LeonGuo1988 / RemainingUsefulLife
It is a collection of all kinds of feature extraction and recognition algorithms
☆13Updated 9 years ago
Related projects: ⓘ
- data set and models for IEEE access paper "Remaining Useful Life Estimation Using Long Short-Term Memory Neural Networks and Deep Fusion"☆19Updated 4 years ago
- A naive LSTM implementation for battery RUL prediction☆14Updated 3 years ago
- ☆16Updated 5 years ago
- For better estimation of aero-engine RUL, we concatenate 1-D CNN and LSTM in a parallel structure.☆12Updated 4 years ago
- RUL Prognostics Method Based on Real Time Updating of LSTM Parameters☆20Updated 6 years ago
- Capacity values of Lithium Ion Battery is used as a prognostic method in order to predict the remaining useful life of Lithium-ion batter…☆34Updated 4 years ago
- Source codes for paper "A weighted multi-scale dictionary learning model and its applications on bearing fault diagnosis"☆40Updated 4 years ago
- Source codes for paper "Enhanced sparse period-group lasso for bearing fault diagnosis"☆17Updated 4 years ago
- 基于相似性的剩余寿命预测☆14Updated 4 years ago
- This LSTM is used to predict the rest useful lifetime of ball-bearings. Its programmed with Pytorch and uses the PRONOSTIA Dataset.☆18Updated 4 years ago
- RUL Nasa Turbofan Dataset (paper)☆26Updated 4 years ago
- This project aims to propose a TCN-Based Bayesian neural nework that is used for remaining useful life prediction.☆15Updated 3 years ago
- A hybrid approach using physical information (PI) lightweight temporal convolutional neural networks (PI-TCN) for remaining useful life (…☆19Updated 2 years ago
- Reamain Useful Life Prediction of Bearing☆9Updated last year
- An artificial neural network (ANN) based method is developed for achieving more accurate remaining useful life prediction of Lithium Ion …☆14Updated 2 years ago
- PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Pa…☆12Updated last year
- Bearing fault diagnosis is important in condition monitoring of any rotating machine. Early fault detection in machinery can save million…☆89Updated 4 years ago
- Comparison of various transfer learning models with the hybridization of an FCNN for battery RUL prediction☆41Updated last year
- FWA-DBN-ELM fault diagnosis 故障诊断 烟花算法优化DBN-ELM的故障诊断☆27Updated last year
- Prediction of battery lifetimes based on a Recurrent Neural Network (RNN) architecture. Data publicly available here: https://doi.org/10.…☆20Updated 4 years ago
- Bayesian Deep Learning for Remaining Useful Life Estimation of Machine Tool Components☆15Updated 2 years ago
- Capacity forecasting of batteries/supercapacitors in estimating their remaining useful life (RUL) using the LSTM network☆18Updated 2 years ago
- ☆24Updated 5 years ago
- Battery Remaining Useful Life (RUL) Prediction based on dataset https://www.kaggle.com/datasets/ignaciovinuales/battery-remaining-useful-…☆12Updated last year
- The code is for the paper "Ma et al. A Two-Stage Integrated Method for Early Prediction of Remaining Useful Life of Lithium-ion Batteries…☆29Updated last year
- Paper-Reproduce: (Sensors-MDPI) Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification☆15Updated last year
- ☆10Updated this week
- MuhammadEsmat / Predictive-Maintenance-Machine-Remaining-Useful-Life-Estimation-using-Deep-Learning-TechniqueDeep Learning algorithm Long-Short-Term-Memory (LSTM) with Feedforward Neural Network (FNN) to predict machine Remaining Useful Life (RUL…☆4Updated 3 years ago
- This repository holds the results of a project on Remaining Useful Lifetime estimation of a turbofan engine for a course of Delft Univers…☆13Updated 6 years ago
- ☆10Updated 5 years ago