Abstract：In fault diagnosis of rotating machinery, Hilbert-Huang transform (HHT) is often used to extract the fault characteristic signal and analyze decomposition results in time-frequency analysis. However, end effect occurs in HHT, which leads to a series of problems such as modal aliasing and false intrinsic mode function(IMF). To solve this problem, a novel method to optimize end effect in HHT through combination of generalized regression neural network (GRNN) and boundary local characteristic-scale continuation (BLCC) to extend signal is proposed, then followed by empirical mode decomposition (EMD). Simulation and measurement experiment for the conditions of time domain, frequency domain and related parameters of Hilbert-Huang spectrum verified the effectiveness of the proposed method through comparison with the results obtained by mirror continuation. The experimental results show that the method can effectively inhibit end effect, reduce modal aliasing and false IMF components, and accurately show the real structure of signal components.
［1］Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis ［J］. Proceedings of the Royal Society of London, Series A, 1998, 454（1971）:903-995.
［2］王传菲,安钢,王凯,等.基于镜像延拓和神经网络的EMD端点效应改进方法［J］.装甲兵工程学院学报,2010,24 (2):62-63.
［3］曹端超,康建设,赵劲松,等.EMD端点效应抑制方法仿真比较与实例分析研究［J］.机械传动,2013,37(3):83-84.
［4］李方溪,陈桂明,刘希亮,等.希尔伯特-黄变换端点效应的自适应端点相位正弦延拓方法［J］.上海交通大学学报,2013,47(4):594-596.
［5］Huang D J, Zhao J P, SU J L. Practical implementation of Hilbert-Huang transform algorithm ［J］. Acta Oceanologica Sinica,2003,22(1):1-14.
［6］Deng Y J, Wang W, QIAN C C. Boundary-processing-technique in EMD method and Hilbert transform［J］.Chinese Science Bulletin,2001,46(11):954-961.
［7］窦东阳,赵英凯.利用ARIMA改进HHT端点效应的方法［J］.振动、测试与诊断,2010,30(3):250-252.
［8］郭明威,倪世宏,朱家海,等.振动信号中HHT/EMD端点延拓方法研究［J］.振动与冲击,2012,31(8):62-63.
［9］Rilling G, Flandrin P, Goncalves P. On empirical mode decomposition and its algorithms［C］//IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, Grado, 2003.
［10］张义平,李夕兵,左宇军.爆破振动信号的HHT分析与应用［M］.北京:冶金工业出版社,2008.
［11］徐斌,徐德城,朱卫平,等.希尔伯特-黄变换方法的改进［J］.西北工业大学学报,2011,29(2):269-270.
［12］白春华,周宣赤,林大超,等. 消除EMD端点效应的PSO-SVM方法研究［J］.系统工程理论与实践,2013,33(5):1299-1300.
［13］Cheng J S, Yu D J, Yang Y. Application of support vector regression machines to the precessing of end effects of Hilbert-Huang transform ［J］.Mechanical Systems and Signal Processing,2007,21(3):1197-1211.
［14］Spech D F. A general regression neural network ［J］.IEEE Trans on Neural Networks,1991,2(6):568-576.
［15］黄诚惕.希尔伯特-黄变换及其应用研究［D］. 成都:西南交通大学,2006.
2016, Vol. 37 
