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基于EMD和HHT的轧机扭振瞬态冲击信号时频分析研究
引用本文:戴桂平.基于EMD和HHT的轧机扭振瞬态冲击信号时频分析研究[J].苏州市职业大学学报,2009,20(1):37-40.
作者姓名:戴桂平
作者单位:苏州市职业大学,电子信息工程系,江苏,苏州,215104
摘    要:为解决轧机扭振非平稳瞬态冲击信号的瞬态时频分析难题,提出了基于EMD和川bert—Huang变换的瞬态振动信号时频分析方法.利用EMD分解提取信号的固有模态函数OMF),再结合Hilbert变换,求解瞬时频率,进而得到信号的Hilbert—Huang时频谱及边际谱,从而提取扭振信号瞬态特征.通过仿真实验验证了该方法的可靠性,通过轧机在咬钢抛钢时实测瞬态信号的分析,表明了该方法的可行性.

关 键 词:瞬态冲击  特征提取  瞬时频率  EMD分解  Hilbert—Huang时频谱

Research on Time-frequency Analysis for Rolling Mill's Transient Torsional Vibration Signal Based on EMD and HHT
DAI Gui-ping.Research on Time-frequency Analysis for Rolling Mill's Transient Torsional Vibration Signal Based on EMD and HHT[J].Journal of Suzhou Vocational University,2009,20(1):37-40.
Authors:DAI Gui-ping
Institution:DAI Gui-ping (Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou 215104, China)
Abstract:To solve the problem of extracting the transient characteristics of torsional vibration nonstationary transient impact signal of the rolling mill, a novel method was presented using signal processing theory. First, the intrinsic mode function(IMF) of the signal was extracted via the empirical mode decomposition(EMD). Then combined with Hilbert transformation, the extracted model of the instantaneous frequency of single-frequency vibration transient signal was established to solve the instantaneous frequency. Afterwards, the Hilbert spectrum and the Hilbert boundary spectrum were obtained. By this means, the transient characteristics of the torsional vibration signal can be effectively extracted. Compared with wavelet decomposition, this algorithm avoids frequency overlapping in the wavelet decomposition and has the advantage of time scale self-adaption. It overcomes the difficulty of selecting elementary wavelet. The numerical simulation shows the feasibility of the method. When roiling mills grip or throw the steel, the example analysis of transient signal show the reliability of the method.
Keywords:transient impact  feature extraction  instantaneous frequency  empirical mode decomposition  hilbert-Huang time-frequency spectrum
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