Fast Mode Identification Technique for Online Monitoring

Document Type

Article

Subject Area(s)

Structural Engineering

Abstract

Today's structural monitoring systems include hundreds of data channels. The number of channels on these systems is expected to grow as sensors become more affordable, creating large computational requirements for the online modal identification of structural systems. This paper presents the mathematical formulation, numerical and experimental validation of a new fast mode identification (FMI) technique for online monitoring. The FMI technique uses experimental data from ambient vibration tests to identify operational mode shapes at a fraction of the time used by traditional modal identification techniques. The method focuses on identifying operational mode shapes at a particular frequency, allowing the modal identification method to be broken down in two steps: (i) identification of natural frequencies and modal damping ratios, and (ii) identification of mode shapes. Dividing the process in two reduces the computational time required by the algorithm. Numerical simulations show that the FMI is robust to the presence of noise in the signals. Experimental results show a good agreement between the results of FMI and those of other widely used modal identification methods. However, FMI shows a higher consistency on the identified modal coordinates and lower processing time than other methods. FMI is envisioned to be used in online monitoring systems with a large number of sensors. FMI can also be used on wireless sensor networks where available processing time and battery life might be limited.

Rights

Copyright © 2010 John Wiley & Sons, Ltd

"This is the peer reviewed version of the following article:

Caicedo, J.M., Marulanda, J. (2011). Fast Mode Identification Technique for Online Monitoring. Structural Control and Health Monitoring. 18(4), 416-429.

which has been published in final form at http://dx.doi.org/10.1002/stc.381. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."

Caicedo, J.M., Marulanda, J. (2011). Fast Mode Identification Technique for Online Monitoring. Structural Control and Health Monitoring. 18(4), 416-429. http://dx.doi.org/10.1002/stc.381


Link to Record

Share

COinS