scholarly journals Temperature Effects on Vibration-Based Damage Detection of a Reinforced Concrete Slab

2020 ◽  
Vol 10 (8) ◽  
pp. 2869 ◽  
Author(s):  
Zhenpeng Wang ◽  
Minshui Huang ◽  
Jianfeng Gu
Keyword(s):  
Elastic Modulus ◽  
Reinforced Concrete ◽  
Ambient Temperature ◽  
Temperature Effects ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Damage Identification ◽  
Mode Shapes ◽  
Arx Model ◽  
Rc Slab

To study the variations in modal properties of a reinforced concrete (RC) slab (such as natural frequencies, mode shapes and damping ratios) under the influence of ambient temperature, a laboratory RC slab is monitored for over a year, the simple linear regression (LR) and autoregressive with exogenous input (ARX) models between temperature and frequencies are established and validated, and a damage identification based on particle swarm optimization (PSO) is utilized to detect the assumed damage considering temperature effects. Firstly, the vibration testing is performed for one year and the variations of natural frequencies, mode shapes and damping ratios under different ambient temperatures are analyzed. The obtained results show that the change of ambient temperature causes a major change of natural frequencies, which, on the contrary, has little effect on damping ratios and modal shapes. Secondly, based on a theoretical derivation analysis of natural frequency, the models are determined from experimental data on the healthy structure, and the functional relationship between temperature and elastic modulus is obtained. Based on the monitoring data, the LR model and ARX model between structural elastic modulus and ambient temperature are acquired, which can be used as the baseline of future damage identification. Finally, the established ARX model is validated based on a PSO algorithm and new data from the assumed 5% uniform damage and 10% uniform damage are compared with the models. If the eigenfrequency exceeds the certain confidence interval of the ARX model, there is probably another cause that drives the eigenfrequency variations, such as structural damage. Based on the constructed ARX model, the assumed damage is identified accurately.

Experimental Verification of the Structural Damage Identification Method Developed for Beam Structures

2006 ◽  
Vol 326-328 ◽  
pp. 1113-1116
Author(s):  
Deokki Youn ◽  
Usik Lee ◽  
Oh Yang Kwon
Keyword(s):  
Experimental Verification ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Damage Identification ◽  
Mode Shapes ◽  
Damage State ◽  
Intact State ◽  
Identification Method ◽  
Structural Damage Identification ◽  
Cantilevered Beam

In this paper, an experimental verification has been conducted for a frequency response function (FRF)-based structural damage identification method (SDIM) proposed in the previous study [1]. The FRF-based SDIM requires the natural frequencies and mode shapes measured in the intact state and the FRF-data measured in the damaged state. Experiments are conducted for the cantilevered beam specimens with one and three slots. It is shown that the proposed FRF-based SDIM provides damage identification results that agree quite well with true damage state.

Structural Damage Identification Under Temperature Variations Based on PSO–CS Hybrid Algorithm

2019 ◽  
Vol 19 (11) ◽  
pp. 1950139 ◽  
Author(s):  
MinShui Huang ◽  
ShaoXi Cheng ◽  
HaiYang Zhang ◽  
Mustafa Gul ◽  
HaiLin Lu
Keyword(s):  
Elastic Modulus ◽  
Temperature Effects ◽  
Hybrid Algorithm ◽  
Structural Damage ◽  
Damage Identification ◽  
Cuckoo Search ◽  
Element Model ◽  
Temperature Variations ◽  
Identification Method ◽  
Better Than

