scholarly journals Frequency Contour-Strip Method for Characterization of Damage in Structures under Noisy Conditions

2021 ◽  
Vol 11 (23) ◽  
pp. 11479
Author(s):  
Jiayi Peng ◽  
Hao Xu ◽  
Hailei Jia ◽  
Dragoslav Sumarac ◽  
Tongfa Deng ◽  
...  
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Contour Line ◽  
Crack Identification ◽  
Dynamic Feature ◽  
Strip Method ◽  
Line Method ◽  
Beam Type ◽  
Noisy Conditions ◽  
Eigen Frequency

Eigen-frequency, compared with mode shape and damping, is a more practical and reliable dynamic feature to portray structural damage. The frequency contour-line method relying on this feature is a representative method to identify damage in beam-type structures. Although this method has been increasingly applied in the area of damage identification, it has two significant deficiencies: inefficiency in establishing the eigen-frequency panorama; and incompetence to identify cracks in noisy conditions, considerably impairing the effectiveness in identifying structural damage. To overcome these deficiencies, a novel method, termed the frequency contour-strip method, is developed for the first time. This method is derived by extending the frequency contour line of 1D to frequency contour strip of 2D. The advantages of the frequency contour-strip method are twofold: (i) it uses the isosurface function to instantly produce the eigen-frequency panorama with a computational efficiency several orders of magnitude higher than that of the frequency contour-line method; and (ii) it can accommodate the effect of random noise on damage identification, thereby thoroughly overcoming the deficiencies of the frequency contour-line method. With these merits, the frequency contour-strip method can characterize damage in beam-type structures with more efficiency, greater accuracy, and stronger robustness against noise. The proof of concept of the proposed method is performed on an analytical model of a Timoshenko beam bearing a crack and the effectiveness of the method is experimentally validated via crack identification in a steel beam.

scholarly journals A Super-Harmonic Feature Based Updating Method for Crack Identification in Rotors Using a Kriging Surrogate Model

2019 ◽  
Vol 9 (12) ◽  
pp. 2428 ◽  
Author(s):  
Zhiwen Lu ◽  
Yong Lv ◽  
Huajiang Ouyang
Keyword(s):  
Surrogate Model ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Gaussian White Noise ◽  
Crack Identification ◽  
Breathing Crack ◽  
Kriging Surrogate Model ◽  
Nonlinear Characteristics ◽  
Practical Applications

Dynamic model updating based on finite element method (FEM) has been widely investigated for structural damage identification, especially for static structures. Despite the substantial advances in this method, the key issue still needs to be addressed to boost its efficiency in practical applications. This paper introduces the updating idea into crack identification for rotating rotors, which has been rarely addressed in the literature. To address the problem, a novel Kriging surrogate model-based FEM updating method is proposed for the breathing crack identification of rotors by using the super-harmonic nonlinear characteristics. In this method, the breathing crack induced nonlinear characteristics from two locations of the rotors are harnessed instead of the traditional linear damage features for more sensitive and accurate breathing crack identification. Moreover, a FEM of a two-disc rotor-bearing system with a response-dependent breathing crack is established, which is partly validated by experiments. In addition, the associated breathing crack induced nonlinear characteristics are investigated and used to construct the objective function of Kriging surrogate model. Finally, the feasibility and the effectiveness of the proposed method are verified by numerical experiments with Gaussian white noise contamination. Results demonstrate that the proposed method is effective, accurate, and robust for breathing crack identification in rotors and is promising for practical engineering applications.

scholarly journals Research on Damage Identification of Nonuniform Microcrack in Beam Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Jia Guo ◽  
Deqing Guan ◽  
Yanran Pan
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Calculation Method ◽  
Structural Damage ◽  
Damage Identification ◽  
Wavelet Coefficient ◽  
Particle Swarm ◽  
Crack Identification ◽  
Swarm Optimization ◽  
Damage Location

Nonuniform microcrack identification is of great significance in mechanical, aerospace, and civil engineering. In this study, the nonuniform crack is simplified as a semielliptical crack, and simplified calculation methods are proposed for damage severity and damage identification of semielliptical cracks. The proposed methods are based on the calculation method for uniform cracks. The wavelet transform and the intelligent algorithm (IA) are used to identify the damage location and the damage severity of the structure, respectively. The singularity of the wavelet coefficient can be used to identify the signal singularity quickly and accurately, and IA efficiently and accurately calculates the structural damage severity. The particle swarm optimization (PSO) algorithm and the genetic algorithm (GA), widely used, are applied to identify the damage severity of the beam. Numerical simulations and experimental analyses of beams with transfixion and semielliptical cracks are carried out to evaluate the accuracy of the semielliptical crack calculation method and the method of wavelet analysis combined with PSO and GA for nonuniform crack identification. The results show that the wavelet-particle swarm optimization (WPSO) and the wavelet-genetic algorithm (WGA) can accurately and efficiently identify the structural semielliptical damage location and severity and that these methods are not easily influenced by noise. The damage severity calculation method for semielliptical cracks can accurately calculate the semielliptical size and can be used to identify damage in beams with semielliptical cracks.

