Vibration-Based Damage Identification in Structures Exhibiting Axial and Torsional Response

2000 ◽  
Vol 123 (1) ◽  
pp. 84-91 ◽  
Author(s):  
T. A. Duffey ◽  
S. W. Doebling ◽  
C. R. Farrar ◽  
W. E. Baker ◽  
W. H. Rhee

A method is derived to detect and localize linear damage in a structure using the measured modal vibration parameters. This method is applicable when the vibration strain energy is stored in the axial or torsional modes, which differentiates it from previously derived strain-energy-based methods. The new method is compared to the previously derived flexibility-change method for comparison. Both methods are verified by application to an analytical eight degree of freedom model. Experimental validation for both methods is also presented by application to an experimental eight degree of freedom spring-mass structure.

Robotica ◽  
1999 ◽  
Vol 17 (5) ◽  
pp. 475-485 ◽  
Author(s):  
Zhen Huang ◽  
Y. Lawrence Yao

This paper presents a new method to analyze the closed-form kinematics of a generalized three-degree-of-a-freedom spherical parallel manipulator. Using this analytical method, concise and uniform solutions are achieved. Two special forms of the three-degree-of-freedom spherical parallel manipulator, i.e. right-angle type and a decoupled type, are also studied and their unique and interesting properties are investigated, followed by a numerical example.


2019 ◽  
Vol 11 (1) ◽  
pp. 168781401881990 ◽  
Author(s):  
Hui-Yong Guo ◽  
He-Fa Yuan ◽  
Qi Huang

It is difficult for the traditional methods to identify uncertain damage problems caused by noise. Therefore, a gray cloud rule generator algorithm based on cloud model and modal strain energy is presented to solve the problems. Cloud model can simulate both randomness and fuzziness with fixed parameters. Therefore, it is applicable for the uncertain damage problems. First, modal strain energy and modal strain energy dissipation ratio index are introduced. Then, numerical characteristics of a cloud model are described and some cloud generators are analyzed. Finally, a gray cloud rule is proposed and the gray cloud rule generator algorithm based on the gray cloud rule generator and modal strain energy is developed. The interference of uncertain noise is reduced through a large number of cloud droplets. A two-dimensional truss structure model has been used to verify the effectiveness of the algorithm. The results indicate that the proposed gray cloud rule generator algorithm is applicable to identify the uncertain damage caused by noise, and the identification results of the proposed method are relatively better than those of modal strain energy dissipation ratio index.


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