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基于SK‑MOMEDA的风电机组轴承复合故障特征分
Separation and Extraction of Composite Fault Characteristics of Wind Turbine Bearing Based on SK⁃MOMEDA
  
DOI:10.16450/j.cnki.issn.1004?6801.2021.04.002
中文关键词:  风电机组  轴承  复合故障  分离提取  谱峭度  多点最优调整的最小熵解卷积
英文关键词:wind turbine  bearing  composite fault  separation and extraction  spectral kurtosis  minimum entropy deconvolution of multi-point optimal adjustment
基金项目:国家自然科学基金资助项目(52075170)
作者单位
向玲, 李京蓄, 胡爱军, 李营 (华北电力大学(保定)机械工程系 保定071003) 
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中文摘要:
      针对在实际工况中风电机组滚动轴承发生复合故障时,多个故障间相互作用,彼此干扰,造成复合故障特征难以分离问题,提出了基于谱峭度(spectral kurtosis,简称SK)与多点最优调整的最小熵解卷积(multipoint optimal minimum entropy deconvolution adjusted,简称MOMEDA)的风电机组滚动轴承复合故障特征分离提取方法。首先,对复合故障信号进行谱峭度分析,选出能量较大的共振频带,并通过构建带通滤波器对相应的共振频带进行滤波,对滤波信号进行包络谱分析,对单一故障特征进行分离提取;其次,对未能实现单一故障特征提取的滤波信号进行多点峭度谱分析并确定故障周期,应用MOMEDA完成后续分离提取过程。仿真信号和工程应用分析结果表明,该方法能够准确且有效地实现轴承复合故障特征的分离提取。
英文摘要:
      For the composite fault of wind turbine rolling bearing in actual working conditions, due to the interaction between multiple faults which interfere with each other, making the composite fault feature difficult to separate. A method for separating and extracting composite fault characteristics of wind turbine rolling bearings is proposed based on spectral kurtosis (SK) and multipoint optimal minimum entropy deconvolution adjusted (MOMEDA). Firstly, the spectral kurtosis analysis is performed on the composite fault signal, and the resonant frequency band with larger energy is selected. The band-pass filter is constructed to filter the corresponding resonant frequency band, and the envelope signal is analyzed by the envelope spectrum to separate the single fault feature. Then, the multipoint kurtosis spectrum analysis is performed on the filtered signal that fails to realize single fault feature extraction, and the fault period is determined. The subsequent separation and extraction process is completed by using MOMEDA. The simulation signal and engineering application analysis results show that the method can effectively and accurately realize the separation and extraction of bearing composite fault features.
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