foryichuanqi's starred repositories
ADVEI-Paper-2024.3-Degradation-path-approximation-for-remaining-useful-life-estimation
Remaining useful life prediction. Degradation path approximation (DPA) is a highly easy-to-understand and brand-new solution way for data-driven RUL prediction. Many research directions on DPA can be further studied.
ADVEI-Paper-2023.11-Zero-shot-fault-diagnosis-by-attribute-fusion-transfer
Zero-shot fault diagnosis on the Tennessee–Eastman process by attribute fusion transfer. Paper: Attribute fusion transfer for zero-shot fault diagnosis
TKDE-Paper-2023.10-Time-series-classification-by-MEB-ResNet
Paper: Multi-Scale Ensemble Booster for Improving Existing TSD Classifiers. We proposed a highly easy-to-use performance enhancement framework called multi-scale ensemble booster(MEB), helping existing time series classification methods achieve performance leap. Our proposed MEB-ResNet achieved the most advanced time series classification ability.
RESS-Paper-2022.09-Remaining-useful-life-prediction-by-TaFCN
The source code of paper: Trend attention fully convolutional network for remaining useful life estimation in the turbofan engine PHM of CMAPSS dataset. Signal selection, Attention mechanism, and Interpretability of deep learning are explored.
NASA_RUL_-CMAPS-
Remaining Useful Life (NASA CMAPS Dataset)
LSTM-Keras-CMAPSS
Using LSTM to predict Remaining Useful Life of CMAPSS Dataset
UCR_Time_Series_Classification_Deep_Learning_Baseline
Fully Convlutional Neural Networks for state-of-the-art time series classification
Tensorflow-Deep-Neural-Networks
用Tensorflow实现的深度神经网络。
Deep-Learning-TensorFlow
Ready to use implementations of various Deep Learning algorithms using TensorFlow.
Mechanical-Fault-Diagnosis-Based-on-Deep-Learning
CNN for mechanical fault diagnosis