alidi24 / bearing-rul-predictionLinks
Deep learning models (RNN & LSTM & WaveNet) for predicting the remaining useful life of rolling element bearings using time series health indicators. Compares performance between different architectures for predictive maintenance applications.
☆24Updated 9 months ago
Alternatives and similar repositories for bearing-rul-prediction
Users that are interested in bearing-rul-prediction are comparing it to the libraries listed below
Sorting:
- case study for remaining useful life estimation☆34Updated last year
- GLIN: Remaining useful life prediction based on fusion of global and local information (Transformer)☆32Updated 2 years ago
- We have developed an innovative deep learning model, PSECNet, for the prediction of bearing Remaining Useful Life (RUL) on the IEEE 2012 …☆31Updated last year
- Produce an example using LSTM to predict remaining useful life of machinery☆16Updated last year
- 基于深度学习的机械故障诊断☆37Updated last year
- Remaining useful life prediction by Transformer-based Model☆53Updated 3 years ago
- Official repository for the paper "Few‐shot multiscene fault diagnosis of rolling bearing under compound variable working conditions"☆18Updated last month
- A fault diagnosis method for rotating machinery based on CNN with mixed information☆44Updated 2 years ago
- Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions☆35Updated last week
- A Unified Framework for Prognostics and Health Management (PHM) Tasks, enabling streamlined execution of key tasks such as Remaining Usef…☆45Updated last month
- The source code of paper: Trend attention fully convolutional network for remaining useful life estimation in the turbofan engine PHM of …☆61Updated 2 years ago
- code for TII paper "Intelligent Mechanical Fault Diagnosis Using Multi-Sensor Fusion and Convolution Neural Network"☆38Updated 3 years ago
- This work presents a multi-feature fusion neural network (MSFN) comprised of two inception layer-type multiple channel networks (MCN) for…☆19Updated 4 years ago
- ☆33Updated 2 years ago
- The implementation of Weighted Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction in PyTorch.☆37Updated 2 years ago
- TL-UESTC / Privacy-Preserving-Adaptive-Remaining-Useful-Life-Prediction-via-Source-Free-Domain-AdaptionThe implementation of Privacy-Preserving Adaptive Remaining Useful Life Prediction via Source-Free Domain Adaption in PyTorch.☆25Updated 9 months ago
- ☆23Updated 4 years ago
- Interpretable Physics-informed Domain Adaptation Paradigm for Cross-machine Transfer Fault Diagnosis (故障诊断)☆40Updated last year
- GTFE-Net: A Gramian Time Frequency Enhancement CNN for bearing fault diagnosis☆39Updated 2 years ago
- Physics-informed Interpretable Wavelet Weight Initialization and Balanced Dynamic Adaptive Threshold for Intelligent Fault Diagnosis of R…☆92Updated 7 months ago
- An AI-based system utilizing Graph Neural Networks (GNNs) for real-time anomaly detection and fault diagnosis in spacecraft engines. It c…☆16Updated last year
- Importance-aware Subgraph Convolutional Networks Based on Multi-source Information Fusion for Cross-domain Mechanical Fault Diagnosis☆49Updated 9 months ago
- Implementation of GCU-Transformer for RUL Prediction on CMAPSS☆41Updated 7 months ago
- Pytorch implementation for Domain Adaptive Remaining Useful Life Prediction with Transformer☆80Updated 2 years ago
- ☆36Updated 3 years ago
- 基于Laplace小波卷积和BiGRU的少量样本故障诊断方法 (Small sample fault diagnosis based on Laplace wavelet convolution and BiGRU)☆65Updated 6 months ago
- ☆34Updated 3 years ago
- An official code for paper: TFPred: Learning discriminative representations from unlabeled data for few-label rotating machinery fault di…☆67Updated last year
- ☆65Updated 5 years ago
- This project aims to propose a TCN-Based Bayesian neural nework that is used for remaining useful life prediction.☆22Updated 4 years ago