|本期目录/Table of Contents|

[1]何军红,陈天宇.基于Hilbert-Huang变换的电机故障诊断系统设计[J].工业仪表与自动化装置,2019,(04):66-69.[doi:1000-0682(2019)04-0000-00]
　HE Junhong,CHEN Tianyu.Design of motor fault diagnosis system based on Hilbert-Huang transform[J].Industrial Instrumentation & Automation,2019,(04):66-69.[doi:1000-0682(2019)04-0000-00]
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基于Hilbert-Huang变换的电机故障诊断系统设计

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

卷:
期数:
2019年04期
页码:
66-69
栏目:
出版日期:
2019-08-15

文章信息/Info

Title:
Design of motor fault diagnosis system based on Hilbert-Huang transform
作者:
何军红; 陈天宇
西北工业大学 航海学院，西安 710072
Author(s):
HE Junhong; CHEN Tianyu
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
关键词:
设备健康; 振动; Hilbert-Huang变换;  频率分析
Keywords:
equipment health;  vibration;  Hilbert-Huang transform;  frequency analysis
分类号:
TP274+.2
DOI:
1000-0682(2019)04-0000-00
文献标志码:
A
摘要:
机械设备在人类文明发展进程中发挥着不可或缺的重要作用，摆在工程技术人员面前的机械设备维修是一项繁重的任务。在工业生产过程中，设备的故障往往是逐渐形成的。如果能在设备出现故障的过程中提前发现设备的健康问题，提前做好设备的保养与维修，就能提高生产效率，有效地避免生产事故和设备损伤。随着近年计算机运算能力的提高，针对设备健康诊断的方案也愈加成熟。Hilbert-Huang变换可以根据信号本身的局部特征自适应地将信号分解成若干固有模态函数，从根本上解决了用基函数拼凑信号带来的固定基函数、最佳基选择、恒定多分辨率以及能量泄漏等问题，更适合于非线性非平稳信号的处理。该文介绍了一种基于Hilbert-Huang变换的电机故障诊断方案。
Abstract:
Mechanical equipment plays an indispensable role in the development of human civilization,it is a heavy task to maintain mechanical equipment in front of engineers and technicians. Equipment failures are often formed in industrial production processes.If the health problems of the equipment can be found in advance in the process of equipment failure, maintenance and repair of the equipment in advance can improve production efficiency and avoid production accidents and equipment damage.With the development of computer computing ability in recent years,the solution for equipment health diagnosis has become more mature.The Hilbert-Huang transform can adaptively decompose the signal into several intrinsic mode functions according to the local features of the signal itself, which fundamentally solves the fixed basis function, the optimal basis selection and the constant multi-resolution brought by the base function patching signal. And energy leakage and other issues, more suitable for the processing of nonlinear non-stationary signals. This paper introduces a set of solutions for motor fault diagnosis based on Hilbert-Huang transform.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2018-11-27
作者简介：何军红(1971)，男，副教授，主要研究方向为控制工程，嵌入式系统开发，工业互联网与大数据、数字化车间与智能制造。
更新日期/Last Update: 1900-01-01