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 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.

Statistics-Based Noise Analysis for Vibration-Based Damage Identification

2006 ◽  
Author(s):  
L. Yu ◽  
T. Yin ◽  
H. P. Zhu
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Perturbation Technique ◽  
Random Perturbation ◽  
Noise Analysis ◽  
Detection Methods ◽  
Mode Shapes ◽  
Composite Function ◽  
Analysis Technique

As the vibration-based structural damage detection methods are easily affected by the environmental noise, a novel noise analysis method is proposed based on the statistics in this paper together with the Monte Carlo technique for assessing the influence of experimental noise of modal data on sensitivity-based damage detection methods. Different from the commonly used random perturbation technique, the proposed technique is deduced directly by the Moore–Penrose generalized inverse of sensitivity matrix under the differential quotient rule of composite function. It can not only make the analysis process more effective but also analyze the noise influence on both frequencies and mode shapes in a similar way. Furthermore, an improved modal sensitivity based damage detection method is also proposed and compared with other two commonly used sensitivity-based methods in this paper. A one-story portal frame is adopted to evaluate the efficiency of both the proposed noise analysis technique and the improved modal sensitivity based method. The assessment results show that the proposed statistics-based noise analysis technique is effective and more suitable for the vibration-based damage identification. The improved modal sensitivity based method is more robust to noise than the other commonly used sensitivity-based methods.

FEM Free Damage Detection of Beam Structures Using the Deflections Estimated by Modal Flexibility Matrix

2021 ◽  
pp. 2150128
Author(s):  
Wen-Yu He ◽  
Wei-Xin Ren ◽  
Lei Cao ◽  
Quan Wang
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Index ◽  
Element Model ◽  
Mode Shapes ◽  
Beam Structures ◽  
Flexibility Matrix ◽  
Damage Quantification ◽  
Modal Flexibility ◽  
The Cost

The deflection of the beam estimated from modal flexibility matrix (MFM) indirectly is used in structural damage detection due to the fact that deflection is less sensitive to experimental noise than the element in MFM. However, the requirement for mass-normalized mode shapes (MMSs) with a high spatial resolution and the difficulty in damage quantification restricts the practicability of MFM-based deflection damage detection. A damage detection method using the deflections estimated from MFM is proposed for beam structures. The MMSs of beams are identified by using a parked vehicle. The MFM is then formulated to estimate the positive-bending-inspection-load (PBIL) caused deflection. The change of deflection curvature (CDC) is defined as a damage index to localize damage. The relationship between the damage severity and the deflection curvatures is further investigated and a damage quantification approach is proposed accordingly. Numerical and experimental examples indicated that the presented approach can detect damages with adequate accuracy at the cost of limited number of sensors. No finite element model (FEM) is required during the whole detection process.

scholarly journals UAV-BASED STRUCTURAL DAMAGE MAPPING – RESULTS FROM 6 YEARS OF RESEARCH IN TWO EUROPEAN PROJECTS

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 187-194 ◽  
Author(s):  
N. Kerle ◽  
F. Nex ◽  
D. Duarte ◽  
A. Vetrivel
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Point Cloud ◽  
Feature Fusion ◽  
Texture Features ◽  
Mobile App ◽  
Detection Methods ◽  
Support Vector ◽  
3D Point Cloud ◽  
Damage Mapping

