Full-field optical deformation measurement and operational modal analysis of a flexible rotor blade

2019 ◽  
Vol 133 ◽  
pp. 106265 ◽  
Author(s):  
Daiju Uehara ◽  
Jayant Sirohi
Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1602
Author(s):  
Ángel Molina-Viedma ◽  
Elías López-Alba ◽  
Luis Felipe-Sesé ◽  
Francisco Díaz

Experimental characterization and validation of skin components in aircraft entails multiple evaluations (structural, aerodynamic, acoustic, etc.) and expensive campaigns. They require different rigs and equipment to perform the necessary tests. Two of the main dynamic characterizations include the energy absorption under impact forcing and the identification of modal parameters through the vibration response under any broadband excitation, which also includes impacts. This work exploits the response of a stiffened aircraft composite panel submitted to a multi-impact excitation, which is intended for impact and energy absorption analysis. Based on the high stiffness of composite materials, the study worked under the assumption that the global response to the multi-impact excitation is linear with small strains, neglecting the nonlinear behavior produced by local damage generation. Then, modal identification could be performed. The vibration after the impact was measured by high-speed 3D digital image correlation and employed for full-field operational modal analysis. Multiple modes were characterized in a wide spectrum, exploiting the advantages of the full-field noninvasive techniques. These results described a consistent modal behavior of the panel along with good indicators of mode separation given by the auto modal assurance criterion (Auto-MAC). Hence, it illustrates the possibility of performing these dynamic characterizations in a single test, offering additional information while reducing time and investment during the validation of these structures.


2018 ◽  
Vol 144 (7) ◽  
pp. 04018054 ◽  
Author(s):  
Charles Dorn ◽  
Sudeep Dasari ◽  
Yongchao Yang ◽  
Charles Farrar ◽  
Garrett Kenyon ◽  
...  

Author(s):  
Gen Fu ◽  
Alexandrina Untaroiu

Abstract Full field response of a structure is critical for evaluating the performance of large slender structures. Since only several discrete measurements can be acquired during operation, the data expansion method is important for the estimation of the full field responses of the large complex structure. In previous studies, modal transformation methods were mainly applied in model reduction/expansion and global shape sensing. Compared to other expansion methods, the modal method is straightforward to implement and computational efficient, which makes it the most suitable approach for real-time expansion. However, only the first several modes were included in the modal transformation method in previous studies. Since the errors due to truncated mode components can occur under high frequency band excitations, it is necessary to include all of the modes that contribute significantly to the responses of the structure. Therefore, in this study, a modal selection method based on operational modal analysis (OMA) is proposed for selecting proper modes. The modal characteristics of the system were derived with the strain data at several discrete locations. The contribution of each mode was quantified. By sorting the modes based on their contribution, the most significant modes can be used in the expansion process. Two operational modal analysis methods, stochastic system identification (SSI) and frequency domain decomposition (FDD), were considered and compared. The proposed approach was implemented with a computational model. Considerable improvement has been observed when high bandwidth excitations were added. The proposed modal selection method can successfully rank the participated modes. It can improve the accuracy of the modal transformation approach as shown in the impact loading case. It can be used for data expansion even when high frequency band is excited. Finally, we believe the novel methods presented in this study could be used in the development of more reliable health monitoring systems for turbomachinery.


2021 ◽  
Author(s):  
David F. Castillo Zuñiga ◽  
Alain Giacobini Souza ◽  
Roberto G. da Silva ◽  
Luiz Carlos Sandoval Góes

Sign in / Sign up

Export Citation Format

Share Document