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

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

A transfer learning fault diagnosis repository covering popular algorithms

基于注意力机制的少量样本故障诊断 pytorch

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

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

This is the code for WaveletKernelNet.

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

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

Siamese network for bearing fault diagnosis

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

A few shot learning repository for bearing fault diagnosis.

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

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

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

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

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

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

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

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