Using the variations in parameters to detect structural damages has been widely used in damage identification of structures. When exposed to varying temperatures, not only the displacements and stresses of a structure will change, but also the elastic modulus of the materials, such as concrete and steel, of which the structure is made. Since the variation in elastic modulus will result in the variation of the stiffness of the structure, a damage identification method without considering the temperature effects is, in principle, unacceptable. In this study, a damage identification method using the particle swarm optimization combined with the cuckoo search (PSO–CS) under the noise and temperature environment is proposed. First, the temperature variations are combined with the elastic modulus variation for addressing the temperature effects in finite element model. Second, a PSO–CS hybrid algorithm is adopted, which applies the updated mechanism of PSO in CS. Third, objective functions comprised of different modal messages with diverse weight coefficients are constructed for the damage identification and validated by numerical analysis of a simply supported beam. The results show that the performance of the PSO–CS is better than either PSO or CS individually. Finally, the PSO–CS is applied to the damage identification of ASCE Benchmark frame, for which the results indicate a satisfactory accuracy of the effectiveness of the proposed scheme.

scholarly journals DIAGNOSTICS OF STRUCTURAL DAMAGE BASED ON THE NATURAL FREQUENCIES RATIO CHANGE

2020 ◽  
pp. 15-27
Author(s):  
Anatoliy Bovsunovsky ◽  
Cecilia Surace
Keyword(s):  
Reinforced Concrete ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Heavy Traffic ◽  
Operating Conditions ◽  
Mode Shapes ◽  
Multiple Cracks ◽  
Vibration Diagnostics ◽  
Ratio Change ◽  
Operational Factors

The problems of vibration diagnostics based on the change of natural frequencies of structures are connected with the influence of ambient and operational factors (temperature, humidity, wind, heavy traffic etc.) on the natural frequencies. In some cases, this effect is comparable with the effect of damage itself and reliable diagnostics of damage becomes problematic. To solve this problem, the use of the ratio change between natural frequencies of different mode shapes is proposed as a characteristic of damage. The study has demonstrated that this ratio is unaffected by the environmental and operational factors. Application of the proposed method is illustrated using the example of Z24 reinforced concrete bridge. As the characteristic feature of the reinforced concrete structures damage is the occurrence of multiple cracks, in the analytical model, apart from the size and location of the cracks, the possibility of several locally located cracks was taken into account.The analytical study was performed to calculate the mode shapes and natural frequencies of damaged multi-span beam-like structure. The results reveal that, in order to identify local damage of subcritical size, natural frequency data of at least four modes of vibration are necessary. The eigenfrequencies obtained experimentally in the study of the Z24 bridge were used to confirm that the change in the eigenfrequency ratio can be used to diagnose relatively small local defects in complex structures. At this the reliability of such vibration diagnostics is much higher than based on the change of natural frequencies and mode shapes, since the change in the ratio of natural frequencies does not depend on the environmental conditions and operating conditions of the structure.

scholarly journals A Novel Parallel Auto-Encoder Framework for Multi-Scale Data in Civil Structural Health Monitoring

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 112 ◽  
Author(s):  
Ruhua Wang ◽  
Ling Li ◽  
Jun Li
Keyword(s):  
Deep Learning ◽  
Dimension Reduction ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Steel Structure ◽  
Mode Shapes ◽  
Multi Scale ◽  
Training Samples ◽  
Sparsity Constraint ◽  
Deep Learning Network

In this paper, damage detection/identification for a seven-storey steel structure is investigated via using the vibration signals and deep learning techniques. Vibration characteristics, such as natural frequencies and mode shapes are captured and utilized as input for a deep learning network while the output vector represents the structural damage associated with locations. The deep auto-encoder with sparsity constraint is used for effective feature extraction for different types of signals and another deep auto-encoder is used to learn the relationship of different signals for final regression. The existing SAF model in a recent research study for the same problem processed all signals in one serial auto-encoder model. That kind of models have the following difficulties: (1) the natural frequencies and mode shapes are in different magnitude scales and it is not logical to normalize them in the same scale in building the models with training samples; (2) some frequencies and mode shapes may not be related to each other and it is not fair to use them for dimension reduction together. To tackle the above-mentioned problems for the multi-scale dataset in SHM, a novel parallel auto-encoder framework (Para-AF) is proposed in this paper. It processes the frequency signals and mode shapes separately for feature selection via dimension reduction and then combine these features together in relationship learning for regression. Furthermore, we introduce sparsity constraint in model reduction stage for performance improvement. Two experiments are conducted on performance evaluation and our results show the significant advantages of the proposed model in comparison with the existing approaches.

