Element‐Level System Identification with Unknown Input

Duan, Wang; Haldar, Achintya

doi:10.1061/(asce)0733-9399(1994)120:1(159)

Cited by 107 publications

(45 citation statements)

References 16 publications

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“…It will be very desirable if a system can be identified using only measured response information completely ignoring the excitation information. The team developed several such techniques, commonly known as Iterative Least Squares with Unknown Input (ILS-UI) [24], Modified ILS-UI or MILS-UI [19], and Generalized ILS-UI or GILS-UI [18]. Mathematical concepts used to develop them cannot be discussed here due to lack of space but widely available in the literature.…”

Section: System Identification With Unknown Inputmentioning

confidence: 99%

Prognostics and Structural Health Assessment Using Uncertain Measured Response Information

Haldar

Al-Hussein

2015

Lecture Notes in Mechanical Engineering

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The authors and their team members have been working on developing implementable techniques for the objective rapid assessment of structural health (RASH) just after major natural and man-made events or in the context of maintenance over a period of time. They used the system-identification techniques by eliminating some of its weaknesses. For easier implementation, the excitation information was completely ignored. To locate defects and their severity at the local element level, the structures were represented by finite elements. By tracking the changes in the stiffness parameters of each element, the location(s) and severity of defects are assessed. The team conducted extensive analytical and laboratory investigations to verify all the methods. They had to overcome several challenges related to the conceptual and analytical development, data processing, and the presence of uncertainty in the every phase. To consider nonlinearity in the system identification process, a method known as Generalized Iterative Least Squares-Extended Kalman Filter-Unknown Input (GLIS-EKF-UI), was developed earlier. Since it failed to identify structures in some cases, the authors recently proposed a new method denoted as Unscented Kalman Filter-Unknown InputWeighted Global Iterations (UKF-UI-WGI). With the help of informative examples, the superiority of UKF-UI-WGI over GLIS-EKF-UI is documented in this paper. Since at the beginning of an inspection, the defects and their severity are expected to be unknown, the authors recommend UKF-UI-WGI for the rapid assessment of health of infrastructures.

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Section: System Identification With Unknown Inputmentioning

confidence: 99%

Prognostics and Structural Health Assessment Using Uncertain Measured Response Information

Haldar

Al-Hussein

2015

Lecture Notes in Mechanical Engineering

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“…Many researchers have proposed parameter extraction for planar frame structures [5][6][7] or have separately identified two translational modal parameters and one torsional modal parameter of building structures [8]. However, even buildings with nominally symmetric plans are actually asymmetric to some degree and undergo lateral as well as torsional vibrations simultaneously when subjected to purely translational excitations.…”

Section: Introductionmentioning

confidence: 99%

Parameter identification of torsionally coupled shear buildings from earthquake response records

Hegde

Sinha

2008

Earthq Engng Struct Dyn

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SUMMARYThis paper presents an efficient procedure to determine the natural frequencies, modal damping ratios and mode shapes for torsionally coupled shear buildings using earthquake response records. It is shown that the responses recorded at the top and first floor levels are sufficient to identify the dominant modal properties of a multistoried torsionally coupled shear building with uniform mass and constant eccentricity even when the input excitation is not known. The procedure applies eigenrealization algorithm to generate the state-space model of the structure using the cross-correlations among the measured responses. The dynamic characteristics of the structure are determined from the state-space realization matrices. Since the mode shapes are obtained only at the instrumented floor (top and first floors) levels, a new mode shape interpolation technique has been proposed to estimate the mode shape coefficients at the remaining floor levels. The application of the procedure has been demonstrated through a numerical experiment on an eight-storied torsionally coupled shear building subjected to earthquake base excitation. The results show that the proposed parameter identification technique is capable of identifying dominant modal parameters and responses even with significant noise contamination of the response records.

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“…In the left side, vector P sub is unknown and, in the right side, vector F ⋅kn includes unknown inertia force. Therefore, to initiate the iteration process for solving the unknown parameters in P sub vector, the unknown excitation forces are assumed to be zero at all time points, as suggested by Wang and Haldar [7] and Katkhuda et al [9]. The iteration process continues until a predetermined convergence tolerance level ( ) on the input excitation at all time points is obtained.…”

Section: Stage 1: Formulation Of 3d Ils-uimentioning

confidence: 99%

“…Initially, the team proposed a concept known as Iterative LeastSquares with Unknown Input (ILS-UI) [7][8][9] to identify a system using only noise-contaminated response information measured at all dynamic degrees of freedoms (DDOFs). At this stage, the team observed that it may be uneconomical and impractical to instrument large infrastructures and measure responses at all DDOFs.…”

Section: Complexitymentioning

confidence: 99%

Complexities in Assessing Structural Health of Civil Infrastructures

Al-Hussein

Haldar

2017

Complexity

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The complexity in the health assessment of civil infrastructures, as it evolves over a long period of time, is briefly discussed. A simple problem can become very complex based on the current needs, sophistication required, and the technological advancements. To meet the current needs of locating defect spots and their severity accurately and efficiently, infrastructures are represented by finite elements. To increase the implementation potential, the stiffness parameters of all the elements are identified and tracked using only few noise-contaminated dynamic responses measured at small part of the infrastructure. To extract the required information, Kalman filter concept is integrated with other numerical schemes. An unscented Kalman filter (UKF) concept is developed for highly nonlinear dynamic systems. It is denoted as 3D UKF-UI-WGI. The basic UKF concept is improved in several ways. Instead of using one long duration time-history in one global iteration, very short duration time-histories and multiple global iterations with weight factors are used to locate the defect spot more accurately and efficiently. The capabilities of the procedure are demonstrated with the help of two informative examples. The proposed procedure is much superior to the extended Kalman filter-based procedures developed by the team earlier.

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Element‐Level System Identification with Unknown Input

Cited by 107 publications

References 16 publications

Prognostics and Structural Health Assessment Using Uncertain Measured Response Information

Prognostics and Structural Health Assessment Using Uncertain Measured Response Information

Parameter identification of torsionally coupled shear buildings from earthquake response records

Complexities in Assessing Structural Health of Civil Infrastructures

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