scholarly journals Beam Damage Detection Under a Moving Load Using Random Decrement Technique and Savitzky–Golay Filter

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 243 ◽  
Author(s):  
Hadi Kordestani ◽  
Chunwei Zhang ◽  
Mahdi Shadabfar
Keyword(s):  
Damage Detection ◽  
Moving Load ◽  
Damage Index ◽  
Velocity Variation ◽  
Simply Supported Beam ◽  
Damage Scenarios ◽  
Simply Supported ◽  
Random Decrement Technique ◽  
Random Decrement ◽  
Output Only

In this paper, a two-stage time-domain output-only damage detection method is proposed with a new energy-based damage index. In the first stage, the random decrement technique (RDT) is employed to calculate the random decrement signatures (RDSs) from the acceleration responses of a simply supported beam subjected to a moving load. The RDSs are then filtered using the Savitzky–Golay filter (SGF) in the second stage. Next, the filtered RDSs are processed by the proposed energy-based damage index to locate and quantify the intensity of the possible damage. Finally, by fitting a Gaussian curve to the damage index resulted from the non-damage conditions, the whole process is systematically implemented as a baseline-free method. The proposed method is numerically verified using a simply supported beam under moving sprung mass with different velocities and damage scenarios. The results show that the proposed method can accurately estimate the damage location/quantification from the acceleration data without any prior knowledge of either input load or damage characteristics. Additionally, the proposed method is neither sensitive to noise nor velocity variation, which makes it ideal when obtaining a constant velocity is difficult.

scholarly journals Direct Use of the Savitzky–Golay Filter to Develop an Output-Only Trend Line-Based Damage Detection Method

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1983 ◽  
Author(s):  
Hadi Kordestani ◽  
Chunwei Zhang
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Moving Load ◽  
Velocity Variation ◽  
Trend Line ◽  
Damage Scenarios ◽  
Acceleration Data ◽  
Before And After ◽  
Output Only ◽  
Direct Use

The Savitzky–Golay filter (SGF) is a time-domain technique that determines a trend line for a signal. The direct application of SGF for damage localization and quantification is investigated in this paper. Therefore, a single-stage trend line-based damage detection method employing SGF is proposed in which the damage is located and quantified at the bridge under moving load. A simply supported beam under moving sprung mass is numerically simulated to verify the proposed method. Four different velocities and five different single- and multi-damage scenarios are considered. The acceleration data along the beam are obtained, manually polluted with noise and their trend lines are then determined using SGF. The results show that the proposed method can accurately locate and quantify the damage using these trend lines. It is proved that the proposed method is insensitive to the noise and velocity variation in which having a constant velocity is a hard task before and after damage. Additionally, defining a normalization factor and fitting a Gaussian curve to this factor provide an estimation for the baseline and therefore, it categorizes the proposed method as baseline-free method.

scholarly journals Application of the Random Decrement Technique in Damage Detection under Moving Load

2018 ◽  
Vol 8 (5) ◽  
pp. 753 ◽  
Author(s):  
Hadi Kordestani ◽  
Yi-Qiang Xiang ◽  
Xiao-Wei Ye ◽  
Ya-Kun Jia
Keyword(s):  
Damage Detection ◽  
Moving Load ◽  
Random Decrement Technique ◽  
Random Decrement

Numerical Studies on Wavelet-Based Crack Detection Based on Velocity Response of a Beam Subjecting to Moving Load

2013 ◽  
Vol 569-570 ◽  
pp. 854-859 ◽  
Author(s):  
Wei Wei Zhang ◽  
Jia Geng ◽  
Zi Long Zhao ◽  
Zhi Hua Wang
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Crack Detection ◽  
Moving Load ◽  
Noise Tolerance ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Damage Location ◽  
Numerical Studies ◽  
Velocity Response

In this paper, the possibility and validity of damage detection based on velocity response of a simply supported beam under the moving load are examined theoretically and numerically. It includes the following parts: First, the theoretic background of the beam vibration subjecting to moving load is briefly described. And then, the velocity responses of a simple supported beam are calculated by software Ansys. Using wavelet transform, the damage location can be identified successfully. At last, the effects of noise and load speed are discussed in detail. Numerical studies show the validity of the proposed method and a good noise tolerance using the velocity response.

