable for use in prognostic applications.

Language: Python - Size: 38.6 MB - Last synced at: 3 days ago - Pushed at: 16 days ago - Stars: 93 - Forks: 18

nasa/prog_models

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.

Size: 12.1 MB - Last synced at: 8 days ago - Pushed at: over 1 year ago - Stars: 125 - Forks: 52

RamtinMoslemi/RUL-Papers

An awesome list of papers on remaining useful life (RUL) prediction from arXiv

Language: Jupyter Notebook - Size: 26.7 MB - Last synced at: 20 days ago - Pushed at: about 2 months ago - Stars: 9 - Forks: 0

kiki101robo/Spacecraft_Pressurevalve_Health

This project aims to enhance Prognostics and Health Management (PHM) technologies for spacecraft propulsion systems. Developed as part of the JAXA Challenge. This study uses telemetry data and a numerical simulator to predict the dynamic response of spacecraft propulsion systems, focusing on fault detecti

Language: Jupyter Notebook - Size: 869 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

nasa/prog_server

The NASA Prognostics As-A-Service (PaaS) Sandbox is a simplified implementation of a Software Oriented Architecture (SOA) for performing prognostics (estimation of time until events and future system states) of engineering systems. The PaaS Sandbox is a wrapper around the Prognostics Algorithms Package and Prognostics Models Package, allowing one or more users to access the features of these packages through a REST API. The package is intended to be used as a research tool to prototype and benchmark Prognostics As-A-Service (PaaS) architectures and work on the challenges facing such architectures, including Generality, Communication, Security, Environmental Complexity, Utility, and Trust.

Language: Python - Size: 1.28 MB - Last synced at: about 13 hours ago - Pushed at: 19 days ago - Stars: 10 - Forks: 7

RidgetopGroupInc/ARULE4Python

Implementation of UD_ARULE CLI version within Python to process feature data (FD) nodes of a system/system-of-systems to predict key prognostic parameters such as RUL, PH, and SoH

Language: Python - Size: 4.23 MB - Last synced at: 7 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

modern-engineer/condition-monitoring-academy

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.

Size: 21.5 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

tvhahn/weibull-knowledge-informed-ml

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

Language: Python - Size: 42.9 MB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 115 - Forks: 35

xxl4tomxu98/NASA-Jet-Engine-Maintenance

ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification

Language: Jupyter Notebook - Size: 220 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 20 - Forks: 3

nasa/prog_algs

The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.

Size: 4.45 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 53 - Forks: 22