Structural Nonlinear Damage Detection Method Using AR/ARCH Model

2017 ◽  
Vol 17 (08) ◽  
pp. 1750083 ◽  
Author(s):  
J. J. Cheng ◽  
H. Y. Guo ◽  
Y. S. Wang
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Fatigue Cracks ◽  
Arch Model ◽  
Structure Model ◽  
Relevant Research ◽  
Engineering Structures ◽  
The Past ◽  
Damage Indicator ◽  
Shear Building

Structural health monitoring (SHM) has received increasing attention in the research community over the past two decades. Most of the relevant research focuses on linear structural damage detection. However, the majority of the damage in civil engineering structures is nonlinear, such as fatigue cracks that open and close under dynamic loading. In this study, a new hybrid AR/ARCH model in the field of economics and a proposed damage indicator (DI) which is the second-order variance indicator (SOVI) based on the model have been used for detecting structural nonlinear damage. The data from an experimental three-storey structure and a simulated eight-storey shear building structure model have been used to verify the effectiveness of the algorithm and SOVI. In addition, a traditional linear DI: cepstral metric indicator (CMI) has also been used to diagnose the nonlinear damage. The results of the CMI and SOVI were compared and it is found that there are advantages in using the SOVI in the field of nonlinear structural damage.

Structural Damage Detection Using Curvature Mode Difference Curve

2011 ◽  
Vol 250-253 ◽  
pp. 1248-1251 ◽  
Author(s):  
Hang Jing ◽  
Ling Ling Jia ◽  
Yi Zhao
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Numerical Differentiation ◽  
Engineering Structures ◽  
System Parameters ◽  
Numerical Studies ◽  
Damage Indicator ◽  
Structural Damage Identification ◽  
Changing Rate

Damage detection in civil engineering structures using the dynamic system parameters has become an important area of research. The sensitivity of damage indicator is of great value to structural damage identification. The curvature mode is an excellent parameter in damage detection of structures, while in case that certain curvature mode curve can’t show existence of damage. In this paper, numerical studies are conducted to demonstrate the deficiency of curvature mode to damage detection. Then a new damage indicator called “curvature mode changing rate” (CMCR) is introduced which is processed by numerical differentiation of curvature mode curve. The simulation results show that the new index is superior to curvature mode for structural damage identification, and it is still sensitive to the damaged location in the mode node.

Study on the Sensitive Factors of Structural Nonlinear Damage Based on the Innovation Series

2020 ◽  
Vol 20 (10) ◽  
pp. 2042011
Author(s):  
Liujie Chen ◽  
Yahui Mei ◽  
Jiyang Fu ◽  
Ching Tai Ng ◽  
Zhen Cui
Keyword(s):  
Standard Deviation ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Mean Squared Error ◽  
Ar Model ◽  
Arch Model ◽  
Residual Series ◽  
Auto Regressive ◽  
Shear Building

Constructing a damage-sensitive factor (DSF) is one of the key steps in structural damage detection. In this paper, innovation series extracted from the auto-regressive conditional heteroscedasticity (ARCH) model are proposed to construct a DSF, which is defined as the standard deviation of innovation (SDI). A three-story shear building structure is used to demonstrate and verify the performance of the proposed method, and the results are compared with the standard deviation of the residuals (SDR) based on an auto-regressive (AR) model. In the proposed method, the AR model is established using the acceleration responses obtained from the reference and test states. The residual series are then extracted for fitting the SDR. Subsequently, the ARCH model is constructed based on the residual series from the AR model, and a new DSF of SDI is defined. This study focuses on analyzing the accuracy of fitting AR model and ARCH model to vibration response data via the normal probability distribution, and identifying the characteristics of the residual and innovation series. The mean squared error (MSE) is used as the loss function to calculate the loss on residual and innovation series from the AR model and ARCH model, respectively. The results demonstrate that the SDR can be used for nonlinear damage detection. However, the proposed SDI can provide more accurate nonlinear damage identification and is robust to varying environmental condition and small damages. Thus, the innovation series developed based on ARCH model are promising for expressing and constructing nonlinear DSFs.

