Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.
Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs
This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Partially inspired by Zheng, S., Ristovski, K., Farahat, A., & Gupta, C. (2017, June). Long short-term memory network for remaining useful life estimation.
锂电池数据集 CALCE
Analysis for NASA data sets
Datasets for Predictive Maintenance
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 prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf
Tool wear prediction by residual CNN
N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)
Predictive Maintenance System for Digital Factory Automation
False Data Injection Attacks in Internet of Things and Deep Learning enabled Predictive Analytics
This project is about predictive maintenance with machine learning. It's a final project of my Computer Science AP degree.
Bearing remaining useful life prediction using support vector machine and hybrid degradation tracking model - Implementation of Research Paper : https://doi.org/10.1016/j.isatra.2019.08.058
A collection of datasets for RUL estimation as Lightning Data Modules.
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