Pinned Repositories
1D_CNN_VibrationSignal_BearingFaultDiagnosis
1D-CNN Vibration Signal Bearing Fault Diagnosis
2017-IndustryBigData
2017工业大数据 风机叶片预测
A-Weakly-Supervised-Learning-based-Oversampling-Framework-for-Imbalanced-Classification
This is a program of a new weakly supervised learning based oversampling framework to solve the imbalanced classification proposed by Min Qian and Yanfu Li. Reference paper：A weakly supervised learning based oversampling framework for class imbalanced fault diagnosis
Adversarial-Multiple-Target-Domain-Adaptation-for-Fault-Classification
This is an implementation of single source multiple target domain adaptation for fault diagnosis
Awesome-domain-adaptation
A collection of AWESOME things about domian adaptation
ChromeAppHeroes
🌈谷粒-Chrome插件英雄榜, 为优秀的Chrome插件写一本中文说明书, 让Chrome插件英雄们造福人类~ ChromePluginHeroes, Write a Chinese manual for the excellent Chrome plugin, let the Chrome plugin heroes benefit the human~ 公众号「0加1」同步更新
Wind_turbine_failure_prediction
Machine learning applied to wind turbines incipient fault detection.
ZJU-Clock-In
浙江大学健康打卡
wzx1998johnny's Repositories
wzx1998johnny/1D_CNN_VibrationSignal_BearingFaultDiagnosis
1D-CNN Vibration Signal Bearing Fault Diagnosis
wzx1998johnny/A-Weakly-Supervised-Learning-based-Oversampling-Framework-for-Imbalanced-Classification
This is a program of a new weakly supervised learning based oversampling framework to solve the imbalanced classification proposed by Min Qian and Yanfu Li. Reference paper：A weakly supervised learning based oversampling framework for class imbalanced fault diagnosis
wzx1998johnny/Adversarial-Multiple-Target-Domain-Adaptation-for-Fault-Classification
This is an implementation of single source multiple target domain adaptation for fault diagnosis
wzx1998johnny/Awesome-domain-adaptation
A collection of AWESOME things about domian adaptation
wzx1998johnny/ChromeAppHeroes
🌈谷粒-Chrome插件英雄榜, 为优秀的Chrome插件写一本中文说明书, 让Chrome插件英雄们造福人类~ ChromePluginHeroes, Write a Chinese manual for the excellent Chrome plugin, let the Chrome plugin heroes benefit the human~ 公众号「0加1」同步更新
wzx1998johnny/comments-for-awesome-courses
名校公开课程评价网
wzx1998johnny/contrastive_loss
Experiments with supervised contrastive learning methods with different loss functions
wzx1998johnny/deep-transfer-learning
A collection of implementations of deep domain adaptation algorithms
wzx1998johnny/External-Attention-pytorch
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
wzx1998johnny/Fault-Detection-and-Diagnosis-with-XAI
This python script developed approach which uses various Explainable AI techniques to interpret the results given by fault detection and diagnosis model for Air Handling Units.
wzx1998johnny/Fault-Detection-wind-turbine
Wind turbine fault detection using one class SVM
wzx1998johnny/gpt_academic
为ChatGPT/GLM提供图形交互界面，特别优化论文阅读润色体验，模块化设计支持自定义快捷按钮&函数插件，支持代码块表格显示，Tex公式双显示，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持清华chatglm等本地模型。兼容复旦MOSS, llama, rwkv, 盘古, newbing, claude等
wzx1998johnny/IFD-Preprocessing-Experiment
机器学习背景下旋转机械振动信号故障诊断是否需要信号预处理——使用CWRU数据的一次尝试 Whether signal preprocessing is needed for fault diagnosis of rotating machinery vibration signals in the context of machine learning - an attempt using CWRU data
wzx1998johnny/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）
wzx1998johnny/openfast
Main repository for the NREL-supported OpenFAST whole-turbine and FAST.Farm wind farm simulation codes.
wzx1998johnny/pdfdir
PDF导航（大纲/目录）添加工具
wzx1998johnny/pinn_wind_bearing
Python scripts for wind turbine main bearing fatigue life estimation with physics-informed neural networks
wzx1998johnny/PRL-SIF
Build powerful Positive-Unlabeled (PU) learning method with labeling bias.
wzx1998johnny/Robust-control-and-estimator-for-Wind-Turbine-with-Actuator-Fault-Simulation-FAST-NREL-
Robust adaptive control for wind turbine with actuator faults FAST simulator (NREL)
wzx1998johnny/SEE-MTDA-Unsupervised-Multi-Target-Domain-Adaptation
(RA-L 2022) See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation.
wzx1998johnny/SimCLRv2---Big-Self-Supervised-Models-are-Strong-Semi-Supervised-Learners
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
wzx1998johnny/Targeted-Supervised-Contrastive-Learning-for-Long-tailed-Recognition
A PyTorch implementation of the paper Targeted Supervised Contrastive Learning for Long-tailed Recognition
wzx1998johnny/TL-Bearing-Fault-Diagnosis
Bearing Fault Diagnosis Employing Transfer Learning Techniques: Domain Adaptation and Domain Generalization
wzx1998johnny/Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
wzx1998johnny/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
wzx1998johnny/Wind-Turbine-Data
This is wind turbine data use to make a IA that predict failure
wzx1998johnny/Wind-Turbine-Driveline-Vibrations-Simscape
Direct-drive 10 MW wind turbine driveline with torque and pitch control and optional transverse vibrations
wzx1998johnny/Wind_Turbine_SCADA_open_data
list of open data wind turbine data sets
wzx1998johnny/ZJU_Thesis
Zhejiang University Graduation Thesis LaTeX Template
wzx1998johnny/ZoteroPlugins
zotero插件下载/zotero plugin download下载链接位于docs/README.md