A Vibration-Based Structural Damage Detection Method and its Applications to Engineering Structures

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Iterative Algorithm ◽  
Structural Damage ◽  
Detection Method ◽  
New Physics ◽  
Logistic Function ◽  
Frame Structure ◽  
Engineering Structures ◽  
System Equations ◽  
Extent Of Damage

Two major challenges associated with a vibration-based damage detection method using changes in natural frequencies are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistic function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using the Levenberg-Marquardt method is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. It is applied to various engineering structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation, and the locations and extent of damage can be successfully detected in experimental damage detection.

scholarly journals Monitoring of Changes in Bridge Response Using Weigh-In-Motion Systems

2013 ◽  
Vol 569-570 ◽  
pp. 183-190
Author(s):  
Daniel Cantero ◽  
Arturo González ◽  
Biswajit Basu
Keyword(s):  
Structural Damage ◽  
Element Model ◽  
Traffic Loading ◽  
Damage Scenarios ◽  
The Road ◽  
The Past ◽  
Road Pavement ◽  
Damage Indicator ◽  
Weigh In Motion ◽  
Bridge Weigh In Motion

Weigh-In-Motion (WIM) and Bridge Weigh-In-Motion (B-WIM) are systems that allow obtaining the axle weights of road vehicles in motion, at normal traffic speeds. While WIM employs sensors embedded in the road pavement, B-WIM use the strain recordings of a bridge to infer the traversing vehicle axle weights. Both systems have been heavily improved over the past decades, and commercial versions are currently in operation. The two main applications of these systems are: (1) to assess the traffic loading on the infrastructure, and (2) to enforce the maximum weight limits. This paper suggests a novel application of these two systems to identify changes in bridge stiffness. It requires the bridge to be instrumented with a B-WIM system and a WIM system nearby. The principle is to use both systems to evaluate the gross weight of vehicles passing over the bridge and correlate their predictions. Changes in correlation of the predicted axle weights over time will indicate either structural damage or faulty sensor. A finite element model of a coupled vehicle-bridge system with different damage scenarios is used to test the approach numerically. Vehicle mechanical properties and speeds are randomly sampled within a Monte Carlo simulation. Results show how correlation changes as damage increases and how this correlation can be employed as a damage indicator.

Active Detection of Structural Damage in Aluminum Alloy Using Magneto-Elastic Active Sensors (MEAS)

2011 ◽  
Author(s):  
David Conrad ◽  
Andrei Zagrai
Keyword(s):  
Aluminum Alloy ◽  
Damage Detection ◽  
Elastic Waves ◽  
Structural Damage ◽  
Fatigue Cracks ◽  
Plate Thickness ◽  
Detection Methods ◽  
Thin Plates ◽  
Active Sensors ◽  
Host Structure

Many structural damage detection methods utilize piezoelectric sensors. While these sensors are efficient in supporting many structural health monitoring (SHM) methodologies, there are a few key disadvantages limiting their use. The disadvantages include the brittle nature of piezoceramics and their dependence of diagnostic results on the quality of the adhesive used in bonding the sensors. One viable alternative is the utilization of Magneto-Elastic Active Sensors (MEAS). Instead of mechanically creating elastic waves, MEAS induce eddy currents in the host structure which, along with an applied magnetic field, generate mechanical waves via the Lorentz force interaction. Since elastic waves are generated electromagnetically, MEAS do not require direct bonding to the host structure and its elements are not as fragile as PWAS. This work explores the capability of MEAS to detect damage in aluminum alloy. In particular, methodologies of detecting fatigue cracks in thin plates were explored. Specimens consisted of two identical aluminum plates featuring a machined slot to create a stress riser for crack formation. One specimen was subjected to cyclic fatigue load. MEAS were used to transmit elastic waves of different characteristics in order to explore several SHM methodologies. Experiments have shown that the introduction of fatigue cracks created measurable amplitude changes in the waves passing through the fatigued region of the aluminum plate. The phase indicated sensitivity to load conditions, but manifestation in the cracked region lacked stability. Nonlinear effects were studied using plate thickness resonance, which revealed birefringence due to local stresses at the site of the fatigue crack. The resonance spectrum has also shown a frequency decrease apparently due to stiffness loss. Preliminary results suggest opportunities for fatigue damage detection using MEAS. Application of MEAS for the diagnosis of complex structures is currently being investigated.

