A local and online sifting process for the empirical mode decomposition and its application in aircraft damage detection

Abstract This paper introduces the Variable-Span Smoothing Sifting (VSSS) for the Empirical Mode Decomposition (EMD), as a substitute for the traditional sifting process. In this method, the local mean of the signal at each point is extracted by applying some smoothing filters to its adjacent data points, within a variable span sliding window. The VSSS is direct, local and online; hence, it may improve the EMD performance, and overcome many drawbacks of the classical algorithm. The performance of the VSSS is verified through some numerical studies, in which, results of the new and traditional sifting processes are compared for some benchmark signals. Finally, the VSSS is applied to the aircraft damage detection problem.

[1]  Y. Zi,et al.  Cosine window-based boundary processing method for EMD and its application in rubbing fault diagnosis , 2007 .

[2]  Sylvain Meignen,et al.  A New Formulation for Empirical Mode Decomposition Based on Constrained Optimization , 2007, IEEE Signal Processing Letters.

[3]  W. Chiang,et al.  Detecting the sensitivity of structural damage based on the Hilbert‐Huang transform approach , 2010 .

[4]  Yuesheng Xu,et al.  A B-spline approach for empirical mode decompositions , 2006, Adv. Comput. Math..

[5]  Gabriel Rilling,et al.  Empirical mode decomposition as a filter bank , 2004, IEEE Signal Processing Letters.

[6]  Christofer Toumazou,et al.  Empirical Mode Decomposition: Real-Time Implementation and Applications , 2013, J. Signal Process. Syst..

[7]  Irene M. Gregory,et al.  General Equations of Motion for a Damaged Asymmetric Aircraft , 2007 .

[8]  Manuel Duarte Ortigueira,et al.  On the HHT, its problems, and some solutions , 2008 .

[9]  J. A. Mulder,et al.  Real Time Damaged Aircraft Model Identification for Reconfiguring Flight Control , 2007 .

[10]  Shuren Qin,et al.  A new envelope algorithm of Hilbert-Huang Transform , 2006 .

[11]  John Kaneshige,et al.  Dynamics and Adaptive Control for Stability Recovery of Damaged Asymmetric Aircraft , 2006 .

[12]  Cheng Junsheng,et al.  Research on the intrinsic mode function (IMF) criterion in EMD method , 2006 .

[13]  Jacques Lemoine,et al.  Empirical mode decomposition: an analytical approach for sifting process , 2005, IEEE Signal Processing Letters.

[14]  Yi Shen,et al.  Boundary extension for Hilbert-Huang transform inspired by gray prediction model , 2012, Signal Process..

[15]  Yaguo Lei,et al.  A review on empirical mode decomposition in fault diagnosis of rotating machinery , 2013 .

[16]  Steve McLaughlin,et al.  Investigation and Performance Enhancement of the Empirical Mode Decomposition Method Based on a Heuristic Search Optimization Approach , 2008, IEEE Transactions on Signal Processing.

[17]  Jeffrey S. Hill,et al.  Airborne Subscale Transport Aircraft Research Testbed: Aircraft Model Development , 2005 .

[18]  Nhan T. Nguyen,et al.  Flight Dynamics and Hybrid Adaptive Control of Damaged Aircraft , 2008 .

[19]  Yu Liu,et al.  Modeling and Model Reference Adaptive Control of Aircraft with Asymmetric Damage , 2009 .

[20]  G.G.S Pegram,et al.  Empirical mode decomposition using rational splines: an application to rainfall time series , 2008, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[21]  Zhihua Yang,et al.  A New Definition of the Intrinsic Mode Function , 2009 .

[22]  Liang-Gee Chen,et al.  Cubic spline interpolation with overlapped window and data reuse for on-line Hilbert Huang transform biomedical microprocessor , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[24]  S. S. Shen,et al.  A confidence limit for the empirical mode decomposition and Hilbert spectral analysis , 2003, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[25]  Jeffrey Ouellette Flight Dynamics and Maneuver Loads on a Commercial Aircraft with Discrete Source Damage , 2010 .

[26]  Robert X. Gao,et al.  Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring , 2006, IEEE Transactions on Instrumentation and Measurement.

[27]  Gautam H. Shah Aerodynamic Effects and Modeling of Damage to Transport Aircraft , 2008 .

[28]  Hongkai Jiang,et al.  An improved EEMD with multiwavelet packet for rotating machinery multi-fault diagnosis , 2013 .