E3S Web Conf.
Volume 260, 20212021 International Conference on Advanced Energy, Power and Electrical Engineering (AEPEE2021)
|Number of page(s)||7|
|Section||Electrical Engineering and Automation|
|Published online||19 May 2021|
Software design of rotating machinery fault diagnosis system based on deep learning
1 Jiangsu Frontier Electric Technologies Co., Ltd., 211102, Nanjing, China
2 School of Energy and Power Engineering, Huazhong University of Science & Technology, 430074 Wuhan, China
* Corresponding author: email@example.com
With the development of Industry 4.0, in order to meet the needs of intelligent fault diagnosis of rotating machinery in the industrial field, this paper developed a fault diagnosis system for rotating machinery based on deep learning and wavelet transform methods. The system is based on the Python language and mainly combines the PyQt graphical interface framework and the TensorFlow machine learning framework to complete the training requirements for historical or online fault data, and perform online monitoring and diagnosis of equipment operating conditions. The diagnostic accuracy of the system test results is more than 95%, the software interface is friendly, the algorithm generalization ability is good, and the reliability is strong. It provides guidance for the diagnosis of rotating machinery.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.