Damage Detection for Cantilever Beam Structures Using Two-Stage Method

2013 ◽  
Vol 351-352 ◽  
pp. 1084-1087
Author(s):  
Cui Hong Li ◽  
Qiu Wei Yang ◽  
Xue Shen
Keyword(s):  
Damage Detection ◽  
Cantilever Beam ◽  
Measurement Errors ◽  
Damage Identification ◽  
Static Displacement ◽  
Two Stage ◽  
Beam Structures ◽  
Static Test ◽  
Second Stage ◽  
Promising Tool

This paper presents a two-stage method for damage identification in cantilever beam structures using the incomplete measured static and dynamic paramenters. The first stage locates damages preliminary by using the static displacement changes, which is obtained by the static test of structure. It has been shown that the point from which the static displacement difference starts increasing linearly is the location of damage. After the suspected damaged elements are determined in the first stage, the first order sensitivity of the structural natural frequency is used to identify damages more precise in the second stage. The significant advantage of the proposed method is that it is economical in computation and is simple to implement. A cantilever beam structure is analyzed as a numerical example to verify the present method. Results show that the proposed method performs well even if the measurement errors inevitably make the damage assessment more difficult. It has been shown that the presented two-stage methodology may be a promising tool to be used by research groups working on experimental damage detection.

Structural Damage Detection Using Static Test Data

2014 ◽  
Vol 501-504 ◽  
pp. 852-855
Author(s):  
Cui Hong Li ◽  
Qiu Wei Yang
Keyword(s):  
Damage Detection ◽  
Measurement Errors ◽  
Structural Damage ◽  
Damage Identification ◽  
Singular Values ◽  
Beam Structure ◽  
Static Displacement ◽  
Simply Supported Beam ◽  
Static Test ◽  
Simply Supported

This paper presents a static-based method for damage identification in the simply supported beam structure using the incomplete measured static displacement parameters. The presented method makes use of the singular value decomposition of structural static displacement change, which is obtained by the static test of structure. It has been shown that structural damage can be detected by the number of the non-zero singular values of the static displacement change. The significant advantage of the proposed method is that it is economical in computation and is simple to implement. A simply supported beam structure is analyzed as a numerical example to verify the present method. Results show that the proposed method performs well even if the measurement errors inevitably make the damage assessment more difficult. It has been shown that the presented static-based methodology may be a promising tool to be used by research groups working on experimental damage detection.

Damage Identification for Truss Structures Using Eigenvectors

2013 ◽  
Vol 753-755 ◽  
pp. 2351-2355
Author(s):  
Wei Min Jin ◽  
Qiu Wei Yang ◽  
Xue Shen ◽  
Fang Jun Lu
Keyword(s):  
Measurement Errors ◽  
Damage Assessment ◽  
Structural Damage ◽  
Damage Identification ◽  
Truss Structures ◽  
Inner Product ◽  
Structural Element ◽  
First Order ◽  
Second Stage ◽  
Promising Tool

This paper presents a two-stage structural damage identification method using the incomplete measured modal parameters. The first stage locates damages preliminary by using the generalized energy change of each structural element, which is defined as the inner product of the mode shape with the elemental stiffness connectivity vector. After the suspected damaged elements are determined in the first stage, the first order sensitivity of the structural eigenvector is used to identify damages more precise in the second stage. The significant advantage of the proposed method is that it is economical in computation and is simple to implement. A truss structure is analyzed as a numerical example to verify the present method. Results show that the proposed method performs well even if the measurement errors inevitably make the damage assessment more difficult. It has been shown that the presented methodology may be a promising tool to be used by research groups working on experimental damage localization.

Research on Structural Damage Diagnosis Based on Strain Modal

2013 ◽  
Vol 438-439 ◽  
pp. 739-742
Author(s):  
Yi Na Zhang ◽  
Lei Cao
Keyword(s):  
Damage Detection ◽  
Cantilever Beam ◽  
Theoretical Basis ◽  
Structural Damage ◽  
Damage Identification ◽  
Damage Diagnosis ◽  
Strain Mode ◽  
Engineering Structure ◽  
Displacement Mode ◽  
Analysis Theory

The damage diagnosis theory and method of engineering structure is one of the hot issues concerned by the engineering circles at present. Based on the strain modal analysis theory, it expounds the connection among displacement mode, strain mode and curvature mode, with a heavy rubber as the material to make a cantilever beam, and establishing the different damage conditions of the cantilever beam, studying about dynamic structural damage identification under the incentive, which provides the theoretical basis and technical support for the research on damage detection of large engineering structure.

scholarly journals A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2366
Author(s):  
Zhifeng Wu ◽  
Bin Huang ◽  
Kong Fah Tee ◽  
Weidong Zhang
Keyword(s):  
Measurement Errors ◽  
Damage Identification ◽  
Measurement Data ◽  
Beam Structures ◽  
Analysis Algorithm ◽  
Static Measurement ◽  
Homotopy Analysis ◽  
Identification Approach ◽  
Stochastic Damage ◽  
Modelling Error