scholarly journals Identification of Structural Damage in Bridges Using High-Frequency Vibrational Responses

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Ivana Mekjavić
Keyword(s):  
High Frequency ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Damage Identification ◽  
Damage Model ◽  
Reinforced Concrete Beam ◽  
Computational Technique ◽  
Damage Scenarios ◽  
Identification Approach ◽  
Girder Bridge

The present research aims to develop an effective and applicable structural damage detection method. A damage identification approach using only the changes of measured natural frequencies is presented. The structural damage model is assumed to be associated with a reduction of a contribution to the element stiffness matrix equivalent to a scalar reduction of the material modulus. The computational technique used to identify the damage from the measured data is described. The performance of the proposed technique on numerically simulated real concrete girder bridge is evaluated using imposed damage scenarios. To demonstrate the applicability of the proposed method by employing experimental measured natural frequencies this technique is applied for the first time to a simply supported reinforced concrete beam statically loaded incrementally to failure. The results of the damage identification procedure show that the proposed method can accurately locate the damage and predict the extent of the damage using high-frequency (here beyond the 4th order) vibrational responses.

DAMAGE DETECTION OF RC SLABS USING NONLINEAR VIBRATION FEATURES

2009 ◽  
Vol 09 (04) ◽  
pp. 687-709 ◽  
Author(s):  
XINQUN ZHU ◽  
HONG HAO
Keyword(s):  
Reinforced Concrete ◽  
Nonlinear Vibration ◽  
Structural Damage ◽  
Concrete Structures ◽  
Dynamic Responses ◽  
Mode Shapes ◽  
Reinforced Concrete Structures ◽  
Vibration Frequencies ◽  
Skeleton Curve ◽  
Time Frequency

Studied herein are the signatures of nonlinear vibration characteristics of damaged reinforced concrete structures using the wavelet transform (WT). A two-span RC slab built in 2003 was tested to failure in the laboratory. Vibration measurements were carried out at various stages of structural damage. The vibration frequencies, mode shapes, and damping ratios at each loading stage were extracted and analyzed. It is found that the vibration frequencies are not sensitive to small damages, but are good indicators when damage is severe. The dynamic responses are also analyzed in the time–frequency domain by WT and the skeleton curve is constructed to describe the nonlinear characteristics in the reinforced concrete structures. The results show that the skeleton curves are good indicators of damage in the reinforced concrete structures because they are more sensitive to small damages than vibration frequencies.

Non-model-based damage identification of plates using measured mode shapes

2016 ◽  
Vol 16 (1) ◽  
pp. 3-23 ◽  
Author(s):  
Yongfeng Xu ◽  
Weidong Zhu
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Damage Index ◽  
Thickness Reduction ◽  
Aluminum Plate ◽  
Mode Shapes ◽  
Identification Method ◽  
Model Based

Mode shapes (MSs) have been extensively used to detect structural damage. This paper presents a new non-model-based damage identification method that uses measured MSs to identify damage in plates. A MS damage index (MSDI) is proposed to identify damage near regions with consistently high values of MSDIs associated with MSs of different modes. A MS of a pseudo-undamaged plate can be constructed for damage identification using a polynomial of a properly determined order that fits the corresponding MS of a damaged plate, if the associated undamaged plate is geometrically smooth and made of materials that have no stiffness and mass discontinuities. It is shown that comparing a MS of a damaged plate with that of a pseudo-undamaged plate is better for damage identification than with that of an undamaged plate. Effectiveness and robustness of the proposed method for identifying damage of different positions and areas are numerically investigated using different MSs; effects of crucial factors that determine effectiveness of the proposed method are also numerically investigated. Damage in the form of a machined thickness reduction area was introduced to an aluminum plate; it was successfully identified by the proposed method using measured MSs of the damaged plate.

