ring-Fault-Detection-using-Deep-Learning-approach
所属分类：模式识别(视觉/语音等)
开发工具：Jupyter Notebook
文件大小：855KB
下载次数：4
上传日期：2022-02-09 21:03:38
上 传 者：
sh-1993
说明： 使用深度学习方法进行轴承故障检测，使用凯斯西储大学的图像分类进行轴承故障的检测和多类分类...
(Detection and multi-class classification of Bearing faults using Image classification from Case Western Reserve University data of bearing vibrations recorded at different frequencies. Developed an algorithm to convert vibrational data into Symmetrized Dot Pattern images based on a Research paper. Created an Image dataset of 50 different)
文件列表:
Baic CNN model.ipynb (215870, 2022-02-10)
Developing Algorithm for SDP images and Creating a data set.ipynb (422805, 2022-02-10)
Training and Testing SDP images using CNN model.ipynb (556744, 2022-02-10)
classification_sdp_.ipynb (322863, 2022-02-10)
# Bearing-Fault-Detection-using-Deep-Learning-approach
Detection and multi-class classification of Bearing faults using Image classification from Case Western Reserve University data of bearing vibrations recorded at different frequencies. Developed an algorithm to convert vibrational data into Symmetrized Dot Pattern images based on a Research paper. Created an Image dataset of 50 different parameters and 4 different fault classes, to select optimum parameters for efficient classification. Trained and tested 50 different datasets on different Image-net models to obtain maximum accuracy. Obtained an accuracy of ***% for Binary classification of Inner and Outer race faults on Efficient Net B7 model on just 5 epochs.
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