scholarly journals Structural Damage Detection and Health Monitoring

2019 ◽  
Vol 9 (19) ◽  
pp. 4027 ◽  
Author(s):  
Gangbing Song ◽  
Siu Chun Michael Ho ◽  
Qingzhao Kong
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Smart Home ◽  
Structural Damage Detection ◽  
Standard Inclusion

Readers who have recently visited or purchased a newly built house may have started to notice the standard inclusion of “smart home” technologies [...]

Piezoelectric sensor–based damage progression in concrete through serial/parallel multi-sensing technique

2019 ◽  
Vol 19 (2) ