Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient
Joint Authors
Liu, Chunsheng
Ren, Chunping
Wang, Nengjian
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-30
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
We propose a novel mathematical algorithm to offer a solution for the inverse random dynamic force identification in practical engineering.
Dealing with the random dynamic force identification problem using the proposed algorithm, an improved maximum entropy (IME) regularization technique is transformed into an unconstrained optimization problem, and a novel conjugate gradient (NCG) method was applied to solve the objective function, which was abbreviated as IME-NCG algorithm.
The result of IME-NCG algorithm is compared with that of ME, ME-CG, ME-NCG, and IME-CG algorithm; it is found that IME-NCG algorithm is available for identifying the random dynamic force due to smaller root mean-square-error (RMSE), lower restoration time, and fewer iterative steps.
Example of engineering application shows that L-curve method is introduced which is better than Generalized Cross Validation (GCV) method and is applied to select regularization parameter; thus the proposed algorithm can be helpful to alleviate the ill-conditioned problem in identification of dynamic force and to acquire an optimal solution of inverse problem in practical engineering.
American Psychological Association (APA)
Ren, Chunping& Wang, Nengjian& Liu, Chunsheng. 2017. Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1192616
Modern Language Association (MLA)
Ren, Chunping…[et al.]. Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient. Mathematical Problems in Engineering No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1192616
American Medical Association (AMA)
Ren, Chunping& Wang, Nengjian& Liu, Chunsheng. Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1192616
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1192616