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2018-phm-data-challenge

2018 phm data challenge, ion mill machine RUL & fault diagnosis

2019iflytek2019_top2

awesome_deep_learning_interpretability

深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)

deep-learning-in-phm

Deep learning in PHM，Deep learning in fault diagnosis，Deep learning in remaining useful life prediction

deep-ttf

Survival analsyis and time-to-failure predictive modeling using Weibull distributions and Recurrent Neural Networks in Keras

deeplearning-models

A collection of various deep learning architectures, models, and tips

deepssl

Remaining Useful Life prediction with a Deep Self-Supervised Learning Approach

hiconstruct_optimize

Contains code to compare several health index construction methods using run-to-failure bearing dataset

keras-wtte-rnn

Demo Weibull Time-to-event Recurrent Neural Network in Keras

prognostics_weighted_ensemble

code repository for the owner's paper on prognostics

projectrul

to prediction the remain useful life of bearing based on 2012 PHM data

pytorch-autoencoders

Autoencoders in PyTorch

pytorch-cnn-for-rul-prediction

PyTorch implementation of CNN for remaining useful life prediction. Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep convolutional neural network-based regression approach for estimation of remaining useful life. In International conference on database systems for advanced applications (pp. 214-228). Springer, Cham.

rul-net

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine

rul_codes_open

This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.

survival-analysis

Application of survival analysis, predictive maintenance, churn analysis, remaining useful life prediction

tfdeepsurv

COX Proportional risk model and survival analysis implemented by tensorflow.

torch-wtte

A PyTorch implementation of Weibull Time to Event Recurrent Neural Networks for churn prediction tasks.

weibull-knowledge-informed-ml

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

wtte-rnn

WTTE-RNN a framework for churn and time to event prediction

wtte-torch

Weibull Time To Event prediction with PyTorch and deep learning