This paper proposes a new damage identification approach for beam structures with stochastic parameters based on uncertain static measurement data. This new approach considers not only the static measurement errors, but also the modelling error of the initial beam structures as random quantities, and can also address static damage identification problems with relatively large uncertainties. First, the stochastic damage identification equations with respect to the damage indexes were established. On this basis, a new homotopy analysis algorithm was used to solve the stochastic damage identification equations. During the process of solution, a static condensation technique and a L1 regularization method were employed to address the limited measurement data and ill-posed problems, respectively. Furthermore, the definition of damage probability index is presented to evaluate the possibility of existing damages. The results of two numerical examples show that the accuracy and efficiency of the proposed damage identification approach are good. In comparison to the first-order perturbation method, the proposed method can ensure better accuracy in damage identification with relatively large measurement errors and modelling error. Finally, according to the static tests of a simply supported concrete beam, the proposed method successfully identified the damage of the beam.

A Two-Stage Scheme for Plate Damage Identification Based on Lock-in Thermography and Dynamic Analysis

2013 ◽  
Vol 569-570 ◽  
pp. 839-846
Author(s):  
Hai Yang Gao ◽  
Xing Lin Guo ◽  
Pei Jun Hou ◽  
Cheng Wei Wu ◽  
Hua Jiang Ouyang
Keyword(s):  
Dynamic Analysis ◽  
Surrogate Model ◽  
Damage Identification ◽  
Two Stage ◽  
Damage Level ◽  
Second Stage ◽  
Damage Quantification ◽  
Stage Scheme ◽  
Lock In ◽  
Plate Type

This paper presents a two-stage scheme of damage identification for plate-type structure. In the first stage, probable damaged regions and their relative severities can be detected based on lock-in thermography technique. In the second stage, the relation between the damage level and its corresponding natural frequencies of the plate is constructed by means of Kriging surrogate model based on dynamic analysis. The inverse problem of damage quantification over the surrogate model is then solved by using a robust stochastic particle swarm optimization algorithm. Experimental study on a double-damaged plate demonstrates the feasibility and effectiveness of the proposed scheme.

Two-Stage Damage Identification Based on Modal Strain Energy and Revised Particle Swarm Optimization

2014 ◽  
Vol 14 (05) ◽  
pp. 1440005 ◽  
Author(s):  
Sheng-Lan Ma ◽  
Shao-Fei Jiang ◽  
Liu-Qing Weng
Keyword(s):  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Damage Detection ◽  
Strain Energy ◽  
Particle Swarm ◽  
Noise Tolerance ◽  
Two Stage ◽  
Modal Strain Energy ◽  
Swarm Optimization ◽  
Second Stage

This paper presents a novel two-stage damage detection method by integrating modal strain energy and revised particle swarm optimization (RPSO). In the first stage, the modal strain energy change ratio (MSECR) is used to roughly identify the locations of damaged elements via an appropriate MSECR threshold which is determined through parameter estimation. In the second stage, RPSO that integrates evolutionary theory with general PSO is used to precisely locate and quantify the damage with the gravity position of the selected excellent particles in the current entire population taken into consideration. Two numerical simulations and a seven-story steel frame experiment in laboratory conditions are performed to validate the proposed method, and a comparison is made between the proposed approach and existing methods. The results show that: (1) the proposed method can not only effectively locate damage, but also accurately evaluate the extent of damage. Meanwhile, it also enjoys good noise-tolerance and adaptability; (2) the damage threshold of the MSECR presented in this paper can be determined by the parameter estimation and reliability index, and then used to reduce the number of elements to be analyzed and to improve the computation efficiency in the second stage; and (3) compared with general PSO algorithm, RPSO is more efficient and robust for damage detection with a better noise-tolerance. This study shows that the proposed method can provide a reliable and fast tool to accurately identify, locate and quantify single- and multi-damage of complex engineering structures.

A Virtual Load Method for Damage Identification of Beam Structures

2018 ◽  
Vol 12 (2) ◽  
pp. 117-126 ◽  
Author(s):  
C.H. Li ◽  
Q.W. Yang ◽  
B.X. Sun ◽  
C.F. Liang
Keyword(s):  
Damage Identification ◽  
Beam Structures

An Enhanced Two Stage MMSE Equalizer for Coded FBMC/OQAM Systems

2019 ◽  
Vol 10 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Mohammad Rizk Assaf ◽  
Abdel-Nasser Assimi
Keyword(s):  
Error Propagation ◽  
Channel Model ◽  
Error Correcting Codes ◽  
Two Stage ◽  
Probability Of Error ◽  
Second Stage ◽  
Different Types ◽  
Mmse Equalizer ◽  
And Performance ◽  
Ici Cancellation

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

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.

Personalised attraction recommendation for enhancing topic diversity and accuracy

2021 ◽  
pp. 016555152199980
Author(s):  
Yuanyuan Lin ◽  
Chao Huang ◽  
Wei Yao ◽  
Yifei Shao
Keyword(s):  
Real World ◽  
Information Overload ◽  
Two Stage ◽  
Misclassification Cost ◽  
Second Stage ◽  
Low Visibility ◽  
Recommendation Diversity ◽  
Optimisation Model ◽  
Definition Of ◽  
Improved Methods

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

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