Structural Damage Detection by Integrating Non-Negative Matrix Factorization and Relevance Vector Machines

2012 ◽  
Vol 249-250 ◽  
pp. 137-146
Author(s):  
Shu Mei Zhou ◽  
Yue Quan Bao
Keyword(s):  
Damage Detection ◽  
Matrix Factorization ◽  
Structural Damage ◽  
Numerical Study ◽  
Wavelet Packet ◽  
Pattern Identification ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Damage Pattern ◽  
Non Negative Matrix Factorization

This paper proposes a structural damage detection method based on wavelet packet decomposition, non-negative matrix factorization (NMF) and a relevance vector machine (RVM). First, vibration data at multiple points are used to calculate the wavelet packet node energies and construct a non-negative damage feature matrix. Second, to increase the damage detection accuracy, the NMF technique is employed to obtain the reduced dimensional representation of the non-negative damage feature matrix and extract the underlying features. Last, the RVM, a powerful tool for classification and regression, that can obtain the probability estimation for classification, is used to determine the relationship between features extracted with NMF and the corresponding damage patterns by considering the measurement noise. The trained RVMs are then used to perform damage pattern identification and classification of an unknown state structure. Numerical study on the Binzhou Yellow River Highway Bridge is carried out to validate the ability of the proposed method in damage detection. The results show that the RVM can achieve a high accuracy in damage pattern identification accuracy using the features extracted by NMF.

Application of Phased Array Antenna Technique in Structural Damage Detection

2011 ◽  
Vol 368-373 ◽  
pp. 1667-1671
Author(s):  
Yu Zhang ◽  
Long Yu ◽  
Yun Ju Yan ◽  
Yu Guo
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Structural Damage ◽  
Phased Array ◽  
Tone Burst ◽  
Array Antenna ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Phased Array Antenna ◽  
Energy Leakage

Over decades phased array antenna technique attracts much more attention in Lamb wave based structural damage detection. Lamb wave generated by the piezoelectric wafers omnidirectionally could be steered at a specific direction during its propagation. Thus, the wave beam steering and focusing has been established, the location of structural damage is done with pulse-echo method by wave propagation. However, the detection accuracy will decrease as side bands energy leakage during wave propagation, so, signals to be generated have to be modified by window tone burst in order to concentrate energy in main bands and minimize the effect of dispersion side bands. In this paper, signals modified by Hanning-windowed tone burst was used to decrease the effect of side bands energy leakage, the results improved the detection accuracy better than signals without window tone burst and show good agreement with theoretical results. Meanwhile, A numerical simulation of aluminium plate demonstrates that phased array antenna technique is feasible in structural damage detection.

Structural damage detection via combining weighted strategy with trace Lasso

2018 ◽  
Vol 22 (3) ◽  
pp. 597-612 ◽  
Author(s):  
Chengbin Chen ◽  
Chudong Pan ◽  
Zepeng Chen ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Swarm Intelligence ◽  
Structural Damage ◽  
Optimization Problem ◽  
Detection Method ◽  
Rapid Development ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Selection Operator

With the rapid development of computation technologies, swarm intelligence–based algorithms become an innovative technique used for addressing structural damage detection issues, but traditional swarm intelligence–based structural damage detection methods often face with insufficient detection accuracy and lower robustness to noise. As an exploring attempt, a novel structural damage detection method is proposed to tackle the above deficiency via combining weighted strategy with trace least absolute shrinkage and selection operator (Lasso). First, an objective function is defined for the structural damage detection optimization problem by using structural modal parameters; a weighted strategy and the trace Lasso are also involved into the objection function. A novel antlion optimizer algorithm is then employed as a solution solver to the structural damage detection optimization problem. To assess the capability of the proposed structural damage detection method, two numerical simulations and a series of laboratory experiments are performed, and a comparative study on effects of different parameters, such as weighted coefficients, regularization parameters and damage patterns, on the proposed structural damage detection methods are also carried out. Illustrated results show that the proposed structural damage detection method via combining weighted strategy with trace Lasso is able to accurately locate structural damages and quantify damage severities of structures.

