scholarly journals Guided wave signal transport in curved and tapered plates

2013 ◽  
Author(s):  
R. A. Roberts
Keyword(s):  
Guided Wave ◽  
Wave Signal ◽  
Tapered Plates

The method of bolt axial force looseness monitoring and control by piezoelectric ceramics in bolted joint structures

2021 ◽  
pp. 095440622110398
Author(s):  
Xinyao Sun ◽  
Jinggan Shao ◽  
Yang Zhou ◽  
Ci Yuan ◽  
Yang Li ◽  
...  
Keyword(s):  
Finite Element ◽  
Active Control ◽  
Axial Force ◽  
Piezoelectric Ceramic ◽  
Control Method ◽  
Piezoelectric Effect ◽  
Guided Wave ◽  
Clamping Force ◽  
Monitoring And Control ◽  
Wave Signal

Aiming at the problem of bolt looseness in structures, this paper proposes an active control method of axial force monitoring through guided wave and axial force compensation via the inverse piezoelectric effect of a piezoelectric ceramic gasket. Based on the finite element model, the propagation process of guided wave wave in bolted connectors is analyzed, which shows that the transmitted wave energy increases with the increase of bolt clamping force. The analysis of the stress-strain characteristics of the axially polarized and radially polarized piezoelectric ceramic gasket shows that the axially polarized piezoelectric ceramic gasket is more suitable for the control of bolt clamping force. The finite element analysis of the application of piezoelectric ceramic gasket in bolt axial force control shows that the power of guided wave signal increases monotonously with the increase of loaded electric field strength. In accordance with these theoretical methods and research, an active control system for bolt axial force is established in this experiment. The system monitors the power of the guided wave signal in real time and controls the axial force of the bolt by adjusting the intensity of the piezoelectric effect, which achieves an accurate control effect.

Model Classification of Guided Wave Signal based on the Visibility Graph and SVM

2018 ◽  
Author(s):  
Weilei MU ◽  
Zhengxing ZOU ◽  
Hailiang SUN ◽  
Guijie LIU ◽  
Guangyin XIA ◽  
...  
Keyword(s):  
Guided Wave ◽  
Visibility Graph ◽  
Wave Signal ◽  
Model Classification

scholarly journals Study on the Property of Guided Wave Signal Analysis according to Defect Shape of Small Size

2012 ◽  
Vol 32 (4) ◽  
pp. 410-417
Author(s):  
Doo-Song Gil ◽  
Yeon-Shik Ahn ◽  
Gye-Jo Jung ◽  
Sang-Gi Park ◽  
Yong-Gun Kim
Keyword(s):  
Signal Analysis ◽  
Guided Wave ◽  
Wave Signal

Guided-wave signal processing by the sparse Bayesian learning approach employing Gabor pulse model

2016 ◽  
Vol 16 (3) ◽  
pp. 347-362 ◽  
Author(s):  
Biao Wu ◽  
Yong Huang ◽  
Xiang Chen ◽  
Sridhar Krishnaswamy ◽  
Hui Li
Keyword(s):  
Damage Detection ◽  
Bayesian Learning ◽  
Guided Waves ◽  
Learning Algorithm ◽  
Guided Wave ◽  
Sparse Bayesian Learning ◽  
Mode Identification ◽  
Wave Signal ◽  
Gabor Dictionary ◽  
The Many

Guided waves have been used for structural health monitoring to detect damage or defects in structures. However, guided wave signals often involve multiple modes and noise. Extracting meaningful damage information from the received guided wave signal becomes very challenging, especially when some of the modes overlap. The aim of this study is to develop an effective way to deal with noisy guided-wave signals for damage detection as well as for de-noising. To achieve this goal, a robust sparse Bayesian learning algorithm is adopted. One of the many merits of this technique is its good performance against noise. First, a Gabor dictionary is designed based on the information of the noisy signal. Each atom of this dictionary is a modulated Gaussian pulse. Then the robust sparse Bayesian learning technique is used to efficiently decompose the guided wave signal. After signal decomposition, a two-step matching scheme is proposed to extract meaningful waveforms for damage detection and localization. Results from numerical simulations and experiments on isotropic aluminum plate structures are presented to verify the effectiveness of the proposed approach in mode identification and signal de-noising for damage detection.

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