A new improved regularization method for dynamic load identification

Sun, Xingsheng; Liu, Jie; Han, Xu; Jiang, Chao; Chen, Rui

doi:10.1080/17415977.2013.854353

Cited by 57 publications

(24 citation statements)

References 24 publications

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“…In order to overcome the ill-posedness caused by little singular values, an improved regularization filter function [35] is used to decrease the amplifying influence of σ À 1 j on measurement noises. As a result, the stable and approximate solutionp α for the unknown loads can be achieved through…”

Section: Regularization For Ill-posed Deterministic Problemmentioning

confidence: 99%

A probability density function discretization and approximation method for the dynamic load identification of stochastic structures

Liu

Sun

et al. 2015

Journal of Sound and Vibration

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Section: Regularization For Ill-posed Deterministic Problemmentioning

confidence: 99%

A probability density function discretization and approximation method for the dynamic load identification of stochastic structures

Liu

Sun

et al. 2015

Journal of Sound and Vibration

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“…It is worth noting that the inverse method has been used in many fields such as mechanical engineering, geophysics, astronomy, hydrology, biology, image processing and impact dynamics. [11][12][13] Tarantola [14] presented a relatively complete inverse method to infer the values of the parameters that appear in physics based on conditional probabilities and Bayes's theorem. Han et al [15] measured the property of functionally grade material by means of computational inverse method of neural network and elastic waves.…”

Section: Introductionmentioning

confidence: 99%

Determination of the state parameters of explosive detonation products by computational inverse method

Liu

Han

et al. 2015

Inverse Problems in Science and Engineering

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A computational inverse method is presented to determine the state parameters of Jones-Wilkins-Lee (JWL) equation of explosive detonation products based on cylinder test. In this method, the inverse problem of identifying the JWL parameters is formulated through minimizing the errors of the measured radial displacements on the cylinder surface and those computed by the forward solver. An available numerical model simulated by finite element method is built for the sake of obtaining results using the given JWL parameters. Because of the difference of coordinate systems between experiment and numerical model, it is necessary to conduct the transformation between the two coordinate systems. The sensitivity analysis method is adopted to evaluate the influence of the JWL parameters on the responses and find out the parameters those are suitable to be identified. In order to improve the computational efficiency, radial basis function approximate model is constructed to replace the time-consuming numerical model. In the process of constructing approximate model, the truncated singular value decomposition method is used to deal with the ill-condition of the model. At last, the intergeneration projection genetic algorithm is adopted to identify the parameters. The numerical results demonstrate that the proposed inverse method is potentially available to effectively identify the JWL parameters.

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“…By relating sensitivity distribution in the generic sensitivity matrix to images reconstructed by the conventional Tikhonov regularization method, we found that the non‐uniform sensitivity distribution, which results from the “soft‐field” nature of ECT, is responsible for the artifacts appearing in the near‐wall region. However, previous efforts that have been devoted to improving the conventional Tikhonov regularization method primarily focused on the modification of filter function, optimized objective function, and mathematical model to obtain the optimal value of regularization parameter . To date, little work has been attempted to reduce the artifacts by considering the “soft‐field” nature of ECT.…”

Section: Introductionmentioning

confidence: 99%

Investigation of gas–solid bubbling fluidized beds using ECT with a modified Tikhonov regularization technique

et al. 2017

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Electrical capacitance tomography (ECT) provides a non-intrusive means to visualize cross-sectional material distribution of gas-solid bubbling fluidized beds. Successful application of ECT strongly depends on the image reconstruction algorithm used. For on-line measurements of bubbling fluidized beds, employing an algorithm that can produce highquality images without extensive computation is necessary. Using the conventional Tikhonov regularization algorithm, image quality in the central area is basically satisfied but suffers from artifacts in the near-wall region. To solve this problem, a similar division operation learned from linear back projection was introduced to modify the conventional Tikhonov algorithm. Both numerical simulations and experiments were performed to evaluate the modified technique.The results indicate that the artifacts can be effectively removed and the reconstructed image quality is similar to Landweber method with dozens of iterations. Furthermore, the modified Tikhonov technique shows high accuracy when obtaining important hydrodynamic parameters in gas-solid bubbling fluidized beds. V C 2017 American Institute of Chemical Engineers AIChE J, 64: 29-41, 2018

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A new improved regularization method for dynamic load identification

Cited by 57 publications

References 24 publications

A probability density function discretization and approximation method for the dynamic load identification of stochastic structures

A probability density function discretization and approximation method for the dynamic load identification of stochastic structures

Determination of the state parameters of explosive detonation products by computational inverse method

Investigation of gas–solid bubbling fluidized beds using ECT with a modified Tikhonov regularization technique

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