scholarly journals Use of Bispectrum Analysis to Inspect the Non-Linear Dynamic Characteristics of Beam-Type Structures Containing a Breathing Crack

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1177
Author(s):  
Li Cui ◽  
Hao Xu ◽  
Jing Ge ◽  
Maosen Cao ◽  
Yangmin Xu ◽  
...  
Keyword(s):  
Damage Detection ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Damage Identification ◽  
Crack Depth ◽  
Excitation Frequency ◽  
Breathing Crack ◽  
Engineering Structures ◽  
Linear Dynamic ◽  
Non Linear

A breathing crack is a typical form of structural damage attributed to long-term dynamic loads acting on engineering structures. Traditional linear damage identification methods suffer from the loss of valuable information when structural responses are essentially non-linear. To deal with this issue, bispectrum analysis is employed to study the non-linear dynamic characteristics of a beam structure containing a breathing crack, from the perspective of numerical simulation and experimental validation. A finite element model of a cantilever beam is built with contact elements to simulate a breathing crack. The effects of crack depth and location, excitation frequency and magnitude, and measurement noise on the non-linear behavior of the beam are studied systematically. The result demonstrates that bispectral analysis can effectively identify non-linear damage in different states with strong noise immunity. Compared with existing methods, the bispectral non-linear analysis can efficiently extract non-linear features of a breathing crack, and it can overcome the limitations of existing linear damage detection methods used for non-linear damage detection. This study’s outcome provides a theoretical basis and a paradigm for damage identification in cracked structures.

scholarly journals Signal Acquisition from Piezoelectric Transducers for Impedance-Based Damage Detection

Proceedings ◽  
2017 ◽  
Vol 2 (3) ◽  
pp. 130 ◽  
Author(s):  
Danilo Budoya ◽  
Fabricio Baptista
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Electrical Impedance ◽  
Correct Diagnosis ◽  
Damage Index ◽  
Impedance Measurement ◽  
Experimental Tests ◽  
Piezoelectric Transducers ◽  
Signal Acquisition ◽  
Engineering Structures

Damage detection in structural health monitoring (SHM) using piezoelectric transducers has received attention in recent decades for increasing safety and reducing maintenance costs of various types of engineering structures. Among the various methods to detect structural damage, the impedance-based method performs the measurement of the electrical impedance of piezoelectric transducers attached in the monitored structure, which is related to the mechanical properties of the structure due to the piezoelectric effect. Therefore, the impedance measurement is critical to ensure the correct diagnosis of the structure and this paper presents an analysis of the main techniques of signal acquisition from piezoelectric transducers that have been proposed in the literature to replace the conventional impedance analyzers. Experimental tests were carried out with a piezoelectric transducer attached to an aluminum bar and the acquisition techniques were analyzed and compared regarding the precision and sensitivity to damage. The analysis was performed using the real part of the impedance signatures and a basic damage index based on the correlation coefficient. The results indicate that the signal acquisition techniques have important differences regarding the precision and sensitivity to structural damage that should be considered in the development of impedance-based SHM systems.

Development of Civil Engineering Structural Damage Diagnosis

2013 ◽  
Vol 671-674 ◽  
pp. 2029-2031
Author(s):  
De Yu Huang
Keyword(s):  
Damage Detection ◽  
Hot Spots ◽  
International Research ◽  
Structural Damage ◽  
Civil Engineering ◽  
Structural Damage Detection ◽  
Traditional Methods ◽  
Engineering Structures ◽  
Damage Diagnosis ◽  
Dynamic Methods

Damage diagnosis of civil engineering structures has become one of the hot spots of the current international research in the field of Civil Engineering.This article describes the tasks and objectives of structural damage detection in civil engineering,systematically expounded the civil engineering structural damage diagnosis describes the traditional methods of structural damage diagnosis, static methods and dynamic methods, and evaluated their respective advantages and disadvantages.Finally, the study made several suggestions and Prospects for structural damage detection.

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