Structural damage detection from wavelet packet sensitivity

2005 ◽  
Vol 27 (9) ◽  
pp. 1339-1348 ◽  
Author(s):  
S.S. Law ◽  
X.Y. Li ◽  
X.Q. Zhu ◽  
S.L. Chan
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Wavelet Packet ◽  
Structural Damage Detection

Structural Damage Identification Based on Information Fusion Techniques

2010 ◽  
Author(s):  
Hui Li ◽  
Yuequan Bao
Keyword(s):  
Damage Detection ◽  
Information Fusion ◽  
Structural Damage ◽  
Damage Identification ◽  
Yellow River ◽  
Numerical Study ◽  
Detection Methods ◽  
Data Sets ◽  
Structural Damage Detection ◽  
Selective Fusion

With the aim to decrease the uncertainties of structural damage detection, two fusion models are presented in this paper. The first one is a weighted and selective fusion method for combing the multi-damage detection methods based on the integration of artificial neural network, Shannon entropy and Dempster-Shafer (D-S) theory. The second one is a D-S based approach for combing the damage detection results from multi-sensors data sets. Numerical study on the Binzhou Yellow River Highway Bridge and an experimental of a 20-bay rigid truss structure were carried out to validate the uncertainties decreasing ability of the proposed methods for structural damage detection. The results show that both of the methods proposed are useful to decrease the uncertainties of damage detection results.

Structural Damage Detection Using Signal Pattern-Recognition

2008 ◽  
Vol 400-402 ◽  
pp. 465-470 ◽  
Author(s):  
Long Qiao ◽  
Asad Esmaeily ◽  
Hani G. Melhem
Keyword(s):  
Pattern Recognition ◽  
Damage Detection ◽  
Structural Damage ◽  
Experimental Studies ◽  
Least Square ◽  
Structural Damage Detection ◽  
Damage Scenario ◽  
Damage Pattern ◽  
Damage Scenarios ◽  
Unknown Damage

Deterioration significantly affects the structure performance and safety. A signal-based pattern-recognition procedure is applied for structural damage detection with a limited number of input/output signals. The method is based on extracting and selecting the sensitive features of the structure response to form a unique pattern for any particular damage scenario, and recognizing the unknown damage pattern against the known database to identify the damage location and level (severity). In this study, two types of transformation algorithms are implemented separately for feature extraction: (1) Continuous Wavelet Transform (CWT); and (2) Wavelet Packet Transform (WPT). Three pattern-matching algorithms are also implemented separately for pattern recognition: (1) correlation, (2) least square distance, and (3) Cosh spectral distance. To demonstrate the validity and accuracy of the procedure, experimental studies are conducted on a simple three-story steel structure. The results show that the features of the signal for different damage scenarios can be uniquely identified by these transformations, and correlation algorithms can best perform pattern recognition to identify the unknown damage pattern. The proposed method can also be used to possibly detect the type of damage. It is suitable for structural health monitoring, especially for online monitoring applications.

Detection of Small Damage of Beam Structures Based on the Slope of Proper Orthogonal Mode

2010 ◽  
Vol 97-101 ◽  
pp. 4457-4460
Author(s):  
Dan Sheng Wang ◽  
Ying Bo Zhang ◽  
Hai Ping Yang ◽  
Hong Ping Zhu
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Detection Method ◽  
Numerical Study ◽  
Structural Damage Detection ◽  
Beam Structures ◽  
Study Results ◽  
The Difference ◽  
Proper Orthogonal

In recent two decades, the issues on structural damage detection and health monitoring have been paid considerable attention in mechanical and civil engineering communities. A lot of researchers have developed many methods to try to resolve the problems. To this day, detection of the small damage of structures, however, has still been a difficulty. The correlation theories of proper orthogonal decomposition (POD) and the basic principle of a new structural damage detection method based on the slope of POD are introduced in this paper. Numerical study on beam structures for small damage detection based on the proposed method is implemented. From the study results one can find that the method based on the slope of the difference of proper orthogonal modes (POMs) has the abilities to localize the small damage of beam structures.

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