<p><strong>Abstract.</strong> Structural disaster damage detection and characterisation is one of the oldest remote sensing challenges, and the utility of virtually every type of active and passive sensor deployed on various air- and spaceborne platforms has been assessed. The proliferation and growing sophistication of UAV in recent years has opened up many new opportunities for damage mapping, due to the high spatial resolution, the resulting stereo images and derivatives, and the flexibility of the platform. We have addressed the problem in the context of two European research projects, RECONASS and INACHUS. In this paper we synthesize and evaluate the progress of 6 years of research focused on advanced image analysis that was driven by progress in computer vision, photogrammetry and machine learning, but also by constraints imposed by the needs of first responder and other civil protection end users. The projects focused on damage to individual buildings caused by seismic activity but also explosions, and our work centred on the processing of 3D point cloud information acquired from stereo imagery. Initially focusing on the development of both supervised and unsupervised damage detection methods built on advanced texture features and basic classifiers such as Support Vector Machine and Random Forest, the work moved on to the use of deep learning. In particular the coupling of image-derived features and 3D point cloud information in a Convolutional Neural Network (CNN) proved successful in detecting also subtle damage features. In addition to the detection of standard rubble and debris, CNN-based methods were developed to detect typical façade damage indicators, such as cracks and spalling, including with a focus on multi-temporal and multi-scale feature fusion. We further developed a processing pipeline and mobile app to facilitate near-real time damage mapping. The solutions were tested in a number of pilot experiments and evaluated by a variety of stakeholders.</p>

L1 Regularized Model Updating for Structural Damage Detection

2018 ◽  
Vol 18 (12) ◽  
pp. 1850157 ◽  
Author(s):  
Yu-Han Wu ◽  
Xiao-Qing Zhou
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Model Updating ◽  
Regularization Parameter ◽  
Structural Vibration ◽  
Mode Shapes ◽  
Modal Data ◽  
Vibration Data ◽  
Stiffness Reduction ◽  
Regularized Model

Model updating methods based on structural vibration data have been developed and applied to detecting structural damages in civil engineering. Compared with the large number of elements in the entire structure of interest, the number of damaged elements which are represented by the stiffness reduction is usually small. However, the widely used [Formula: see text] regularized model updating is unable to detect the sparse feature of the damage in a structure. In this paper, the [Formula: see text] regularized model updating based on the sparse recovery theory is developed to detect structural damage. Two different criteria are considered, namely, the frequencies and the combination of frequencies and mode shapes. In addition, a one-step model updating approach is used in which the measured modal data before and after the occurrence of damage will be compared directly and an accurate analytical model is not needed. A selection method for the [Formula: see text] regularization parameter is also developed. An experimental cantilever beam is used to demonstrate the effectiveness of the proposed method. The results show that the [Formula: see text] regularization approach can be successfully used to detect the sparse damaged elements using the first six modal data, whereas the [Formula: see text] counterpart cannot. The influence of the measurement quantity on the damage detection results is also studied.

Vibration-Based Damage Detection Techniques for Health Monitoring of Construction of a Multi-Storey Building

2018 ◽  
Vol 931 ◽  
pp. 178-183 ◽  
Author(s):  
Yuriy Y. Shatilov ◽  
Alexander A. Lyapin
Keyword(s):  
Damage Detection ◽  
Damage Index ◽  
The State ◽  
Diagnostic Methods ◽  
Detection Methods ◽  
Mode Shapes ◽  
Dynamic Parameters ◽  
Labor Costs ◽  
Detection Techniques ◽  
Storey Building

Conducting surveys of multi-storey buildings is a laborious task, because large volumes of visual and instrumental research should be carried out. Reduction of labor costs with an increase in the reliability of information about the state of damage and technical condition is an actual scientific and practical task. One of the ways to solve it is to use non-destructive vibration diagnostic methods. The purpose of carrying out diagnostics with the use of vibration based damage detection methods is to search for damages in structural elements that can cause the deviation of the dynamic parameters of a structure from calculated ones. Determination of the dynamic parameters of the structure, in particular natural frequencies and mode shapes of mechanical systems, is one of the most important tasks that allows obtaining integral information about the state of a structure. This article presents the results of calculations for the localization of slabs defects in a multi-storey building with a transverse crack, span L = 4.5 (m), height H = 0.2 (m), with prestressed reinforcement d = 0.05 (m). Vibration based Damage Index method was used to localize the defect. During the study, reliable localization values of the defect area of the slab were obtained, this indicates that the vibration method for determining the damage index with a sufficient degree of accuracy allowed predicting the site of damage to the structure.

Sign in / Sign up

Export Citation Format

Share Document