Using cross correlations of turbulent flow-induced ambient vibrations to estimate the structural impulse response. Application to structural health monitoring

2007 ◽  
Vol 121 (4) ◽  
pp. 1987-1995 ◽  
Author(s):  
Karim G. Sabra ◽  
Eric S. Winkel ◽  
Dwayne A. Bourgoyne ◽  
Brian R. Elbing ◽  
Steve L. Ceccio ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Turbulent Flow ◽  
Impulse Response ◽  
Health Monitoring ◽  
Ambient Vibrations ◽  
Structural Health ◽  
Cross Correlations

scholarly journals Integration of Refined Composite Multiscale Cross-Sample Entropy and Backpropagation Neural Networks for Structural Health Monitoring

2020 ◽  
Vol 10 (3) ◽  
pp. 839 ◽  
Author(s):  
Tzu-Kang Lin ◽  
Yu-Ching Chen
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Confusion Matrix ◽  
Sample Entropy ◽  
Ambient Vibrations ◽  
Analysis Software ◽  
Element Analysis ◽  
Structural Health ◽  
Training Samples

This study developed a structural health monitoring (SHM) system based on refined composite multiscale cross-sample entropy (RCMCSE) and an artificial neural network for monitoring structures under ambient vibrations. RCMCSE was applied to enhance the reliability of entropy estimations. First, RCMCSE was implemented to extract damage features, and finite element analysis software was then used to generate training samples, which included stiffness reductions to achieve various damage patterns. A neural network model was constructed and trained using entropy values for these damage patterns. An experiment was conducted on a seven-story steel benchmark structure to validate the performance of the proposed system. Additionally, a confusion matrix was established to evaluate the performance of the proposed system. The results obtained for a scaled-down benchmark structure indicated that 89.8% of the floors were accurately classified, and 90% of the practical damaged floors were correctly diagnosed. The performance evaluation demonstrated that the proposed SHM system exhibited increased damage location accuracy.

Vibration-Based Structural Health Monitoring – Concepts and Applications

2005 ◽  
Vol 293-294 ◽  
pp. 3-20 ◽  
Author(s):  
Claus Peter Fritzen
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Measurement Data ◽  
Aerospace Engineering ◽  
Current Status ◽  
Ambient Vibrations ◽  
Pronounced Change ◽  
Time Frequency ◽  
Structural Health ◽  
Direct Use

This paper gives an overview on the current status of vibration-based methods for Structural Health Monitoring. All these methods have in common that a structural change due to a damage results in a more or less pronounced change of the dynamic behavior. The use of modal information is discussed, as well as the direct use of forced and ambient vibrations. From this information, different strategies can be deduced which depend on the type of measurement data (time/frequency domain) but also on the frequency spectrum. The incorporation of actuation and sensing devices into the structure leads to modern concepts of Smart Structural Health Monitoring. Examples from civil and aerospace engineering show the applicability of these methods.

Estimation of guided waves from cross‐correlations of diffuse Wavefields for passive Structural Health Monitoring

2008 ◽  
Vol 123 (5) ◽  
pp. 3184-3184
Author(s):  
Adelaide Duroux ◽  
Karim G. Sabra ◽  
Massimo Ruzzene ◽  
Vin Sharma ◽  
James Ayers
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Guided Waves ◽  
Structural Health ◽  
Cross Correlations

Fusion of structural damage identification results from different test scenarios and evaluation indices in structural health monitoring

2020 ◽  
pp. 147592172096216
Author(s):  
XY Li ◽  
SJ Lin ◽  
SS Law ◽  
YZ Lin ◽  
JF Lin
Keyword(s):  
Structural Health Monitoring ◽  
Impulse Response ◽  
Response Function ◽  
Health Monitoring ◽  
Structural Damage ◽  
Impulse Response Function ◽  
Identification Algorithm ◽  
Structural Health ◽  
Damage Indices ◽  
Test Parameters

There are many existing algorithms and damage indices that can effectively meet the engineering need in damage diagnosis. However, all of them (except those with an exact formulation) are based on certain assumptions with approximations, and their performances depend on the combination of test parameters, for example, type, number, and location of excitations and sensors; identification algorithm adopted; and environmental noise effect. Results obtained from different combinations of these test parameters are different and they may be mathematically biased or contradicting. Existing practice adopts the general indication of result for further maintenance decisions or by subjective screening the results with engineering sense. This article demonstrates the possibility to have a better design of the structural health monitoring system where the benefits of different damage indices and evaluation methodologies can be reaped via the fusion of the identified results. The scenario for discussion is the vibration-based damage localization problem. The change in mode shape in the modal domain and change in the covariance of impulse response function change in the time domain are selected as damage indices for the illustration. An exact form of the covariance of impulse response function is also proposed for this purpose. The demonstration is conducted via a simulated truss structure, an experimental beam, and 280 days valid recorded data from an in-service suspension bridge deck. Different measurements are analyzed to produce large number of identified results for reducing traffic excitation effect, the temperature effect, and so on, and to enhance the structural damage information in the final set of results. Experiences in handling the structural health monitoring data for monitoring the movement of a structural joint before and after a typhoon are also presented. The proposed strategy does not need a mathematical model of the structure, but this leads to heavy sensor requirement for a fine spatial resolution of the local damage.

scholarly journals Structural Vibration Monitoring Using Cumulative Spectral Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Satoru Goto ◽  
Yoshinori Takahashi ◽  
Mikio Tohyama
Keyword(s):  
Spectral Analysis ◽  
Structural Health Monitoring ◽  
Impulse Response ◽  
Health Monitoring ◽  
Structural Condition ◽  
Vibration Monitoring ◽  
Structural Vibration ◽  
Scale Model ◽  
Structural Health ◽  
Resonance Decay

This paper describes a resonance decay estimation for structural health monitoring in the presence of nonstationary vibrations. In structural health monitoring, the structure's frequency response and resonant decay characteristics are very important for understanding how the structure changes. Cumulative spectral analysis (CSA) estimates the frequency decay by using the impulse response. However, measuring the impulse response of buildings is impractical due to the need to shake the building itself. In a previous study, we reported on system damping monitoring using cumulative harmonic analysis (CHA), which is based on CSA. The current study describes scale model experiments on estimating the hidden resonance decay under non-stationary noise conditions by using CSA for structural condition monitoring.

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