On Wavelets-Based Holder Exponents for Clamped-Clamped Beams Crack Identification

2011 ◽  
Vol 94-96 ◽  
pp. 381-387 ◽  
Author(s):  
Run Bo Bai ◽  
Hai Hong Xu ◽  
Xin Xin Zhang
Keyword(s):  
Structural Damage ◽  
Comprehensive Analysis ◽  
Mode Shapes ◽  
Crack Identification ◽  
Structural Damage Detection ◽  
Hölder Exponent ◽  
Beam Type ◽  
Clamped Beams ◽  
Hölder Exponents ◽  
Different Order

Structural damage detection by the Holder exponent receives much attention recently. Many investigations have been successfully applied to the crack identification, especially for the beam-type structures. However, a comprehensive analysis of the Holder exponent has been absent. Result in some conclusions had been drawn are unilateral. In this paper, the mode shapes of the clamped-clamped beams are analytical studied and a program calculating the Holder exponents of the mode shape signals with different damages is compiled with MATLAB. By comprehensively studying the Holder exponents of the clamped-clamped beams with cracks of different sizes, locations, and different order modes, a new phenomenon that the values of the Holder exponent vary with different locations of the crack is detected. The results also show that the Holder exponent decreases with the increase of the mode number. However, there are not obvious relations between the Holder exponent and the order of the mode for the whole beam locations.

scholarly journals Structural Damage Identification Using a Modified Directional Bat Algorithm

2021 ◽  
Vol 11 (14) ◽  
pp. 6507
Author(s):  
Yonghui Su ◽  
Lijun Liu ◽  
Ying Lei
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Bat Algorithm ◽  
Maximum Relative Error ◽  
Accurate Identification ◽  
Population Number ◽  
Structural Damage Identification ◽  
Beam Type

Bat algorithm (BA) has been widely used to solve optimization problems in different fields. However, there are still some shortcomings of standard BA, such as premature convergence and lack of diversity. To solve this problem, a modified directional bat algorithm (MDBA) is proposed in this paper. Based on the directional bat algorithm (DBA), the individual optimal updating mechanism is employed to update a bat’s position by using its own optimal solution. Then, an elimination strategy is introduced to increase the diversity of the population, in which individuals with poor fitness values are eliminated, and new individuals are randomly generated. The proposed algorithm is applied to the structural damage identification and to an objective function composed of the actual modal information and the calculated modal information. Finally, the proposed MDBA is used to solve the damage detection of a beam-type bridge and a truss-type bridge, and the results are compared with those of other swarm intelligence algorithms and other variants of BA. The results show that in the case of the same small population number and few iterations, MDBA has more accurate identification and better convergence than other algorithms. Moreover, the study on anti-noise performance of the MDBA shows that the maximum relative error is only 5.64% at 5% noise level in the beam-type bridge, and 6.53% at 3% noise in the truss-type bridge, which shows good robustness.

Experimental investigation of damage identification in beam structures based on the strain statistical moment

2016 ◽  
Vol 20 (5) ◽  
pp. 747-758 ◽  
Author(s):  
Dansheng Wang ◽  
Zhen Chen ◽  
Wei Xiang ◽  
Hongping Zhu
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Gaussian White Noise ◽  
Statistical Moment ◽  
Least Square ◽  
Detection Technique ◽  
Before And After ◽  
Beam Type ◽  
Strain Responses

A new two-step damage detection technique based on the fourth strain statistical moment was recently proposed by the authors, and its sensitivity to local structural damage has been numerically demonstrated for beam-type structures. In this article, the proposed method is extended to an experimental beam to assess its feasibility and practicality. A simply supported steel beam was manufactured and subjected to Gaussian white-noise excitation before and after damage. The strain responses of each measurement point were recorded based on which fourth strain statistical moments were calculated. The proposed two-step technique was implemented to locate the damaged elements of the experimental beam, for which the damage sizes were identified based on the least-square updating algorithm. The experimental results show that the proposed fourth strain statistical moment index and the two-step damage detection technique are effective and feasible for beam-type structures.

Research on Sheet Crack Identification of Frame Structure Using Wavelet Analysis

2011 ◽  
Vol 71-78 ◽  
pp. 4074-4077
Author(s):  
De Qing Guan ◽  
Xiao Lin Zhong ◽  
Hong Wei Ying
Keyword(s):  
Finite Element ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Structural Damage ◽  
Damage Identification ◽  
Frame Structure ◽  
Crack Identification ◽  
Wavelet Coefficients ◽  
Strain Mode ◽  
Plane Frame

This research presented the damage identification problem of frame structure using the wavelet transform of strain mode. Solving strain modal parameters of plane frames with cracks by means of the finite element theory, applying the gauss2 wavelet transform to analyze the stain mode of plane frame, and denoising the wavelet coefficients of the strain mode by db3 wavelet, then the location of crack of the plane frame could be identified by the maximum of wavelet coefficients after denoising. Taking one-layer plane frame as an example, this research gave the finite element model of framework with sheet crack (non-through surface crack and internal crack), calculated the strain mode of the structure, and identified the location of cracks by wavelet analysis of strain mode. Results show that this method is able to identify the damage of frame structure. Numerical calculation shows that the approach is effective. This paper provides a valuable reference of structural damage identification and diagnosis in engineering applications.

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.

Sign in / Sign up

Export Citation Format

Share Document