Enhanced vibration separation technique for fault diagnosis of sun gear

IF 1.8 4区 工程技术 Q3 ENGINEERING, MECHANICAL Journal of The Brazilian Society of Mechanical Sciences and Engineering Pub Date : 2024-09-04 DOI:10.1007/s40430-024-05155-8
Changliang Liu, Shaokang Liu, Weiliang Liu, Shuai Liu, Yingjie Wu, Ziqi Wang, Zhihong Luo
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Abstract

The complex structure of a planetary gearbox weakens the gear fault characteristics in measurement signals. Vibration separation (VS) technology can address this problem by eliminating the impact of time-varying transfer paths on the signal. However, existing methods for determining the first window position (FWP) of VS are not highly accurate. To address this issue, a novel method for determining the FWP has been proposed in this paper, thereby creating an enhanced VS (EVS) technology. First, the envelope signal, which contains the amplitude-modulated signal (AMS) due to time-varying transfer paths, is separated using a zero-phase bandpass filter and Hilbert transform. Then, adaptive chirp mode decomposition is employed to accurately estimate a harmonic of the AMS. A sequence is formed by identifying the maximum points of the harmonic signal, indicating the moments when the planetary gear passes beneath the accelerometer. Finally, the VS method is applied based on the selected FWP. The results from both simulation and experimental signal analyses indicate that the FWP error of the EVS method (1.57%) is lower than the errors (1.83, 20.06, and 12.04%) found in the comparison methods. Additionally, the fault characteristic amplitude in the envelope order spectrum using EVS (9.78 m/s2) is higher than the amplitudes (6.14 m/s2, 6.18 m/s2, 8.56 m/s2, and 0.95 m/s2) recorded by the comparison methods. These findings confirm the effectiveness and superiority of EVS over other methods in terms of FWP accuracy and fault characteristic enhancement.

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用于太阳齿轮故障诊断的增强型振动分离技术
行星齿轮箱的复杂结构削弱了测量信号中的齿轮故障特征。振动分离(VS)技术可以消除时变传递路径对信号的影响,从而解决这一问题。然而,现有的 VS 第一窗口位置(FWP)确定方法精确度不高。为解决这一问题,本文提出了一种确定 FWP 的新方法,从而创建了增强型 VS(EVS)技术。首先,利用零相带通滤波器和希尔伯特变换分离包络信号,其中包含因时变传输路径而产生的调幅信号(AMS)。然后,采用自适应啁啾模式分解来准确估计 AMS 的谐波。通过识别谐波信号的最大点形成序列,表明行星齿轮经过加速度计下方的时刻。最后,根据选定的 FWP 应用 VS 方法。模拟和实验信号分析的结果表明,EVS 方法的 FWP 误差(1.57%)低于对比方法的误差(1.83%、20.06% 和 12.04%)。此外,使用 EVS 的包络阶谱中的故障特征振幅(9.78 m/s2)高于对比方法记录的振幅(6.14 m/s2、6.18 m/s2、8.56 m/s2 和 0.95 m/s2)。这些发现证实了 EVS 在 FWP 精确度和故障特征增强方面的有效性和优越性。
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来源期刊
CiteScore
3.60
自引率
13.60%
发文量
536
审稿时长
4.8 months
期刊介绍: The Journal of the Brazilian Society of Mechanical Sciences and Engineering publishes manuscripts on research, development and design related to science and technology in Mechanical Engineering. It is an interdisciplinary journal with interfaces to other branches of Engineering, as well as with Physics and Applied Mathematics. The Journal accepts manuscripts in four different formats: Full Length Articles, Review Articles, Book Reviews and Letters to the Editor. Interfaces with other branches of engineering, along with physics, applied mathematics and more Presents manuscripts on research, development and design related to science and technology in mechanical engineering.
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