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 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.

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.

Interpolation Damage Detection Method on a Suspension Bridge Model: Influence of Sensors Disturbances

2013 ◽  
Vol 569-570 ◽  
pp. 734-741 ◽  
Author(s):  
Marco Domaneschi ◽  
Maria Pina Limongelli ◽  
Luca Martinelli
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Suspension Bridge ◽  
Longitudinal Axis ◽  
Noise Signal ◽  
Damage Scenarios ◽  
Spatially Correlated ◽  
Bridge Model ◽  
Structural Responses ◽  
Detection And Localization

In this paper the IDDM (Interpolation Damage Detection Method), recently proposed as a speedy damage detection and localization technique, is applied to the numerical model of a cable suspended bridge derived from the ANSYS model of the Shimotsui-Seto Bridge in Japan (940m length of the main span). The wind excitation is simulated as a spatially correlated process acting in the horizontal direction, transversal to the deck. The bridge is assumed to be monitored by sensors located at the nodes of the model along the longitudinal axis, and recording the absolute acceleration of the bridge deck in the transversal direction Noise in recorded responses can reduce the sensitivity of the method to damage. The influence of noise on the results of the damage detection method is herein investigated by adding a white-noise signal to the structural responses. The mutual relationship between level of noise, intensity of damage and lengths of recorded signals is also investigated with reference to various damage scenarios.

scholarly journals Mode Shape-Based Damage Detection Method (MSDI): Experimental Validation

2021 ◽  
Vol 11 (10) ◽  
pp. 4589
Author(s):  
Ivan Duvnjak ◽  
Domagoj Damjanović ◽  
Marko Bartolac ◽  
Ana Skender
Keyword(s):  
Boundary Conditions ◽  
Damage Detection ◽  
Mode Shape ◽  
Experimental Validation ◽  
Detection Method ◽  
Dynamic Properties ◽  
Damage Index ◽  
Main Principle ◽  
The Difference ◽  
Different Levels

The main principle of vibration-based damage detection in structures is to interpret the changes in dynamic properties of the structure as indicators of damage. In this study, the mode shape damage index (MSDI) method was used to identify discrete damages in plate-like structures. This damage index is based on the difference between modified modal displacements in the undamaged and damaged state of the structure. In order to assess the advantages and limitations of the proposed algorithm, we performed experimental modal analysis on a reinforced concrete (RC) plate under 10 different damage cases. The MSDI values were calculated through considering single and/or multiple damage locations, different levels of damage, and boundary conditions. The experimental results confirmed that the MSDI method can be used to detect the existence of damage, identify single and/or multiple damage locations, and estimate damage severity in the case of single discrete damage.

Elimination of outlier measurements for damage detection of structures under changing environmental conditions

2021 ◽  
pp. 147592172199847
Author(s):  
William Soo Lon Wah ◽  
Yining Xia
Keyword(s):  
Damage Detection ◽  
Multiple Regression ◽  
Natural Frequencies ◽  
Detection Method ◽  
Detection Methods ◽  
Structure Model ◽  
Bridge Structure ◽  
Beam Structure ◽  
Dependent Variables ◽  
The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

scholarly journals Monitoring Master Swimmers’ Performance and Active Drag Evolution along a Training Mesocycle

2021 ◽  
Vol 18 (7) ◽  
pp. 3569
Author(s):  
Henrique P. Neiva ◽  
Ricardo J. Fernandes ◽  
Ricardo Cardoso ◽  
Daniel A. Marinho ◽  
J. Arturo Abraldes
Keyword(s):  
Aerobic Training ◽  
Training Period ◽  
Velocity Variation ◽  
Hydrodynamic Drag ◽  
Swimming Training ◽  
Front Crawl ◽  
Maximal Intensity ◽  
Before And After ◽  
Active Drag

This study aimed to analyze the effects of a swimming training mesocycle in master swimmers’ performance and active drag. Twenty-two 39.87 ± 6.10 year-old master swimmers performed a 25 m front crawl at maximal intensity before and after a typical four-week training mesocycle. Maximum, mean and minimum speeds, speed decrease and hip horizontal intra-cyclic velocity variation were assessed using an electromechanical speedometer, and the active drag and power to overcome drag were determined using the measuring active drag system. Maximum, mean and minimum front crawl speeds improved from pre- to post-training (mean ± 95% CI: 3.1 ± 2.8%, p = 0.04; 2.9 ± 1.6%, p = 0.01; and 4.6 ± 3.1%, p = 0.01; respectively) and the speed decrease along the 25 m test lowered after the training period (82.5 ± 76.3%, p = 0.01). The training mesocycle caused a reduction in the active drag at speeds corresponding to 70% (5.0 ± 3.9%), 80% (5.6 ± 4.0%), and 90% (5.9 ± 4.0%), but not at 100% (5.9 ± 6.7%), of the swimmers’ maximal exertions in the 25 m test. These results showed that four weeks of predominantly aerobic training could improve master swimmers’ performance and reduce their hydrodynamic drag while swimming mainly at submaximal speeds.

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.

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