Spectral indicators in structural damage identification: A case study

1999 ◽  
Vol 213 (4) ◽  
pp. 411-415 ◽  
Author(s):  
J. A. Brandon ◽  
A. E. Stephens ◽  
E. M. O. Lopes ◽  
A. S. K. Kwan
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Vibration Signal ◽  
Open Crack ◽  
Severe Damage ◽  
Closed Crack ◽  
Spectral Signatures ◽  
Linear Behaviour ◽  
Systematic Effects

A pre-loaded cracked cantilever beam was excited vising a random vibration signal. Excitation levels were within the range of amplitudes that caused no suspicion of non-linear behaviour in an undamaged specimen of identical dimensions and material. Spectral signatures were acquired which made it possible to discriminate between open crack, closed crack and breathing conditions. Systematic effects relating to variations in resonant frequency were largely consistent with the literature for a lightly damaged beam but were unsupported for a beam with more severe damage.

scholarly journals Assessing Structural Damage after a Severe Wildfire: A Case Study

Buildings ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 171
Author(s):  
Angeliki Papalou ◽  
Dimitrios K. Baros
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Temperature Distribution ◽  
Structural Damage ◽  
Extreme Heat ◽  
The Finite Element Method ◽  
Residential Areas ◽  
Severe Damage ◽  
Construction Type

Wildfires have always been a threat to forests and areas of high combustible vegetation. When they are not kept under control, they can spread to residential areas, creating severe damage and destruction. This paper examines the effects of the extreme heat conditions that developed during a wildfire on buildings as a function of their construction type. One of the deadliest wildfires in Greece (July 2018) is considered as a case study, and the damage that occurred to buildings during this event is presented. The temperature of the various structural subsystems in extreme heat conditions was estimated using the finite element method. Parameters that influenced the corresponding temperature distribution were identified. Simple guidelines are given to prevent or reduce damage in buildings exposed to wildfires.

Damage Identification for Beam Structure Based on Correlation Dimension

2012 ◽  
Vol 193-194 ◽  
pp. 1342-1345
Author(s):  
Mao Jiang ◽  
Ling Zhou ◽  
Ying Tao Li ◽  
Hai Qing Zhou ◽  
Jun Shao
Keyword(s):  
Structural Damage ◽  
Correlation Dimension ◽  
Damage Identification ◽  
Fractal Theory ◽  
Vibration Signal ◽  
Structural Vibration ◽  
Damage Analysis ◽  
Beam Structure ◽  
Damage Degree ◽  
System Output

In order to explore the effective damage identification method for structure, the structural vibration signal is directly correlation dimension analyzed according to fractal theory, and structural damage is identified by measuring the singularity in system output, then the method for structural damage identification based on correlation dimension of vibration response is proposed. The damage analysis results of a simply supported beam demonstrate that, the proposed method can accurately detect single and multi different degree damage’s location of beam structure, and alteration of correlation dimension will increase along with the damage degree

Optimal Sensor Placement Algorithm for Structural Damage Identification

2020 ◽  
Vol 14 (1) ◽  
pp. 69-81
Author(s):  
C.H. Li ◽  
Q.W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Sensor Placement ◽  
Optimization Procedure ◽  
Frame Structure ◽  
Truss Structures ◽  
Optimal Sensor Placement ◽  
Structural Damage Identification ◽  
Placement Algorithm ◽  
Sensor Locations

Background: Structural damage identification is a very important subject in the field of civil, mechanical and aerospace engineering according to recent patents. Optimal sensor placement is one of the key problems to be solved in structural damage identification. Methods: This paper presents a simple and convenient algorithm for optimizing sensor locations for structural damage identification. Unlike other algorithms found in the published papers, the optimization procedure of sensor placement is divided into two stages. The first stage is to determine the key parts in the whole structure by their contribution to the global flexibility perturbation. The second stage is to place sensors on the nodes associated with those key parts for monitoring possible damage more efficiently. With the sensor locations determined by the proposed optimization process, structural damage can be readily identified by using the incomplete modes yielded from these optimized sensor measurements. In addition, an Improved Ridge Estimate (IRE) technique is proposed in this study to effectively resist the data errors due to modal truncation and measurement noise. Two truss structures and a frame structure are used as examples to demonstrate the feasibility and efficiency of the presented algorithm. Results: From the numerical results, structural damages can be successfully detected by the proposed method using the partial modes yielded by the optimal measurement with 5% noise level. Conclusion: It has been shown that the proposed method is simple to implement and effective for structural damage identification.

Sparse damage detection via the elastic net method using modal data

2021 ◽  
pp. 147592172110219
Author(s):  
Rongrong Hou ◽  
Xiaoyou Wang ◽  
Yong Xia
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Measurement Data ◽  
Elastic Net ◽  
Sensitivity Matrix ◽  
Regularization Technique ◽  
Modal Data ◽  
Regularization Techniques ◽  
Net Method

The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice the independency criteria of the l1 regularization technique. This study employs the elastic net method to solve the problem by combining the l1 and l2 regularization techniques. Moreover, the proposed method enables the grouped structural damage being identified simultaneously, whereas the l1 regularization cannot. A numerical cantilever beam and an experimental three-story frame are utilized to demonstrate the effectiveness of the proposed method. The results showed that the proposed method is able to accurately locate and quantify the single and multiple damages, even when the number of measurement data is much less than the number of elements. In particular, the present elastic net technique can detect the grouped damaged elements accurately, whilst the l1 regularization method cannot.

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