fault-diagnosis

emadeldeen24/TS-TCC

[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

liguge/Journals-of-Prognostics-and-Health-Management

智能故障诊断和寿命预测期刊（Journals of Intelligent Fault Diagnosis and Remaining Useful Life）

SNBQT/Limited-Data-Rolling-Bearing-Fault-Diagnosis-with-Few-shot-Learning

This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning

iqiukp/KPCA-MATLAB

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).

mingzhangPHD/Transfer-Learning-for-Fault-Diagnosis

This repository is for the transfer learning or domain adaptive with fault diagnosis.

liguge/Fault-diagnosis-for-small-samples-based-on-attention-mechanism

基于注意力机制的少量样本故障诊断 pytorch

Xiaohan-Chen/transfer-learning-fault-diagnosis-pytorch

A transfer learning fault diagnosis repository covering popular algorithms

emadeldeen24/AdaTime

[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

HazeDT/DAGCN

This code is about the implementation of Domain Adversarial Graph Convolutional Network for Fault Diagnosis Under Variable Working Conditions.

HazeDT/WaveletKernelNet

This is the code for WaveletKernelNet.

liguge/1D-Grad-CAM-for-interpretable-intelligent-fault-diagnosis

智能故障诊断中一维类梯度激活映射可视化展示 1D-Grad-CAM for interpretable intelligent fault diagnosis

biswajitsahoo1111/cbm_codes_open

This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.

mingzhangPHD/Few-shot-Learning-for-Fault-Diagnosis

This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.

monologuesmw/bearing-fault-diagnosis-cnn

Siamese network for bearing fault diagnosis

petrobras/BibMon

Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.

Xiaohan-Chen/few-shot-fault-diagnosis

A few shot learning repository for bearing fault diagnosis.

Western-OC2-Lab/Vibration-Based-Fault-Diagnosis-with-Low-Delay

Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.

liguge/EWSNet

Physics-informed Interpretable Wavelet Weight Initialization and Balanced Dynamic Adaptive Threshold for Intelligent Fault Diagnosis of Rolling Bearings pytorch

Yifei20/Few-shot-Fault-Diagnosis-MAML

Implementation of the model-agnostic meta-learning framework on CWRU bearing fault dataset to address cross-domain few-shot fault diagnosis problem.

Xiaohan-Chen/TFPred

An official code for paper: TFPred: Learning discriminative representations from unlabeled data for few-label rotating machinery fault diagnosis

junior209lsj/FaultDiagnosisOptimizerBenchmark

Benchmark code for optimizers of bearing fault diagnosis. This code provides moduled features of data download, preprocessing, training, and logging.

schwxd/awesome-digital-twin

phoenixdyf/Theory-guided-Progressive-Transfer-Learning-Network

Demo code release for TPTLN: Combining the theoretical bound and deep adversarial network for machinery open-set diagnosis transfer

liguge/MDPS_pytorch

A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor Data and Periodic Sampling （pytorch)

biswajitsahoo1111/data_driven_features_ims

Multiclass bearing fault classification using features learned by a deep neural network.

zhiqan/AMPCNN

A Fault Diagnosis Method of Rotor System Based on Parallel Convolutional Neural Network Architecture with Attention Mechanism

liuzy0708/MCC5-THU-Gearbox-Benchmark-Datasets

A benchmark fault diagnosis dataset comprises vibration data collected from a gearbox under variable working conditions with intentionally induced faults, encompassing diverse fault severities and types, and various compound faults.

zhiqan/Random-convolution-layer

Random convolution layer: An auxiliary method to improve fault diagnosis performance

mache102/ma1dcnn-pytorch

PyTorch Implementation of "Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis" by Wang et al.

liuzy0708/CFD-Datasets

Compound Fault Diagnosis Dataset of Rotating Machinery

melli0505/TCN-LSTM

TCN-LSTM Motor Vibration Fault Diagnosis Model

mo26-web/Induction-Motor-Faults-Detection-with-Stacking-Ensemble-Method-and-Deep-Learning

This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.

foryichuanqi/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

Lichen0102/Multi-mode-Fault-Diagnosis-Datasets-with-TE-process

Multi-mode Fault Diagnosis Datasets with TE process (MMFDD-TEP) can be used for the purpose of comparison studies or validation of algorithms

ntkhoa95/Convolutional-Attention-Neural-Network-for-Induction-Motors

Effective Fault Diagnosis Based on Wavelet and Convolutional Attention Neural Network for Induction Motors