基于AE与STFT的变桨轴承裂纹诊断研究
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TH133.3;O313.7

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国家重点研发计划项目《大容量风电机组电网友好型控制技术》课题5《不同电网运行条件下风电机组的载荷分析及稳定优化控制研究》(2018YFB0904005)


Research on Crack Diagnosis of Pitch Bearing Based on AE and STFT
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    摘要:

    由于变桨轴承不完全转动的工作特殊性,基于振动或应变等常规监测手段难以奏效,为此提出一种基于声发射(acoustic emission,简称AE)技术监测方法获取信号,并采用短时傅里叶方法(short time Fourier transform,简称STFT)进行分析诊断的方法。首先,研究了AE技术的信号采集方法,推导了STFT的原理及过程,并在某风电机组变桨轴承上进行实验验证;其次,先后在时域、频域及时频域对有裂纹数据和无裂纹数据进行对比,发现时频域基于STFT分析方法可以有效发现裂纹;最后,通过新的裂纹数据进行验证,可以确认裂纹特征。结果表明:AE信号能较好地获取变桨轴承的状态信息,STFT分析方法可以较好地识别裂纹故障,较少受工况或其他因素的影响,有较高的实用价值。

    Abstract:

    It is difficult to monitor pitch bearings with methods based on vibration signal or strain. In light of this limit, a method based on the acoustic emission (AE) technology is proposed to obtain signals, and the short time Fourier transform (STFT) method is introduced to analyze and diagnose the signals. First, the AE technology is studied, and the principle and process of STFT are deduced. Then, the experiments are carried out on a wind turbine pitch bearing. The data of pitch bearing with and without cracks are compared in time domain, frequency domain and time-frequency domain. It shows that the STFT analysis method works best in detecting the cracks in time-frequency domain. Finally, the characteristics of cracks are determined by new data. The results show that AE signals perform better in grasping the state information of pitch bearing, and STFT analysis method is prior in identifying crack faults. The STFT method maintains its performance when the working conditions or other factors change, which is more practical.

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  • 在线发布日期: 2021-07-05
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