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Modal Identification of Output-Only Systems using Frequency Domain Decomposition

TL;DR: In this paper, a decomposition of the spectral density function matrix is introduced for the modal identification of output-only systems, i.e. in the case where the modality parameters must be estimated without knowing the input of the system.
Abstract: In this paper a new frequency domain technique is introduced for the modal identification of output-only systems, i.e. in the case where the modal parameters must be estimated without knowing the input exciting the system. By its user friendliness the technique is closely related to the classical approach where the modal parameters are estimated by simple peak picking. However, by introducing a decomposition of the spectral density function matrix, the response spectra can be separated into a set of single degree of freedom systems, each corresponding to an individual mode. By using this decomposition technique close modes can be identified with high accuracy even in the case of strong noise contamination of the signals. Also, the technique clearly indicates harmonic components in the response signals.

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Citations
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Journal ArticleDOI
TL;DR: The biggest challenge in realization of health monitoring of large real-life structures is automated detection of damage out of the huge amount of very noisy data collected from dozens of sensors on a daily, weekly, and monthly basis.
Abstract: Signal processing is the key component of any vibration-based structural health monitoring (SHM). The goal of signal processing is to extract subtle changes in the vibration signals in order to detect, locate and quantify the damage and its severity in the structure. This paper presents a state-of-the-art review of recent articles on signal processing techniques for vibration-based SHM. The focus is on civil structures including buildings and bridges. The paper also presents new signal processing techniques proposed in the past few years as potential candidates for future SHM research. The biggest challenge in realization of health monitoring of large real-life structures is automated detection of damage out of the huge amount of very noisy data collected from dozens of sensors on a daily, weekly, and monthly basis. The new methodologies for on-line SHM should handle noisy data effectively, and be accurate, scalable, portable, and efficient computationally.

349 citations

Journal ArticleDOI
TL;DR: In this paper, a network of low-cost wireless sensors was installed in the Geumdang Bridge, Korea to monitor the bridge response to truck loading, and a signal conditioning circuit that amplifies and filters low-level accelerometer outputs is proposed.
Abstract: As researchers continue to explore wireless sensors for use in structural monitoring systems, validation of field performance must be done using actual civil structures. In this study, a network of low-cost wireless sensors was installed in the Geumdang Bridge, Korea to monitor the bridge response to truck loading. Such installations allow researchers to quantify the accuracy and robustness of wireless monitoring systems within the complex environment encountered in the field. In total, 14 wireless sensors were installed in the concrete box girder span of the Geumdang Bridge to record acceleration responses to forced vibrations introduced by a calibrated truck. In order to enhance the resolution of the capacitive accelerometers interfaced to the wireless sensors, a signal conditioning circuit that amplifies and filters low-level accelerometer outputs is proposed. The performance of the complete wireless monitoring system is compared to a commercial tethered monitoring system that was installed in parallel. The performance of the wireless monitoring system is shown to be comparable to that of the tethered counterpart. Computational resources (e.g. microcontrollers) coupled with each wireless sensor allow the sensor to estimate modal parameters of the bridge such as modal frequencies and operational displacement shapes. This form of distributed processing of measurement data by a network of wireless sensors represents a new data management paradigm associated with wireless structural monitoring. (Some figures in this article are in colour only in the electronic version)

269 citations

Journal ArticleDOI
TL;DR: In this article, two output-only time-domain system identification methods are employed to obtain dynamic characteristics of a suspension bridge, namely, the Random Decrement Method combined with the Ibrahim Time Domain (ITD) method and the Natural Excitation Technique (NExT) combined with Eigensystem Realization Algorithm (ERA).

259 citations

01 Nov 2007
TL;DR: This research highlights the need to understand more fully the role of phosphorous in the response of the immune system to disease and its role in promoting wound healing.
Abstract: Financial support for this research was provided in part by the National Science Foundation (NSF) under NSF grants CMS 03-01140 and CMS 06-00433 (Dr. S. C. Liu, Program Manager). The first author was supported by a Vodafone-U.S. Foundation Graduate Fellowship. This support is gratefully acknowledged.

256 citations

Journal ArticleDOI
TL;DR: In this paper, the performance of a building under wind and seismic loads depends on stiffness and mass distribution, and may be estimated using finite element codes, however, experience has shown that such finite element models often fail to predict accurately the fundamental natural frequencies.
Abstract: The performance of a building under wind and seismic loads depends on stiffness and mass distribution, and may be estimated using finite element codes. Experience has, however, shown that such finite element models often fail to predict accurately the fundamental natural frequencies. Usually the frequencies will be underestimated, that is the building will turn out to be stiffer than anticipated, meaning the design would usually be conservative. On the other hand, effects like torsional eccentricity and foundation compliance may not be correctly modelled, which could be less desirable. A full understanding of linear performance under lateral loads can be obtained through experimental evaluation of the vibration modes. Traditionally only a limited range of modal analysis procedures and software has been applied to civil applications and the ‘special case’ where no input forces can be measured has been the usual situation for large civil structures. Recent developments in system identification, which is the set of procedures to build mathematical models of the dynamic structural systems based on measured data, have added significantly to the potential of ambient vibration or ‘output only’ testing. The aim of the research reported here has been to apply and evaluate the procedures on typical buildings. The procedures are briefly explained and two experimental programmes are then described; a long-term tremor monitoring exercise on a 280m office tower and an ambient vibration survey of a smaller office block. The different forms of response data are examined to study the performance of the analysis procedures and expose benefits and limitations in their use. There is a growing interest in output-only modal analysis procedures in civil engineering. The experience reported in this paper has shown that quick and reliable estimation of mode shapes and frequencies can be obtained, even with small amounts of data. Judgement of modal participation and damping ratios requires more detailed study yet the results are at least as convincing as existing and relatively limited frequency domain methods. Copyright © 2002 John Wiley & Sons, Ltd.

224 citations

References
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Book
01 Jan 1971
TL;DR: A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems, is presented in this article.
Abstract: From the Publisher: A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems. With more than 100,000 copies in print and six foreign translations, the first edition standardized the methodology in this field. This new edition covers all new procedures developed since 1971 and extends the application of random data analysis to aerospace and automotive research; digital data analysis; dynamic test programs; fluid turbulence analysis; industrial noise control; oceanographic data analysis; system identification problems; and many other fields. Includes new formulas for statistical error analysis of desired estimates, new examples and problem sets.

6,693 citations

Book
13 May 1980
TL;DR: This chapter discusses single-Input/Single-Output Relationships, nonstationary data analysis techniques, and procedures to Solve Multiple- Input/Multiple-Output Problems.
Abstract: Discusses engineering applications and recent developments based upon correlation and spectral analysis. Illustrations deal with applications to acoustics, mechanical vibrations, system identification, and fluid dynamics problems in aerospace, automotive, industrial noise control, civil engineering and oceanographic fields, as well as similar problems in other fields. Tackles problems and solutions, assuming reader has required hardware and software to compute estimates of correlation, spectra, coherence, and phase functions.

2,447 citations