• Journal of KSNVE
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• v.9 no.2
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• pp.377-386
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• 1999

This paper is a study on model method for estimating system inputs from vibration responses, which is one of indirect input identification methods in frequency domain. The method has advantages over direct inverse method especially when points of operational inputs are inaccessible so that artificial excitation forces cannot be applied to obtain frequency response functions of the complete system. Procedures of extended modal model method are proposed and checked by numerical experiment. Mechanisms of error propagation, i.e., how errors in modal parameters such as poles nad mode shape vectors affect estimation of the input forces, are illustrated. Then, in order to counteract the error propagation, discrete modal filter approach is taken in this paper to compute the inversion of modal matrix in which the most serious errors seem to be generated. Further, a Reduced form of Modified Reciprocal Modal Vector(RMRMV) is proposed for estimating multiple inputs. It is shown to have smaller orthogonality error than MRMV.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.593-615
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• 2011

This study determines the water length effects on the modal behavior of a prototype arch dam using Operational and Analytical Modal Analyses. Achievement of this purpose involves construction of a prototype arch dam-reservoir-foundation model under laboratory conditions. In the model, reservoir length was taken to be as much as three times the dam height. To determine the experimental dynamic characteristics of the arch dam using Operational Modal Analysis, ambient vibration tests were implemented for empty reservoir and three different reservoir water lengths. In the ambient vibration tests, the dam was vibrated by natural excitations provided from small impact effects and the response signals were measured using sensitive accelerometers. Operational Modal Analysis software process signals collected from the ambient vibration tests, and Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification techniques estimated modal parameters of the dams. To validate the experimental results, 3D finite element model of the prototype arch dam was modeled by ANSYS software for empty reservoir and three different reservoir water lengths, and dynamic characteristics of each model were determined analytically. At the end of the study, experimentally and analytically identified dynamic characteristics compared to each other. Also, changes on the natural frequencies along to water length are plotted as graphs. Results suggest that reservoir water complicates the modal behavior of the arch dam significantly.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1162-1165
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• 2001

Operational Modal Analysis also known as Output Only Modal Analysis has in the recent years been used for extracting modal parameters of civil engineering structures and is now becoming popular for mechanical structures. The advantage of the method is that no artificial excitation need to be applied to the structure or force signals to be measured. All the parameter estimation is based upon the response signals, thereby minimising the work of preparation for the test. This test case is a controlled lab set-up enabling different parameter estimation methods techniques to be used and compared to the Operational Modal Analysis. For Operational Modal Analysis two different estimation techniques are used： a non-parametric technique based on Frequency Domain Decomposition (FDD), and a parametric technique working on the raw data in time domain, a data driven Stochastic Subspace Identification (SS!) algorithm. These are compared to other methods such as traditional Modal Analysis.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.278-285
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• 2009

Operational modal analysis (OMA) allows modal parameters, such as natural frequencies and damping, to be estimated solely from data collected during operation. However, a main shortcoming of these methods resides in the evaluation of the accuracy of the results. This paper will explore the uncertainty and possible variations in the estimates of modal parameters for different operating conditions. Two algorithms based on the Least Square Complex Exponential (LSCE) method will be used to estimate the modal parameters. The uncertainties will be calculated using a Monte-Carlo approach with the hypothesis of constant modal parameters at a given operating condition. In collaboration with Andritz-Hydro Ltd, data collected on two different stay vanes from an Andritz-Hydro Ltd Francis turbine will be used. This paper will present an overview of the procedure and the results obtained.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.121-128
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• 2020

This paper presents an experimental study on the dynamic characteristics of infilled reinforced concrete (RC) frames. A 1/3-scaled, one-bay, three-storey RC frame was produced and tested by using operational modal analysis (OMA). The experiments were performed on five specimens: one reference frame with no infill walls and four frames with infill walls. The RC frame systems included infill walls made of hollow clay brick, which were constructed in four different patterns. The dynamic characteristics of the patterns, including the frequency, mode shapes and damping ratios in the in-plane direction, were obtained by 6 accelerometers. Twenty-minute records under ambient vibration were collected for each model, and the dynamic characteristics were determined using the ambient vibration testing and modal identification software (ARTeMIS). The experimental studies showed that the infill walls significantly affected the frequency value, rigidity and damping ratio of the RC frame system.

• Smart Structures and Systems
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• v.26 no.4
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• pp.419-433
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• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• Smart Structures and Systems
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• v.17 no.2
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.1-18
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• 2015

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

• Computers and Concrete
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• v.12 no.1
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• pp.79-90
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• 2013

In this study, dynamic characteristics such as natural frequencies, mode shapes and damping ratios of RC frame is determined for different construction stages using Operational Modal Analyses method under ambient vibration. Full scaled, one bay and one story RC frames are selected as an application for different construction stages such as plane, brick in-filled and brick in-filled with plaster. The RC frame is vibrated by natural excitations with small impact effects and the response signals are measured using sensitive accelerometers during ambient vibration tests. Measurement time-frequency span and effective mode number are determined by considering similar studies in literature. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, output-only system identification technique is employed namely; Enhanced Frequency Domain Decomposition technique in the frequency domain. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of RC frames.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.579-593
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• 2010

Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.