Structural Damage Assessment Using Output-Only Measurement: Localization and Quantification

2013 ◽  
Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao
Keyword(s):  
Damage Detection ◽  
Damage Assessment ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Null Space ◽  
Singular Spectrum Analysis ◽  
Damage Index ◽  
Computation Efficiency ◽  
Output Only

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.

Damage Detection Using Piezoelectrics Modal Analysis and PSD Technique

2000 ◽  
Author(s):  
Sauro Liberatore ◽  
Gregory P. Carman
Keyword(s):  
Theoretical Model ◽  
Damage Detection ◽  
State Space Model ◽  
Piezoelectric Sensor ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Power Spectral ◽  
Frequency Changes ◽  
Set Up ◽  
Aluminum Beam

Abstract A damage detection method has been implemented on a simply supported beam structure. The method is developed with both a theoretical model and experimental results. The simply supported beam contains one piezoelectric actuator and one piezoelectric sensor. The theoretical model was obtained from an energy formulation and a Rayleigh-Ritz approach. Matrices were composed in a State Space model to reproduce the input-output system between actuator and sensor. The damage was modeled with material properties variations. The experimental set up consisted of an aluminum beam with damage introduced by adding different weights in various locations. The dynamic changes produced were investigated and compared with theoretical prediction with reasonable agreement obtained. In order to quantify the size of damage, Power Spectral Density approach was used. To locate damage, frequency changes were used.

Bridge Damage Detection Using Quasi-Static Component of Moving Vehicle-Induced Dynamic Response

2020 ◽  
pp. 2042001
Author(s):  
Zhiwei Chen ◽  
Yigui Zhou ◽  
Wen-Yu He ◽  
Mengqi Liu
Keyword(s):  
Dynamic Response ◽  
Damage Detection ◽  
Detection Method ◽  
Damage Index ◽  
Frequency Component ◽  
Critical Signal ◽  
Moving Vehicle ◽  
Damage Scenarios ◽  
Static Component ◽  
Bridge Damage

The critical signal component extracted from the bridge response caused by a moving vehicle is normally used to construct damage index for damage detection. The dynamic response of bridges subjected to moving vehicle includes several components, among which the quasi-static component reflects the inherent characteristics of the bridge. In view of this, this paper presents a bridge damage detection method based on quasi-static component of the moving vehicle-induced dynamic response. First, damage-induced changes of the natural-frequency component, moving-frequency component and quasi-static component responses are investigated via a simply-supported beam bridge. The quasi-static component response is proved to be less sensitive to the moving velocity of the load and more suitable for damage detection. Subsequently, a quasi-static component response extraction method is proposed based on analytical mode decomposition (AMD) and moving average filter (MAF). The extracted quasi-static component response is further employed to localize and quantify damages. Finally, numerical simulations are conducted to examine the feasibility, accuracy and advantages of the proposed damage detection method. The results indicated that the proposed method performs well in different damage scenarios and is insensitive to the moving velocity of the load and road roughness.

Research on Curvature Mode Characteristics of Damaged Simply Supported Beam

2013 ◽  
Vol 455 ◽  
pp. 261-266 ◽  
Author(s):  
Xin Shang ◽  
Yue Xu ◽  
Geng Feng Ren
Keyword(s):  
Numerical Simulation ◽  
Simulation Analysis ◽  
Unit Length ◽  
Damage Index ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Difference Curve ◽  
Mode Characteristics ◽  
Mode Order ◽  
Beam Damage

This paper approaches the rules of curvature mode and curvature mode difference about a simply supported beam. On the basis of the theory of curvature mode, through numerical simulation analysis of simply supported beam on four conditions, the result of simply supported beam with curvature mode and curvature mode difference were obtained. The results show that for the damaged beam information with numerical simulation, the curvature mode and curvature mode difference index calculated by difference method at the unit length unevenly is with strong noise, which can even submerge the beam damage information, and for different damage index of the beam, damage information from curvature mode difference curve is stronger and effected by unit length weaker than those from curvature mode curve, and damage information from curvature mode curve and curvature mode difference curve decrease with the increasing mode order.

