Acoustic impact testing and waveform analysis for damage detection in glued laminated timber

Holzforschung ◽  
2017 ◽  
Vol 71 (10) ◽  
pp. 801-811 ◽  
Author(s):  
Feng Xu ◽  
Xiping Wang ◽  
Marko Teder ◽  
Yunfei Liu
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Wavelet Packet ◽  
Acoustic Signals ◽  
Impact Testing ◽  
Waveform Analysis ◽  
Structural Defects ◽  
Glued Laminated Timber ◽  
Acoustic Impact ◽  
First Moment

AbstractDelamination and decay are common structural defects in old glued laminated timber (glulam) buildings, which, if left undetected, could cause severe structural damage. This paper presents a new damage detection method for glulam inspection based on moment analysis and wavelet transform (WT) of impact acoustic signals. Acoustic signals were collected from a glulam arch section removed from service through impact testing at various locations. The presence and positions of internal defects were preliminarily determined by applying time centroid and frequency centroid of the first moment. Acoustic signals were then decomposed by wavelet packet transform (WPT) and the energy of the sub-bands was calculated as characteristics of the response signals. The sub-bands of 0–375 Hz and 375–750 Hz were identified as the most discriminative features that are associated with decay and delamination and therefore are indicative of the presence of delamination or decay defects. A defect diagnosis algorithm was tested for its ability to identify internal decay and delamination in glulam. The results show that depth of delamination in a glulam member can be determined with reasonable accuracy.

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 Health Monitoring (SHM) of Offshore Jacket Platforms

2011 ◽  
Author(s):  
Mohammad Ali Lotfollahi-Yaghin ◽  
Sajad Shahverdi ◽  
Reza Tarinejad ◽  
Behrouz Asgarian
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Structural Damage ◽  
Wavelet Packet ◽  
Structural Health ◽  
Finite Element Software ◽  
Modal Properties ◽  
Large Structures

In the present paper, Structural health monitoring has become an evolving area of research in last few decades with increasing need of online monitoring the health of large structures. The damage detection by visual inspection of the structure can prove impractical, expensive and ineffective in case of large structures like offshore platforms, multistoried buildings and bridges. Structural health monitoring is defined as the process of detecting damage in a structural system. Damage in the system causes a change in dynamic properties of a system. The structural damage is typically a local phenomenon, which tends to be captured by higher frequency signals. Most of vibration-based damage detection methods require the modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such a good sensitive indication of structural damage. Structural damage detection and damage localization of jacket platforms, based on wavelet packet transforms is presented in this paper. Dynamic signals measured from the structure by the finite element software package ANSYS are first decomposed into wavelet packet components. Component energies are then calculated and used for damage assessment. The results show that the WPT-based component energies are good candidate indices that are sensitive to structural damage. These component energies can be used for damage assessment including identifying damage occurrence and location.

Application of Wavelet Packet Transform and Neural Network to Detect Damage of Elastic Thin Plate

2012 ◽  
Vol 594-597 ◽  
pp. 1105-1108 ◽  
Author(s):  
Dong Hai Xie ◽  
Hong Wei Tang
Keyword(s):  
Damage Detection ◽  
Thin Plate ◽  
Structural Damage ◽  
Civil Engineering ◽  
Wavelet Packet ◽  
Engineering Application ◽  
Physical Models ◽  
Structural Damage Detection ◽  
Engineering Structures ◽  
Elastic Thin Plate

In recent years,most existing engineering structures which have approached their normal life span, such as concrete plate, concrete beam etc., Almost all of these architecture structures are subjected to damage due to external loads, initial design defect etc. Structural damage detection and assessment has been becoming a focus of increasing interest in civil engineering field. However,At present, the study on structural damage detection is still at initial stage and the adopted main approaches are theoretical analysis and numerical simulation, but physical models are scarce. This leads to the yielded theories and methods are not sufficiently applicable for practical engineering application. Aiming at this, this paper focuses on developing effective methods of using wavelet and neural networks to detect the damage of elastic thin plate due to their extensive applications in civil engineering.

Damage Detection in Offshore Free Span Pipelines Using Wavelet Packet Transform

2011 ◽  
Author(s):  
Sajad Shahverdi ◽  
Mohammad Ali Lotfollahi-Yaghin ◽  
Mohammad Hossein Aminfar ◽  
Ramin Valizadeh
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Wavelet Packet ◽  
Offshore Structures ◽  
Wavelet Packet Transform ◽  
Detection Methods ◽  
Mode Shapes ◽  
Mathematical Tool ◽  
Energy Rate ◽  
Modal Properties

During the service life, offshore structures continually accumulate damage as a result of applying the various environmental forces. Clearly the development of strong techniques for early damage detection is very important to avoid the possible occurrence of a disastrous structural failure. Most of vibration-based damage detection methods require the modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such a good sensitive indication of structural damage. The wavelet packet transform (WPT) is a mathematical tool that has a special advantage over the traditional Fourier transform in analyzing non-stationary signals. In this study, a damage detection index called wavelet packet energy rate index (WPERI), is used for the damage detection of offshore free span pipelines. The measured dynamic signals are decomposed into the wavelet packet components and the wavelet energy rate index is computed to indicate the structural damage. It is observed that this method can be used for damage detection of this kind of structures.

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.

Structural Damage Detection of Continuous Beam by NExT Based Wavelet Packet Energy

2012 ◽  
Vol 490-495 ◽  
pp. 2588-2593
Author(s):  
Peng Yan ◽  
Qiao Li
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Decomposition Method ◽  
Wavelet Packet ◽  
Damage Index ◽  
Detection Algorithm ◽  
Reference Points ◽  
Favorable Effect ◽  
Continuous Beam ◽  
Structural Damage Detection

For the purpose of effective damage localization, combined with natural excitation technique (NExT) and wavelet packet (WP) decomposition method, a new algorithm named NExT based wavelet packet energy (WPE) damage detection algorithm was proposed for continuous beam. Finite measuring points of bridge structure response are set firstly, and then classified as reference points and response points. Calculated with each corresponding two-point, the virtual impulse response signals are taken as input data of WP decomposition method. Finally, structural damage detection is carried out by using WPE as damage index. Through a three-span continuous beam finite element model, this algorithm was discussed with respect to the applicability and effectiveness of damage detection. The analysis results reveal that, with certain robustness to noise, the proposed algorithm has favorable effect on damage interval localization. Therefore, the algorithm put forward is practical to detect damage of continuous beam.

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