A novel identification procedure from ambient vibration data

Ambient vibration modal identification, also known as Operational Modal Analysis, aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on applying the Hilbert Transform, to obtain the analytical representation of the system response in terms of the correlation function. In particular, it is worth stressing that the analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. A 3DOF numerical example will be presented to show the accuracy of the proposed procedure, and comparisons with data from other methods assess the reliability of the approach. Finally, the identification method will be extended to the real case study of the Chiaramonte Palace, a historic building located in Palermo and known as “Steri”.

[1]  Edward Bedrosian,et al.  The Analytic Signal Representation of Modulated Waveforms , 1962, Proceedings of the IRE.

[2]  Niklas Grip,et al.  Recent trends in operation modal analysis techniques and its application on a steel truss bridge , 2019 .

[3]  Lingmi Zhang.  FROM TRADITIONAL EXPERIMENTAL MODAL ANALYSIS (EMA) TO OPERATIONAL MODAL ANALYSIS (OMA), AN OVERVIEW , 2013 .

[4]  C. Bilello,et al.  Time Delay Induced Effects on Control of Non-Linear Systems under Random Excitation , 2002 .

[5]  Egidio Rizzi,et al.  Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping , 2016 .

[6]  E. Bedrosian.  A Product Theorem for Hilbert Transforms , 1963 .

[7]  Nuno M. M. Maia,et al.  Theoretical and Experimental Modal Analysis , 1997 .

[8]  Joseph Lardies,et al.  Modal parameter identification based on ARMAV and state–space approaches , 2010 .

[9]  Yozo Fujino,et al.  System identification of suspension bridge from ambient vibration response , 2008 .

[10]  Siu-Kui Au.  Operational Modal Analysis , 2017 .

[11]  Carlo Rainieri,et al.  Operational modal analysis for the characterization of heritage structures , 2011 .

[12]  A I Lima.  Lo Steri di Palermo nel secondo Novecento / Dagli studi di Giuseppe Spatrisano al progetto di Roberto Calandra con la consulenza di Carlo Scarpa , 2006 .

[13]  M. Feldman.  Hilbert transform in vibration analysis , 2011 .

[14]  Antonina Pirrotta,et al.  A damage identification procedure based on Hilbert transform: Experimental validation , 2012 .

[15]  Rune Brincker,et al.  Modal identification of output-only systems using frequency domain decomposition , 2001 .

[16]  Julius S. Bendat,et al.  Engineering Applications of Correlation and Spectral Analysis , 1980 .

[17]  Antonina Pirrotta,et al.  A Numerical Model for Pre-Monitoring Design of Historical Colonnade Courtyards: The Case Study of Chiaramonte Palace in Palermo , 2016 .

[18]  Van Valkenburg,et al.  Analog Filter Design , 1982 .

[19]  Salvatore Salamone,et al.  Incipient damage identification through characteristics of the analytical signal response , 2008 .

[20]  Shahrum Abdullah,et al.  The Study of EMA Effect on Modal Identification: A Review , 2017 .

[21]  Antonina Pirrotta,et al.  Low stiffness variation in structural systems: Identification and localization , 2008 .

[22]  Antonina Pirrotta,et al.  α-stable distributions for better performance of ACO in detecting damage on not well spaced frequency systems , 2014 .

[23]  J. Bendat,et al.  Random Data: Analysis and Measurement Procedures , 1971 .

[24]  Rik Pintelon,et al.  Welch Method Revisited: Nonparametric Power Spectrum Estimation Via Circular Overlap , 2010, IEEE Transactions on Signal Processing.

[25]  Michal Petrů,et al.  Health Monitoring of Civil Infrastructures by Subspace System Identification Method: An Overview , 2020, Applied Sciences.

[26]  Juan M. Caicedo,et al.  Practical guidelines for the natural excitation technique (NExT) and the eigensystem realization algorithm (ERA) for modal identification using ambient vibration , 2011 .

[27]  Rune Brincker,et al.  Output-only Modal Analysis by Frequency Domain Decomposition , 2000 .

[28]  P. Welch.  The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .