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Feature Extraction Using Discrete Wavelet Transform for Gear Fault Diagnosis of Wind Turbine Gearbox

机译：基于离散小波变换的特征提取在风机齿轮箱齿轮故障诊断中的应用

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摘要

Vibration diagnosis is one of the most common techniques in condition evaluation of wind turbine equipped with gearbox. On the other side, gearbox is one of the key components of wind turbine drivetrain. Due to the stochastic operation of wind turbines, the gearbox shaft rotating speed changes with high percentage, which limits the application of traditional vibration signal processing techniques, such as fast Fourier transform. This paper investigates a new approach for wind turbine high speed shaft gear fault diagnosis using discrete wavelet transform and time synchronous averaging. First, the vibration signals are decomposed into a series of subbands signals with the use of a multiresolution analytical property of the discrete wavelet transform. Then, 22 condition indicators are extracted from the TSA signal, residual signal, and difference signal. Through the case study analysis, a new approach reveals the most relevant condition indicators based on vibrations that can be used for high speed shaft gear spalling fault diagnosis and their tracking abilities for fault degradation progression. It is also shown that the proposed approach enhances the gearbox fault diagnosis ability in wind turbines. The approach presented in this paper was programmed in Matlab environment using data acquired on a 2 MW wind turbine.
机译：振动诊断是装备变速箱的风力发电机组状态评估中最常用的技术之一。另一方面，变速箱是风力涡轮机传动系统的关键组件之一。由于风力涡轮机的随机运行，变速箱轴的转速以很高的百分比变化，这限制了传统振动信号处理技术（例如快速傅立叶变换）的应用。本文研究了一种基于离散小波变换和时间同步平均的风力机高速轴齿轮故障诊断新方法。首先，利用离散小波变换的多分辨率分析特性，将振动信号分解为一系列子带信号。然后，从TSA信号，残差信号和差信号中提取22个状态指示器。通过案例分析，一种新方法可以基于振动揭示最相关的状态指标，这些指标可用于高速轴齿轮剥落故障诊断及其对故障退化进程的跟踪能力。还表明，所提出的方法增强了风力涡轮机中的齿轮箱故障诊断能力。本文介绍的方法是在Matlab环境中使用在2兆瓦风力涡轮机上采集的数据进行编程的。

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  • 来源
    《Shock and vibration》 |2016年第1期|6748469.1-6748469.10|共10页
  • 作者

    Bajric Rusmir; Zuber Ninoslav; Skrimpas Georgios Alexandros; Mijatovic Nenad;

  • 作者单位

    EPC Elektroprivreda BiH, Kreka Coal Mines, Tuzla 75000, Bosnia & Herceg;

    Univ Novi Sad, Fac Tech Sci, Novi Sad 21000, Serbia;

    Bruel & Kjaer Vibro, DK-2850 Naerum, Denmark;

    Tech Univ Denmark, DK-2800 Lyngby, Denmark;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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