Estimation of modal loads using structural response

Hwang, Jae‐Seung; Kareem, Ahsan; Kim, Wha-jung

doi:10.1016/j.jsv.2009.05.003

Cited by 70 publications

(41 citation statements)

References 17 publications

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“…A recursive deterministic method was presented by Klinkov and Fritzen [12], estimating both the input and system states from a set of output measurements. Currently, the attention is shifted to the development of recursive combined deterministic-stochastic approaches [13,14]. These methods do not only account for measurement errors, but also for modelling errors and additional unknown vibration sources.…”

Section: Introductionmentioning

confidence: 99%

Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics

Maes

Lourens

Nimmen

et al. 2015

Mechanical Systems and Signal Processing

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In structural dynamics, the forces acting on a structure are often not well known. System inversion techniques may be used to estimate these forces from the measured response of the structure. This paper first derives conditions for the invertibility of linear system models that apply to any instantaneous input estimation or joint input-state estimation algorithm. The conditions ensure the identifiability of the dynamic forces and system states, their stability and uniqueness. The present paper considers the specific case of modally reduced order models, which are generally obtained from a physical, finite element model, or from experimental data. It is shown how in this case the conditions can be directly expressed in terms of the modal properties of the structure. A distinction is made between input estimation and joint input-state estimation. Each of the conditions is illustrated by a conceptual example. The practical implementation is discussed for a case study where a sensor network for a footbridge is designed.

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Section: Introductionmentioning

confidence: 99%

Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics

Maes

Lourens

Nimmen

et al. 2015

Mechanical Systems and Signal Processing

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“…The time update equations include (7) and (9). The equations for estimating the unknown wind load include (11), (13), (12), and (17). The measurement update equations include (24) to (26).…”

Section: Wind Load Identification Based On Minimum-variancementioning

confidence: 99%

“…Law et al developed a regularization method to obtain the unknown wind load based on structural displacement or strain responses, and this method was numerically validated by identifying the wind load on a 50 m guyed mast [16]. Hwang et al utilized limited measured responses to identify the modal wind load based on Kalman filter method [17,18]. Klinkov and Fritzen identified the wind loads on a 5 MW wind energy plant with a nonlinear observer and implemented the wind load reconstruction technique as a unit into the prototype structural health monitoring system [19].…”

Section: Introductionmentioning

confidence: 99%

“…Gillijns and Moor addressed simultaneously estimating the state and the unknown input method based on the minimumvariance unbiased estimation in 2007 [22,23] and to the best of the authors' knowledge it has not been applied to wind load identification. Several studies observed that identification of the wind load from structural acceleration responses was relatively more stable and robust [17,18]. Meanwhile, the measurement technology of structural acceleration responses is advanced and capable of high precision.…”

Section: Introductionmentioning

confidence: 99%

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Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation

Xue

Lin

Luo

et al. 2017

Shock and Vibration

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A minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown structural responses only with limited measurement of structural acceleration response. The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the wind load on a twenty-story shear building structure. The influences of the number and location of accelerometers are examined and discussed. In order to study the stability of the proposed method, the effects of the errors in crucial factors such as natural frequency and damping ratio are discussed through detailed parametric analysis. It can be found from the identification results that the proposed method can identify the wind load from limited measurement of acceleration responses with good accuracy and stability, indicating that it is an effective approach for estimating wind load on building structures.

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“…In recent years, several teams of researchers have developed the use of modal filters and have applied the results of such analyses in the tasks of vibration control, damage detection, and load identification [1][2][3][4][5][6][7][8][9][10][11][12][13]. Generally speaking, the modal filter extracts the modal coordinates of each individual mode from a system's output.…”

Section: Introductionmentioning

confidence: 99%

Operational modal filter and its applications

Mendrok

Kurowski

2012

Arch Appl Mech

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In the paper, the procedure for the estimation of modal filter coefficients from output-only data is presented. The basic concept of the procedure consists in frequency response functions synthesis based on the knowledge of an operational modal model. A method of operational mode shapes scaling is described. The method is then compared with the classical modal filter and with modal filtration of responses spectra, which is sometimes used as a solution for modal filtration based on the output-only data. Each solution is applied to load identification and damage detection. The study shows the method verification on data obtained from laboratory experiment.

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Estimation of modal loads using structural response

Cited by 70 publications

References 17 publications

Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics

Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics

Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation

Operational modal filter and its applications

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