scholarly journals Damage Identification by Using a Self-Synchronizing Multipoint Laser Doppler Vibrometer

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Chong Yang ◽  
Yu Fu ◽  
Jianmin Yuan ◽  
Min Guo ◽  
Keyu Yan ◽  
...  
Keyword(s):  
Mode Shape ◽  
Natural Frequencies ◽  
Damage Identification ◽  
Reference Beam ◽  
Laser Doppler Vibrometer ◽  
Laser Doppler ◽  
Vibration Measurement ◽  
Mode Shapes ◽  
Interference Signal ◽  
Short Period

The vibration-based damage identification method extracts the damage location and severity information from the change of modal properties, such as natural frequency and mode shape. Its performance and accuracy depends on the measurement precision. Laser Doppler vibrometer (LDV) provides a noncontact vibration measurement of high quality, but usually it can only do sampling on a single point. Scanning LDV is normally used to obtain the mode shape with a longer scanning time. In this paper, a damage detection technique is proposed using a self-synchronizing multipoint LDV. Multiple laser beams with various frequency shifts are projected on different points of the object, reflected and interfered with a common reference beam. The interference signal containing synchronized temporal vibration information of multiple spatial points is captured by a single photodetector and can be retrieved in a very short period. Experiments are conducted to measure the natural frequencies and mode shapes of pre- and postcrack cantilever beams. Mode shape curvature is calculated by numerical interpolation and windowed Fourier analysis. The results show that the artificial crack can be identified precisely from the change of natural frequencies and the difference of mode shape curvature squares.

A Flexibility-Based Method for Structural Damage Identification Using Ambient Modal Data

2009 ◽  
Vol 24 (3) ◽  
pp. 153-159 ◽  
Author(s):  
Q. W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Simulated Data ◽  
Least Square ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Vibration Modes ◽  
Sensitivity Equation ◽  
Structural Damage Identification ◽  
Normalization Factors

Structural damage identification using ambient vibration modes has become a very important research area in recent years. The main issue surrounding the use of ambient vibration modes is the mass normalization of the measured mode shapes. This paper presents a promising approach that extends the flexibility sensitivity technique to tackle the ambient vibration case. By introducing the mass normalization factors, manipulating the flexibility sensitivity equation, the unknown damage parameters and mass normalization factors can be computed simultaneously by the least-square technique. The effectiveness of the proposed method is illustrated using simulated data with measurement noise on three examples. It has been shown that the proposed procedure is simple to implement and may be useful for structural damage identification under ambient vibration case.

Damage Identification in Collocated Structural Systems Using Structural Markov Parameters

2013 ◽  
Author(s):  
Ramin Bighamian ◽  
Hamid Reza Mirdamadi ◽  
Jin-Oh Hahn
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Mode Shapes ◽  
Structural Systems ◽  
Structural System ◽  
Computationally Efficient ◽  
Markov Parameters ◽  
Novel Approach ◽  
Stiffness Matrices ◽  
Stiffness Characteristics

This paper presents a novel approach to damage identification in a class of collocated multi-input multi-output structural systems. In the proposed approach, damage is identified via the structural Markov parameters obtained from a system identification procedure, which is in turn exploited to localize and quantify damage by evaluating relative changes occurring in the mass and stiffness matrices associated with the structural system. To this aim, an explicit relationship between structural Markov parameters versus mass and stiffness matrices is developed. The main strengths of the proposed approach are that it is capable of quantitatively identifying the occurrence of multiple damages associated with both mass and stiffness characteristics in the structural system, and it is computationally efficient in that it is solely based on the structural Markov parameters but does not necessitate costly calculations related to natural frequencies and mode shapes, making it highly attractive for structural damage detection and health monitoring applications. Numerical examples are provided to demonstrate the validity and effectiveness of the proposed approach.

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