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《无线互联科技》杂志社 ›› 2025, Vol. 22 ›› Issue (1): 59-62.

• 技术应用 • 上一篇    下一篇

HHT算法在船舶轴系扭振监测系统中的应用

党艳, 陈智*, 李艳能, 郭慧玲, 董晶   

  1. 兰州信息科技学院 计算机与人工智能学院,甘肃 兰州 730300
  • 出版日期:2025-01-10 发布日期:2025-03-21
  • 通讯作者: * 陈智(1983— ),男,副教授,硕士;研究方向:电子信息工程。
  • 作者简介:党艳(1994— ),女,硕士研究生;研究方向:信号处理。

Application of HHT algorithm in ship shafting torsional vibration monitoring system

DANG Yan, CHEN Zhi*, LI Yaneng, GUO Huiling, DONG Jing   

  1. School of Computer and Artificial Intelligence, Lanzhou University of Information Science and Technology, Lanzhou 730300, China
  • Online:2025-01-10 Published:2025-03-21

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摘要： 在分析实际测量信号的具体特征时,经常采用EMD分解法获取信号的各特征分量,但用此方法得到的各IMF分量包含了混叠模态信号,导致后续分解过程困难。为解决模态混叠现象对信号特征分析结果的影响,文章对中船重工某研究所采集到的某5缸机船舶轴系振动监测数据信息分别利用EMD分解方法和改进EMD分解方法即集合经验模态分解法(EEMD)对其进行处理分析,从而验证了EEMD分解方法具有抗模态混叠的优越性能。最后,文章对分解的各IMF分量进行HHT变换,得到各信号的边际谱特征。

关键词: EMD, EEMD, 扭振监测

Abstract: When analyzing the specific characteristics of actual measured signals, EMD decomposition method is often used to obtain each characteristic component of the signal, but each IMF component obtained by this method contains aliasing mode signals, which makes the subsequent decomposition process difficult. In order to solve the influence of mode aliasing phenomenon on the analysis results of signal characteristics, the vibration monitoring data of a 5-cylinder ship shafting collected by a research institute of China Shipbuilding Heavy Industry were processed and analyzed by EMD decomposition method and improved EMD decomposition method, namely ensemble Empirical Mode decomposition method (EEMD). It is proved that the EEMD decomposition method has excellent performance of anti-mode aliasing. Finally, the decomposed IMF components are transformed by HHT, and the marginal spectrum characteristics of each signal are obtained.

Key words: EMD, EEMD, torsional vibration monitorin

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