Selected Journal of the Excellence Action Plan for China's Science and Technology Journals (Phase II),Selected Journal of Chinese Applied Core Journals (Extended Edition) / CACJ (Extended),Indexed in the Chinese Core Journals (Selection) Database
Article View

M1DCNN模型在燃气调压器故障诊断的应用

Issue Number Issue 05, 2024 [View other articles in this issue]
DOI
Receiving Time
Revision Time
Publish Date
Publication Date 2024.05.15
Manuscript ID
Author 王  强1,李泽明1,张龙桦2
Organization 1.无锡华润燃气有限公司
2.润智科技有限公司

Abstract

燃气调压器的健康状况直接关系到燃气输配系统的稳定和安全运行,针对调压器的故障识别,需要大量的专家经验,且给燃气企业带来较大的运维成本。本文提出一种基于多尺度一维卷积神经网络(M1DCNN)的燃气调压器故障诊断模型,该模型在一维卷积神经网络的基础上,构建多个不同尺寸卷积核和池化层的通道,分别提取调压器出口压力数据特征信息并进行处理,最后进行特征融合,输出诊断故障类别。实验结果表明,M1DCNN模型能更全面的提取故障特征,有效进行故障识别,实现调压器智能故障诊断。

Keywords

燃气调压器;CNN;多尺度特征提取;故障诊断

References

Declaration:

The English version of this article is translated with the assistance of AI.

Related Articles

Contact Us
Urban Gas Magazine Co., Ltd.
Address:
Room 1207, Tower B, Financial Street Investment Plaza, Xicheng District, Beijing 100045, China
Tel:
+86-10-66020170
Advertising Department:
+86-18611817393
Circulation Department:
+86-18518361665

 

Gas800.com 版权所有 Copyright @ 2006-2026 京ICP备19057877号-1

京公网安备 11010802030632号