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Research on a Method of Fault Signal Extraction Based on Improved Algorithm

机译:基于改进算法的故障信号提取方法研究

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Considering the difficulty of diagnosis signal de-noising and feature extraction problems, according to the characteristics of periodicity and shock attenuation respond of mechanical fault vibration signals, a method of improved sequential decomposition algorithm is proposed, it transforms an initial time series into a group of two-dimensional time series, prominent time series partial information, time series decomposition is reversible, can be used for filtering and feature extraction of time signal. Through the simulation and experiments, the validity of method for highlighting partial feature information of the signal is verified, helping to extract weak fault information in strong background noise environment.
机译:考虑到诊断信号去噪和特征提取问题的难度,根据机械故障振动信号的周期性和冲击衰减的特性,提出了一种改进的顺序分解算法的方法,它将初始时间序列转换为一组二维时间序列,突出的时间序列部分信息,时间序列分解是可逆的,可用于过滤和特征提取时间信号。通过模拟和实验,验证了突出显示信号部分特征信息的方法的有效性,有助于提取强大的背景噪声环境中的弱故障信息。

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