# Deep_Learning_For_Fault_Diagnosis
# 基于深度学习的故障诊断
Date: 2023/11/29 22:58
Author: Tan Qiyu
Citation:[1]谭启瑜,马萍,张宏立.基于图卷积神经网络的滚动轴承故障诊断[J].噪声与振动控制,2023,43(06):101-108+116.
E-mail：[email protected]
Home: https://github.com/Tan-Qiyu
Dataset Download Link：https://github.com/Tan-Qiyu/Mechanical_Fault_Diagnosis_Dataset
This repository mainly stores mechanical fault diagnosis codes based on deep learning, including the following stages: data preprocessing, building deep learning model training, validation, and visualization.
The data preprocessing converts the original vibration signals into one-dimensional original signals and different types of two-dimensional image signals as model inputs.
The network model includes one-dimensional and two-dimensional deep learning models,
and visualization validation includes loss maps The visualization results of TSNE features, classification confusion matrix, and some parts still need further improvement due to time constraints.
毕设&课程作业_基于深度学习的机械故障诊断.zip
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毕设&课程作业_基于深度学习的机械故障诊断.zip （89个子文件） 
Graduation Design 深度学习故障诊断 
generate_dataset.py 11KB dataset_1d __init__.py 88B SQV.py 5KB UoC.py 4KB JNU.py 4KB XJTU.py 5KB CWRU.py 5KB MFPT.py 4KB QianPeng_gear.py 5KB SEU.py 5KB __user_functions.py 3KB Bearing311.py 6KB __pycache__ MFPT.cpython-39.pyc 3KB CWRU.cpython-39.pyc 3KB DC.cpython-39.pyc 3KB wind_gearbox.cpython-39.pyc 3KB QianPeng_gear.cpython-39.pyc 4KB __init__.cpython-39.pyc 290B UoC.cpython-39.pyc 3KB XJTU.cpython-39.pyc 3KB SQV.cpython-39.pyc 4KB Bearing311.cpython-39.pyc 3KB JNU.cpython-39.pyc 3KB __user_functions.cpython-39.pyc 2KB SEU.cpython-39.pyc 3KB DC.py 4KB wind_gearbox.py 4KB utils __init__.py 88B _confusion.py 4KB save_data.py 2KB train_utils.py 10KB _tsne.py 2KB __pycache__ __init__.cpython-39.pyc 285B save_data.cpython-39.pyc 2KB train_utils.cpython-39.pyc 6KB _confusion.cpython-39.pyc 3KB _tsne.cpython-39.pyc 2KB dataset_2d _gen_recurrence_image.py 1KB _user_functions.py 3KB __init__.py 88B JNU_image_dataset.py 5KB _gen_cwt_tf_image.py 2KB SEU_image_dataset.py 6KB DC_image_dataset.py 5KB _gen_MarkovTransField_image.py 1KB Bearing311_image_dataset.py 7KB _gen_gaf_image.py 966B Uoc_image_dataset.py 5KB WindGearbox_image_dataset.py 5KB _load_image_dataset.py 3KB XJTU_image_dataset.py 6KB SQV_image_dataset.py 6KB __pycache__ CWRU_image_dataset.cpython-39.pyc 4KB MFPT_image_dataset.cpython-39.pyc 3KB QianPeng_image_dataset.cpython-39.pyc 4KB DC_image_dataset.cpython-39.pyc 3KB JNU_image_dataset.cpython-39.pyc 3KB _load_image_dataset.cpython-39.pyc 2KB Bearing311_image_dataset.cpython-39.pyc 4KB __init__.cpython-39.pyc 287B _user_functions.cpython-39.pyc 3KB _gen_recurrence_image.cpython-39.pyc 1KB SEU_image_dataset.cpython-39.pyc 3KB _gen_MarkovTransField_image.cpython-39.pyc 1KB XJTU_image_dataset.cpython-39.pyc 4KB Uoc_image_dataset.cpython-39.pyc 3KB WindGearbox_image_dataset.cpython-39.pyc 3KB _gen_gaf_image.cpython-39.pyc 1KB SQV_image_dataset.cpython-39.pyc 4KB _gen_cwt_tf_image.cpython-39.pyc 2KB QianPeng_image_dataset.py 6KB CWRU_image_dataset.py 6KB MFPT_image_dataset.py 5KB models __init__.py 88B CNN_1D.py 3KB AlexNet.py 2KB ResNet.py 3KB DenseNet.py 3KB __pycache__ ResNet.cpython-39.pyc 3KB VGG.cpython-39.pyc 2KB DenseNet.cpython-39.pyc 3KB __init__.cpython-39.pyc 286B AlexNet.cpython-39.pyc 2KB LeNet.cpython-39.pyc 2KB CNN_1D.cpython-39.pyc 2KB LeNet.py 1KB VGG.py 3KB train.py 10KB README.md 1KB资源评论
