Journal ArticleDOI
Load Identification Using a Modified Modal Filter Technique
Krzysztof Mendrok,Tadeusz Uhl +1 more
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Abstract:
In this paper the authors propose a modification to the known force identification procedure based on modal filtration. The modification consists of replacing the modal vectors with the Ritz vectors. The latter seem to be more accurate because they take into account the static deformation of the structure and are less sensitive to truncation error. After the main idea- the algorithm modification- is presented, it is verified and then compared with the original solution. Two sets of data are used for this purpose, firstly simulation data from the numerical model, and then physical data recorded during a laboratory experiment.read more
Citations
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Journal ArticleDOI
A radial basis function artificial neural network (RBF ANN) based method for uncertain distributed force reconstruction considering signal noises and material dispersion
TL;DR: A radial basis function artificial neural network (RBF ANN) based method for distributed dynamic force reconstruction considering multi-source uncertainties is presented in this paper, where the distributed forces are approximated by truncated Legendre orthogonal polynomial in the time history.
Journal ArticleDOI
A support vector regression (SVR)-based method for dynamic load identification using heterogeneous responses under interval uncertainties
TL;DR: A support vector regression (SVR)-based method is presented, which aims to reconstruct the uncertain dynamic load using heterogeneous responses, and results indicate that the proposed method can be utilized to identify the interval of dynamic load with outstanding accuracy and efficiency.
Journal ArticleDOI
Impact localization and identification under a constrained optimization scheme
Qiaofeng Li,Qiuhai Lu +1 more
TL;DR: In this paper, a method for localization and identification of impact is proposed, where the location of impact was first determined with an error functional indicator using the complex method, and the identification of the impact history was then considered a constrained optimization problem.
Journal ArticleDOI
Fatigue test load identification using weighted modal filtering based on stress
TL;DR: In this article, a modal shape filter is used to control the test such that the shapes that are generating stress in critical points are reproduced, and a selective weighting of the mode shapes allows for accurate reproduction of the stress and hence the damage, also in circumstances when the exact location of the excitation force cannot be reconstructed in the test.
Extraction of ritz vectors from vibration test data
Hoon Sohn,Kincho H. Law +1 more
TL;DR: This paper presents a procedure to extract load-dependent Ritz vectors using a complete flexibility matrix constructed from measured vibration test data and cannot only construct the RitzVector corresponding to the actual load pattern employed in vibration tests, but also generate Ritz vector from arbitrary load patterns.
References
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Journal ArticleDOI
An eigensystem realization algorithm for modal parameter identification and model reduction
Jer-Nan Juang,Richard S. Pappa +1 more
TL;DR: A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm.
Journal ArticleDOI
Inverse Problems in Vibration
TL;DR: In this article, a review of the literature on inverse problems relating to the reconstruction or estimation of the physical properties of mechanical systems from a knowledge of (some of) their spectral and/or modal data is presented.
ReportDOI
Force Reconstruction Using the Sum of Weighted Accelerations Technique-Max-flat Procedure
TL;DR: In this paper, a new method of estimating the weights, using measured frequency response function data, is developed and contrasted with the traditional SWAT method of inverting the mode-shape matrix, but is not based on deconvolution.
A procedure to extract ritz vectors from dynamic testing data
TL;DR: In this article, the authors extend the usefulness of Ritz vectors by developing an approach to extract Ritz vector from measured dynamic data, which has been shown to offer superior performance in model reduction and time-simulations.