Correlation-Based Damage Identification and Quantification Using Modal Kinetic Energy Change

2020 ◽  
Vol 20 (10) ◽  
pp. 2042007
Author(s):  
J. T. Joseph ◽  
T. H. T. Chan ◽  
K.-D. Nguyen
Keyword(s):  
Kinetic Energy ◽  
Damage Detection ◽  
Damage Identification ◽  
Numerical Study ◽  
Traditional Approach ◽  
Mass Change ◽  
Algorithm Optimization ◽  
Damage Scenarios ◽  
Simply Supported ◽  
Modal Properties

Many existing damage identification or quantification methods can be employed only if the internal and external mass changes are negligible when tested at two different states of a structure. This paper presents a new Modal Kinetic Energy (MKE)-based method to detect and quantify damage using modal properties of structures, which can be employed even in situations when mass change is not more than a certain extent. A new damage sensitivity parameter has been developed using measured modal characteristics of baseline structure. The MKE change (MKEC) concept is then employed to locate damage and to estimate relative perturbation at each element. The relative damage extent vector is estimated by searching the best correlation between the analytical and experimental MKEC vectors with the help of genetic algorithm optimization tool. The extent of damage is calculated after computing damage scaling coefficient using measured eigenvalue change vector. A numerical study is carried out on a simply supported single span beam to confirm its performance under various test conditions. The robustness of the proposed MKE method and the significance of mass variation in the damage detection approach are evaluated by comparing the damage quantification results with a traditional approach. Finally, the proposed damage detection method is applied on a two-span simply supported beam for single and multiple damage scenarios by extracting the modal properties experimentally. The results revealed that the proposed approach is capable of detecting and estimating single and multiple damages with reasonable accuracy even in moderate noise contaminated and mass change environments.

scholarly journals Damage detection of beam bridge under a moving load using Auto-encoder

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Juntao Wu ◽  
Zhenhua Nie
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Structural Damage ◽  
Moving Load ◽  
Damage Index ◽  
Structural Vibration ◽  
Vibration Data ◽  
Vibration Responses ◽  
Hidden Layer ◽  
The Time Domain

A novel damage detection approach based on Auto-encoder neural network is proposed to identify damage in beam-like bridges subjected to a moving mass. In this approach, several sensors are used to measure structural vibration responses during a mass moving across the bridge. An auto-encoder (AE) neural network is designed to extract features from the measured responses. A fixed moving window is used to cut out the time-domain responses to generate inputs of the AE neural network. Moreover, some constraints are applied on the hidden layer to improve the performance of the AE network in training process. When the training is complete, the encoder was regarded as a feature extractor. And the damage index is defined as the cosine distance between two feature vectors obtained from adjacent data windows. By moving the window along the measured vibration data, we can calculate a damage index series and locate the damage position of the structure. To demonstrate the performance of the proposed method, numerical simulation is carried out. The results show that the proposed method can accurately locate both single and multiple damages using acceleration response. It infers the proposed method is promising for structural damage detection.

A New Damage Index Using FRF Data, 2D-PCA Method and Pattern Recognition Techniques

2017 ◽  
Vol 17 (08) ◽  
pp. 1750090 ◽  
Author(s):  
F. Khoshnoudian ◽  
S. Talaei
Keyword(s):  
Pattern Recognition ◽  
Damage Detection ◽  
Damage Identification ◽  
Damage Index ◽  
Principal Component ◽  
Frame Structure ◽  
Damage Scenarios ◽  
Pattern Recognition Techniques ◽  
Damage Indices ◽  
Truss Bridge

A pattern recognition-based damage detection method using a brand-new damage index (DI) obtained from the frequency response function (FRF) data is proposed in this paper. One major issue of using the FRF data is the large size of input variables. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices by applying a data reduction technique called the two-dimensional principal component analysis (2D-PCA). The proposed damage indices can be used as the unique patterns. After introducing the damage indices, a dataset of damage scenarios and related patterns is composed. Pattern recognition techniques such as the artificial neural networks and look-up-table (LUT) method are employed to find the most similar known DI to the unknown DI obtained for the damaged structure. As the result of this procedure, the actual damage location and severity can be determined. In this paper, the 2D-PCA and LUT method for damage detection is introduced for the first time. The damage identification of a truss bridge and a two-story frame structure is performed for verification of the proposed method, considering all single damage cases as well as many multiple damage scenarios. In addition, the robustness of the proposed algorithm to measurement noise was investigated by polluting the FRF data with 5%, 10%, 15% and 20% noises.

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