2511 Damage detection method in non-destructive inspection using topology optimization

As an important load-bearing component, steel wire ropes (WRs) are widely used in complex systems such as mine hoists, cranes, ropeways, elevators, oil rigs, and cable-stayed bridges. Non-destructive damage detection for WRs is an important way to assess damage states to guarantee WR’s reliability and safety. With intelligent sensors, signal processing, and pattern recognition technology developing rapidly, this field has made great progress. However, there is a lack of a systematic review on technologies or methods introduced and employed, as well as research summaries and prospects in recent years. In order to bridge this gap, and to promote the development of non-destructive detection technology for WRs, we present an overview of non-destructive damage detection research of WRs and discuss the core issues on this topic in this paper. First, the WRs’ damage type is introduced, and its causes are explained. Then, we summarize several main non-destructive detection methods for WRs, including electromagnetic detection method, optical detection method, ultrasonic guided wave detection method, and acoustic emission detection method. Finally, a prospect is put forward. Based on the review of papers, we provide insight about the future of the non-destructive damage detection methods for steel WRs to a certain extent.

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Genetic algorithms-based parameter optimization of a non-destructive damage detection method

Proceedings of the Thirty-Fourth Southeastern Symposium on System Theory (Cat. No.02EX540) ◽

10.1109/ssst.2002.1027024 ◽

2003 ◽

Cited By ~ 2

Author(s):

E.S. Sazonov ◽

P. Klinkhachorn ◽

U.B. Halabe

Keyword(s):

Genetic Algorithms ◽

Damage Detection ◽

Parameter Optimization ◽

Detection Method ◽

Non Destructive

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Mode Shape-Based Damage Detection Method (MSDI): Experimental Validation

Applied Sciences ◽

10.3390/app11104589 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4589

Author(s):

Ivan Duvnjak ◽

Domagoj Damjanović ◽

Marko Bartolac ◽

Ana Skender

Keyword(s):

Boundary Conditions ◽

Damage Detection ◽

Mode Shape ◽

Experimental Validation ◽

Detection Method ◽

Dynamic Properties ◽

Damage Index ◽

Main Principle ◽

The Difference ◽

Different Levels

The main principle of vibration-based damage detection in structures is to interpret the changes in dynamic properties of the structure as indicators of damage. In this study, the mode shape damage index (MSDI) method was used to identify discrete damages in plate-like structures. This damage index is based on the difference between modified modal displacements in the undamaged and damaged state of the structure. In order to assess the advantages and limitations of the proposed algorithm, we performed experimental modal analysis on a reinforced concrete (RC) plate under 10 different damage cases. The MSDI values were calculated through considering single and/or multiple damage locations, different levels of damage, and boundary conditions. The experimental results confirmed that the MSDI method can be used to detect the existence of damage, identify single and/or multiple damage locations, and estimate damage severity in the case of single discrete damage.

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Elimination of outlier measurements for damage detection of structures under changing environmental conditions

Structural Health Monitoring ◽

10.1177/1475921721998476 ◽

2021 ◽

pp. 147592172199847

Author(s):

William Soo Lon Wah ◽

Yining Xia

Keyword(s):

Damage Detection ◽

Multiple Regression ◽

Natural Frequencies ◽

Detection Method ◽

Detection Methods ◽

Structure Model ◽

Bridge Structure ◽

Beam Structure ◽

Dependent Variables ◽

The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

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Fast Non-Destructive Detection of Wool Content in Blended Fabrics Based on Near-Infrared Spectroscopy Technology

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.671.356 ◽

2015 ◽

Vol 671 ◽

pp. 356-362 ◽

Cited By ~ 1

Author(s):

Zhi Feng Chen ◽

Yuan Quan Hong ◽

Chang Jiang Wan ◽

Lian Ying Zhao

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Detection Method ◽

Quantitative Model ◽

National Standard ◽

Fast Detection ◽

Significant Difference ◽

Validation Set ◽

Non Destructive

A fast non-destructive method of detection of wool content in blended fabrics was studied based on Near Infrared spectroscopy technology in order to avoid the time-consuming, tedious work and the destruction of samples in the traditional inspection. 621 wool/nylon, wool/polyester and wool/nylon/polyester blended fabrics were taken as research objects. To get the wool content, we established the wool near-infrared quantitative model by partial least squares (PLS) method after analyzing the color and composition of the samples. For verifying the validity and practicability of the model, 100 samples were chosen as an independent validation set. The variance analysis shows that there is no significant difference between Near Infrared fast detection method and national standard method (GB/T2910-2009),which indicates that this method is expected to be a means of fast non-destructive detection and will have extensive application future in the field of wool content detection.

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Structural Steel Plate Damage Detection using Non Destructive Testing, Frame Energy based Statistical Features and Artificial Neural Networks

Procedia Engineering ◽

10.1016/j.proeng.2013.02.049 ◽

2013 ◽

Vol 53 ◽

pp. 376-386 ◽

Cited By ~ 8

Author(s):

M.P. Paulraj ◽

Sazali Yaacob ◽

M.S. Abdul Majid ◽

Mohd Nor Fakhzan Mohd Kazim ◽

Pranesh Krishnan

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Damage Detection ◽

Structural Steel ◽

Steel Plate ◽

Statistical Features ◽

Non Destructive Testing ◽

Destructive Testing ◽

Artificial Neural ◽

Non Destructive

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Damage detection method for shear buildings using the changes in the first mode shape slopes

Computers & Structures ◽

10.1016/j.compstruc.2011.02.014 ◽

2011 ◽

Vol 89 (9-10) ◽

pp. 733-743 ◽

Cited By ~ 44

Author(s):

Hongping Zhu ◽

Lin Li ◽

Xiao-Qiao He

Keyword(s):

Damage Detection ◽

Mode Shape ◽

Detection Method ◽

Shear Buildings

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Study on Damage Detection of Bridge Based on Wavelet Multi-Scale Analysis

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.639-640.1010 ◽

2013 ◽

Vol 639-640 ◽

pp. 1010-1014 ◽

Cited By ~ 1

Author(s):

Ke Ding ◽

Ting Peng Chen

Keyword(s):

Wavelet Transform ◽

Damage Detection ◽

Detection Method ◽

Mode Shapes ◽

Scale Analysis ◽

Multi Scale ◽

Damage Location ◽

Transform Coefficients ◽

Beam Bridge ◽

Multi Scale Analysis

The damage detection method based on wavelet multi-scale analysis is presented in the paper. The damage location can be identified by analyzing the multi-scale wavelet transform coefficients of curvatures of mode shapes. The extreme value of wavelet transform coefficients indicates the damage location. But it is difficult to detect the location of defect if the defect is near to the equilibrium position of vibration. In order to solve this problem, we put forward a method which is to add the wavelet transform coefficients of multi modals together. The method can effectively overcome the above problem. Three damage situations of simply supported beam bridge are discussed in the paper. The results show that the peaks of wavelet transform coefficients indicate the damage location of structural. It is possible to pinpoint the damage location based on wavelet multi-scale analysis on curvatures of mode shapes.

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