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Research on characteristic function for cable inverse analysis based on dynamic stiffness theory and its application.
- Source :
-
Engineering Structures . Sep2019, Vol. 194, p384-395. 12p. - Publication Year :
- 2019
-
Abstract
- • A cable inverse-analysis characteristic function. • A parameter identification method based on the H-I ridges of characteristic function. • Identify cable force and bending stiffness simultaneously. • Short cables should consider bending stiffness, while long cables is negligible. • Short cables are more sensitive to cable length errors than long cables. • Bending stiffness of cables is variation with tension force with the same cables. Parameter identification of cables in the operation period is a significant issue related to the state of serviceability and safety evaluation of cables. A generalized characteristic function is established based on the dynamic stiffness theory to identify cable parameters in the study. The characteristic function exhibits an analytical form. The function relatively fits actual engineering cables due to comprehensively considering cable bending stiffness, sag, inclination, etc., and thus it is a relatively accurate inverse-analysis model of cable parameters. The variation of bending stiffness and cable force with different geometric parameters and the influence of geometric parameters on the identification accuracy of the two parameters are investigated based on numerical analysis. And a parameter identification method based on the H-I ridges of inverse-analysis characteristic function is proposed. The proposed method identifies cable parameters using the multi-order frequencies of cables simultaneously, and the order of modal frequencies and the fundamental or lower-order frequency are not required in the application of the proposed method. Finally, the results of tension tests on two real cables with lengths of 20 m and 168 m verify the applicability of the inverse-analysis characteristic function and the parameter identification method proposed in the study. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01410296
- Volume :
- 194
- Database :
- Academic Search Index
- Journal :
- Engineering Structures
- Publication Type :
- Academic Journal
- Accession number :
- 136878709
- Full Text :
- https://doi.org/10.1016/j.engstruct.2019.05.062