scholarly journals Gaussian and Golden Wavelets: A Comparative Study and their Applications in Structural Health Monitoring

2021 ◽  
Vol 22 (1) ◽  
pp. 139-155
Author(s):  
F. E. Gossler ◽  
B. R. Oliveira ◽  
M. A. Q. Duarte ◽  
J. Vieira Filho ◽  
F. Villarreal ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Structural Health Monitoring ◽  
Comparative Study ◽  
Health Monitoring ◽  
Scale Space ◽  
Vanishing Moments ◽  
Real Signal ◽  
Structural Health ◽  
Frequency Domains ◽  
Base Functions

In this work, a comparative analysis between Gaussian and Golden wavelets is presented. These wavelets are generated by the derivative of specific base functions. In this case, the order of the derivative also indicates the number of vanishing moments of the wavelet. Although these wavelets have a similar waveform, they have several distinct characteristics in time and frequency domains. These distinctions are explored here in the scale space. In order to compare the results provided by these wavelets for a real signal, they are used in the decomposition of a signal inserted in the context of structural health monitoring.

scholarly journals Comparative Study of Fiber Bragg Gratings and Fiber Polarimetric Sensors for Structural Health Monitoring of Carbon Composites

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Massimo Olivero ◽  
Guido Perrone ◽  
Alberto Vallan ◽  
Daniele Tosi
Keyword(s):  
Structural Health Monitoring ◽  
Comparative Study ◽  
Health Monitoring ◽  
Smart Materials ◽  
Vibration Monitoring ◽  
Carbon Fiber Composites ◽  
Test Plate ◽  
Structural Health ◽  
Dynamic Excitation ◽  
Cheap Alternative

A comparative study is presented between Bragg grating (FBG) and polarimetric sensors (PS), two of the most promising fiber optic sensing techniques for the structural health monitoring of smart materials based on carbon fiber composites. The paper describes the realization of a test plate equipped with both types of sensors and reports the characterization under static and dynamic conditions, highlighting pros and cons of both technologies. The FBG setup achieves 1.15 ± 0.0016 pm/kg static load response and reproduces dynamic excitation with 0.1% frequency uncertainty; the PS system exhibits a sensitivity of 1.74 ± 0.001 mV/kg and reproduces dynamic excitation with 0.5% frequency uncertainty. It is shown that the PS technology is a good and cheap alternative to FBG for vibration-monitoring of small structures at high frequency.

scholarly journals A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Guang-Dong Zhou ◽  
Ting-Hua Yi ◽  
Huan Zhang ◽  
Hong-Nan Li
Keyword(s):  
Structural Health Monitoring ◽  
Comparative Study ◽  
Health Monitoring ◽  
Firefly Algorithm ◽  
Hamming Distance ◽  
Optimization Problems ◽  
High Reliability ◽  
Sensor Placement ◽  
Structural Health ◽  
Wide Range

Optimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is conducted. To overcome the drawback related to the inapplicability of the FA in optimization problems with discrete variables, some improvements are proposed, including the one-dimensional binary coding system, the Hamming distance between any two fireflies, and the semioriented movement scheme; also, a simple discrete firefly algorithm (SDFA) is developed. The capabilities of the SDFA and the GA in finding the optimal sensor locations are evaluated using two disparate objective functions in a numerical example with a long-span benchmark cable-stayed bridge. The results show that the developed SDFA can find the optimal sensor configuration with high reliability. The comparative study indicates that the SDFA outperforms the GA in terms of algorithm complexity, computational efficiency, and result quality. The optimization mechanism of the FA has the potential to be extended to a wide range of optimization problems.

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