scholarly journals A Numerical Study on Computational Time Reversal for Structural Health Monitoring

Signals ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 225-244
Author(s):  
Christos G. Panagiotopoulos ◽  
Georgios E. Stavroulakis
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Time Reversal ◽  
Numerical Study ◽  
Real Life ◽  
Computational Time ◽  
External Loading ◽  
Sensors And Actuators ◽  
Time Reversibility ◽  
Structural Health

Structural health monitoring problems are studied numerically with the time reversal method (TR). The dynamic output of the structure is applied, time reversed, as an external loading and its propagation within the deformable medium is followed backwards in time. Unknown loading sources or damages can be discovered by means of this method, focused by the reversed signal. The method is theoretically justified by the time-reversibility of the wave equation. Damage identification problems relevant to structural health monitoring for truss and frame structures are studied here. Beam structures are used for the demonstration of the concept, by means of numerical experiments. The influence of the signal-to-noise ratio (SNR) on the results was investigated, since this quantity influences the applicability of the method in real-life cases. The method is promising, in view of the increasing availability of distributed intelligent sensors and actuators.

scholarly journals Online frequency and amplitude tracking in structural vibrations under environment using APES spectrum postprocessing and Kalman filtering

2021 ◽  
Author(s):  
Xuewen Yu ◽  
Danhui Dan
Keyword(s):  
Structural Health Monitoring ◽  
Kalman Filtering ◽  
Health Monitoring ◽  
Time Window ◽  
Numerical Study ◽  
Amplitude Spectrum ◽  
Real Life ◽  
Structural Vibrations ◽  
Vibration Signals ◽  
Structural Health

Identifying time-varying frequency and amplitude online in real-life structural vibrations is an essential topic of data processing in structural health monitoring. This paper proposes a novel method for this task. We assume that structural vibration signals are stationary in a short time, thus a spectral analysis method called amplitude and phase estimation (APES) is conducted to obtain the amplitude spectrum at corresponding time window, and a postprocessing technique is proposed to extract the modal frequency and amplitude from the spectrum automatically. The extracted frequency and amplitude could be regarded as the average of the instantaneous frequency and instantaneous amplitude during the window. Due to the instability of measured structural vibrations and the uncertainty of spectral shapes under ambient excitation, Kalman ?filtering is introduced by taking the signal that reconstructed from the identi?fied frequencies and amplitudes as the prediction to enhance the reliability and quality (signal-to-noise ratio) of the next measured signals. Numerical study is performed to inspect the performance of the proposed method. It is also employed to analyze the vibration signals of actual structures, i.e., a cable of a cable-stayed bridge, a hanger of an arch bridge and the main girder of a suspension bridge. The results show its potential to track frequency and amplitude in structural vibrations under environmental measurements. The method is supposed to provide fundamental support for further information obtaining and high-level decision making for structural health monitoring systems.

scholarly journals Numerical Study of a Multi-Layered Strain Sensor for Structural Health Monitoring of Asphalt Pavement

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 41
Author(s):  
Jiayue Shen ◽  
Minghao Geng ◽  
Abby Schultz ◽  
Weiru Chen ◽  
Hao Qiu ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Polyurethane Foam ◽  
Health Monitoring ◽  
Numerical Study ◽  
Asphalt Pavement ◽  
Strain Sensor ◽  
Traffic Load ◽  
Structural Health ◽  
Initiation And Propagation ◽  
Load Monitoring

Crack initiation and propagation vary the mechanical properties of the asphalt pavement and further alter its designate function. As such, this paper describes a numerical study of a multi-layered strain sensor for the structural health monitoring (SHM) of asphalt pavement. The core of the sensor is an H-shaped Araldite GY-6010 epoxy-based structure with a set of polyvinylidene difluoride (PVDF) piezoelectric transducers in its center beam, which serve as a sensing unit, and a polyurethane foam layer at its external surface which serves as a thermal insulation layer. Sensors are coated with a thin layer of urethane casting resin to prevent the sensor from being corroded by moisture. As a proof-of-concept study, a numerical model is created in COMSOL Multiphysics to simulate the sensor-pavement interaction, in order to design the strain sensor for SHM of asphalt pavement. The results reveal that the optimum thickness of the middle polyurethane foam is 11 mm, with a ratio of the center beam/wing length of 3.2. The simulated results not only validate the feasibility of using the strain sensor for SHM (traffic load monitoring and damage detection), but also to optimize design geometry to increase the sensor sensitivity.

Time reversal focusing for pipeline structural health monitoring.

2009 ◽  
Vol 126 (4) ◽  
pp. 2197
Author(s):  
Joel Harley ◽  
Nicholas O’Donoughue ◽  
José M.F. Moura ◽  
Yuanwei Jin
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Time Reversal ◽  
Structural Health

scholarly journals Smart Sensing Technologies for Structural Health Monitoring of Civil Engineering Structures

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
M. Sun ◽  
W. J. Staszewski ◽  
R. N. Swamy
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Smart Materials ◽  
Civil Engineering ◽  
Piezoelectric Sensors ◽  
Sensors And Actuators ◽  
Engineering Structures ◽  
Structural Health ◽  
Civil Engineering Structures ◽  
Smart Sensing

Structural Health Monitoring (SHM) aims to develop automated systems for the continuous monitoring, inspection, and damage detection of structures with minimum labour involvement. The first step to set up a SHM system is to incorporate a level of structural sensing capability that is reliable and possesses long term stability. Smart sensing technologies including the applications of fibre optic sensors, piezoelectric sensors, magnetostrictive sensors and self-diagnosing fibre reinforced composites, possess very important capabilities of monitoring various physical or chemical parameters related to the health and therefore, durable service life of structures. In particular, piezoelectric sensors and magnetorestrictive sensors can serve as both sensors and actuators, which make SHM to be an active monitoring system. Thus, smart sensing technologies are now currently available, and can be utilized to the SHM of civil engineering structures. In this paper, the application of smart materials/sensors for the SHM of civil engineering structures is critically reviewed. The major focus is on the evaluations of laboratory and field studies of smart materials/sensors in civil engineering structures.

A synthetic time-reversal imaging method for structural health monitoring

2004 ◽  
Vol 13 (2) ◽  
pp. 415-423 ◽  
Author(s):  
Chun H Wang ◽  
James T Rose ◽  
Fu-Kuo Chang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Time Reversal ◽  
Imaging Method ◽  
Structural Health
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