Damage Detection of Steel Beam Using Frequency Response Function Measurement Data and Fractal Dimension

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Eun-Taik Lee ◽  
Hee-Chang Eun
Keyword(s):  
Fractal Dimension ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Measurement Data ◽  
Fractal Dimensions ◽  
Dynamic Responses ◽  
Steel Beam ◽  
Health State ◽  
Measured Frequency Response

Fractal-dimension-based signal processing has been extensively applied to various fields for nondestructive testing. The dynamic response signal can be utilized as an analytical tool to evaluate the structural health state without baseline data. The fractal features of the dynamic responses with fractal dimensions (FDs) were investigated using the Higuchi, Katz, and Sevcik methods. The waveform FD proposed by these methods was extracted from the measured frequency response function (FRF) data in the frequency domain. Damage was observed within this region, which resulted in an abrupt change in the curvature of the FD. The effectiveness of the methods was investigated via the results of a steel beam test and a numerical experiment to detect damage.

Structural Damage Identification Based on Strain Frequency Response Functions

2018 ◽  
Vol 18 (12) ◽  
pp. 1850159 ◽  
Author(s):  
Fariba Shadan ◽  
Faramarz Khoshnoudian ◽  
Akbar Esfandiari
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Model Updating ◽  
Measurement Data ◽  
Sensitivity Equation ◽  
Strain Frequency

Damage identification using the sensitivity of the dynamic characteristics of the structure of concern has been studied considerably. Among the dynamic characteristics used to locate and quantify structural damages, the frequency response function (FRF) data has the advantage of avoiding modal analysis errors. Additionally, previous studies demonstrated that strains are more sensitive to localized damages compared to displacements. So, in this study, the strain frequency response function (SFRF) data is utilized to identify structural damages using a sensitivity-based model updating approach. A pseudo-linear sensitivity equation which removes the adverse effects of incomplete measurement data is proposed. The approximation used for the sensitivity equation utilizes measured natural frequencies to reconstruct the unmeasured SFRFs. Moreover, new approaches are proposed for selecting the excitation and measurement locations for effective model updating. The efficiency of the proposed method is validated numerically through 2D truss and frame examples using incomplete and noise polluted SFRF data. Results indicate that the method can be used to accurately locate and quantify the severity of damage.

scholarly journals Dynamic characterizations of underwater structures using noncontact vibration tests based on nanosecond laser ablation in water: evaluation of passive vibration suppression with damping materials

2017 ◽  
Vol 24 (16) ◽  
pp. 3714-3725 ◽  
Author(s):  
Naoki Hosoya ◽  
Itsuro Kajiwara ◽  
Koh Umenai ◽  
Shingo Maeda
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Vibration Suppression ◽  
Pass Filter ◽  
Reliability Factor ◽  
Measured Frequency ◽  
Measured Frequency Response ◽  
Underwater Structure ◽  
Underwater Structures

Recently, the demand for higher performing underwater structures under diverse conditions has increased. Examples include improved precision and speed of the position control of robot manipulators. To prevent the control spillover problems when active controls are used, a control system is typically constituted with a low-pass filter to eliminate all modes except for the target modes. However, experimentally measuring the dynamic properties of an underwater structure in an environment where the structure and a fluid continuously influence each other is difficult. We have recently proposed a noncontact vibration testing method for dynamic characterizations of underwater structures in which the response to a laser ablation excitation force is measured by laser Doppler vibrometer. Integrating passive control using a vibration-damping material affixed onto the underwater structure and active control constituted with the low-pass filter may realize a more cost-effective system. To develop this combined control into a practical method, the reliability of the measured frequency response function must be validated. Additionally, the applicable frequency range must be expanded to encompass the high-frequency region (several tens of kHz) so that the vibration suppression quality of underwater structures can be evaluated. Herein we quantify the effect of random measurement errors on the measured frequency response function with a reliability factor based on the concept of coherence functions. Using the measured frequency response function with a reliability factor, we demonstrated that our method can evaluate passive vibration suppression effect of an underwater structure with a damping material in high-frequency ranges up to 20 kHz.

scholarly journals Damage Identification for Underground Structure Based on Frequency Response Function

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3033 ◽  
Author(s):  
Shengnan Wang ◽  
Xiaohong Long ◽  
Hui Luo ◽  
Hongping Zhu
Keyword(s):  
Frequency Response ◽  
Modal Analysis ◽  
Response Function ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Underground Structure ◽  
Measurement Data ◽  
Scale Model ◽  
Design Parameters

Damage identification that is based on modal analysis is widely used in traditional structural damage identification. However, modal analysis is difficult in high damping structures and modal concentrated structures. Unlike approaches based on modal analysis, damage identification based on the frequency response function allows for the avoidance of error and easy verification through other test points. An updating algorithm is devised is this study by utilizing the frequency response function together with the dynamic reduction with respect to the selected design parameters. Numerical results indicate that the method can be used to define multiple parameters with large variation and incomplete measurement data and is robust against measurement noise. With the purpose of avoiding the occurrence of resonance and gaining additional information, the trial and error method has been used to choose a proper frequency. Furthermore, an experimental scale model in a soil box is subjected to the excitation of moving load to validate the effectiveness of the damage identification approach. The improved damage identification method for underground structures, which is based on the analysis of the frequency response function, can be adopted as an efficient and functional damage identification tool.

Secondary Path Estimation by PCA-Compressed Frequency Response Function in Active Vibration Control

2011 ◽  
Vol 66-68 ◽  
pp. 721-726
Author(s):  
Xin Hui Li ◽  
Tie Jun Yang ◽  
Jian Chao Dong ◽  
Ze Qi Lu
Keyword(s):  
Vibration Control ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Active Vibration Control ◽  
Principal Component ◽  
Good Control ◽  
Noise Elimination ◽  
Measured Frequency Response ◽  
Active Vibration

The FXLMS algorithm is widely used in active vibration control system. The estimation of secondary path plays very important roles in such a system. This paper presents an experimental investigation of effective secondary path estimation in active vibration control using measured Frequency Response Function (FRF). Principal component analysis (PCA) is pursued to the measured FRF for noise elimination, and then the PCA-compressed FRF data are used for secondary path estimation. The control results indicate that the proposed method has good control performance.

scholarly journals Road Roughness Estimation Based on the Vehicle Frequency Response Function

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 89
Author(s):  
Qingxia Zhang ◽  
Jilin Hou ◽  
Zhongdong Duan ◽  
Łukasz Jankowski ◽  
Xiaoyang Hu
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Gaussian White Noise ◽  
Estimation Method ◽  
Time Shift ◽  
Ride Quality ◽  
The Road ◽  
Road Roughness ◽  
Measured Response

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

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