Operational modal identification in the presence of harmonic excitation

Abstract The dynamic behavior of structures can be studied by the identification of their modal parameters. Classical modal analysis methods are based on the relation between the forces applied to structures (inputs) and their vibration responses (outputs). In real operational conditions it is difficult, or even impossible, to measure the excitation. For this reason, operational modal analysis approaches which consider only output data are proposed. However, most of these output-only techniques are proposed under the assumption of white noise excitation. If additional components, like harmonics for instance, are present in the exciting force, they will not be separated from the natural frequencies. Consequently, this assumption is no longer valid. In this context, an operational modal identification technique is proposed in order to only identify real poles and eliminate spurious ones. It is a method based on transmissibility functions. The objective of the proposed paper is to identify modal parameters in operational conditions in the presence of harmonic excitations. Identification is performed using a method based on transmissibility measurements and then with the classical stochastic subspace identification method, which is based on white noise excitation. These two methods are first applied to numerical examples and then to a laboratory test. Results validate the novel ability of the method based on transmissibility measurements to eliminate harmonics, contrary to the stochastic subspace identification approach.

[1]  Rune Brincker,et al.  Eliminating the Influence of Harmonic Components in Operational Modal Analysis , 2007 .

[2]  Palle Andersen,et al.  Using EFDD as a Robust Technique for Deterministic Excitation in Operational Modal Analysis , 2007 .

[3]  Bart Peeters,et al.  POLYMAX: A REVOLUTION IN OPERATIONAL MODAL ANALYSIS , 2005 .

[4]  Christof Devriendt,et al.  Identification of modal parameters from transmissibility measurements , 2008 .

[5]  Pascal Ray,et al.  Dynamic characterization of machining robot and stability analysis , 2016 .

[6]  J. Antoni Blind separation of vibration components: Principles and demonstrations , 2005 .

[7]  Norris Stubbs,et al.  A new method to extract modal parameters using output-only responses , 2005 .

[8]  Paul Sas,et al.  Modal Analysis Theory and Testing , 2005 .

[9]  Pascal Ray,et al.  Experimental protocol for the dynamic modeling of machining robots , 2013 .

[10]  Prasenjit Mohanty,et al.  Modified SSTD method to account for harmonic excitations during operational modal analysis , 2004 .

[11]  Christof Devriendt,et al.  Operational modal analysis in the presence of harmonic excitations by the use of transmissibility measurements , 2009 .

[12]  Palle Andersen,et al.  An Indicator for Separation of Structural and Harmonic Modes in Output-Only Modal Testing , 2000 .

[13]  L. Hermans,et al.  MODAL TESTING AND ANALYSIS OF STRUCTURES UNDER OPERATIONAL CONDITIONS: INDUSTRIAL APPLICATIONS , 1999 .

[14]  J. Antoni The spectral kurtosis: a useful tool for characterising non-stationary signals , 2006 .

[15]  Bart Peeters,et al.  COMPARATIVE STUDY OF MODAL ANALYSIS TECHNIQUES FOR BRIDGE DYNAMIC CHARACTERISTICS , 2003 .

[16]  Pascal Ray,et al.  Modal identification of spindle-tool unit in high-speed machining , 2011 .

[17]  Christof Devriendt,et al.  The use of transmissibility measurements in output-only modal analysis , 2007 .

[18]  Guido De Roeck,et al.  REFERENCE-BASED STOCHASTIC SUBSPACE IDENTIFICATION FOR OUTPUT-ONLY MODAL ANALYSIS , 1999 .

[19]  Bart De Moor,et al.  Subspace algorithms for the stochastic identification problem, , 1993, Autom..