|本期目录/Table of Contents|

[1]于 波,杨可玉.基于LabVIEW和BP神经网络的旋转机械故障诊断研究[J].工业仪表与自动化装置,2020,(06):32-34.[doi:1000-0682(2020)06-0000-00]
　YU Bo,YANG Keyu.Research on fault diagnosis of rotating machinery based on LabVIEW and BP neural network[J].Industrial Instrumentation & Automation,2020,(06):32-34.[doi:1000-0682(2020)06-0000-00]
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基于LabVIEW和BP神经网络的旋转机械故障诊断研究

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2020年06期
页码:
32-34
栏目:
出版日期:
2020-12-15

文章信息/Info

Title:
Research on fault diagnosis of rotating machinery based on LabVIEW and BP neural network
作者:
于 波; 杨可玉
东北石油大学 物理与电子工程学院，黑龙江 大庆 163318
Author(s):
YU Bo; YANG Keyu
School of Physics and Electronic Engineering,Northeast Petroleum University,Heilongjiang Daqing 163318, China
关键词:
旋转机械; LabVIEW; BP神经网络; 故障诊断
Keywords:
rotating machinery;  LabVIEW;  BP neural network;  fault diagnosis
分类号:
TH165+.3
DOI:
1000-0682(2020)06-0000-00
文献标志码:
A
摘要:
旋转机械产生的振动信号是复杂的非平稳信号，使用单一的BP神经网络，难以快速分析出故障的状态。该文研究了基于LabVIEW和BP神经网络的旋转机械故障诊断。利用LabVIEW软件作为测试平台，对旋转机械的振动信号进行分析和提取，构造出特征向量，以此作为BP神经网络的故障样本进行训练。实验结果表明，BP神经网络能够快速收敛到目标精度，为旋转机械故障状态诊断积累了应用经验。
Abstract:
The vibration signal produced by rotating machinery is a complex non-stationary signal. Using a single BP neural network, it is difficult to analyze the fault state quickly. This paper studies the fault diagnosis of rotating machinery based on LabVIEW and BP neural network. Using LabVIEW software as the test platform, the vibration signal of rotating machinery is analyzed and extracted, and the eigenvector is constructed, which is used as the fault sample of BP neural network for training. Finally, the experimental results show that the BP neural network can quickly converge to the target accuracy, which accumulates the application experience for the fault diagnosis of rotating machinery.

参考文献/References:

[1] 林水泉.旋转机械故障诊断技术及其发展趋势[J].化工机械,2019,46(06):607-610.

[2] 邴智刚,李威霖,陈锋,等.基于虚拟仪器的旋转机械主轴故障在线监测系统研究[J].机电工程,2016,33(06):722-726.
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[5] 唐贵基,范德功,胡爱军,等.基于小波包能量特征向量神经网络的旋转机械故障诊断[J].汽轮机技术,2006(03):215-217.?div>[6] 李赟恒. 基于BP神经网络的采煤机截割部故障诊断研究[D].西安:西安科技大学,2017.?div>[7] 王勇,师款.基于BP神经网络技术的采煤机齿轮箱早期故障诊断[J].煤矿机械,2019,40(04):158-160.

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备注/Memo

备注/Memo:
收稿日期：2020-05-04
作者简介：于 波（1968），男，黑龙江大庆人，教授，硕士生导师，研究方向为通信信号处理、振动故障诊断技术研究。
更新日期/Last Update: 1900-01-01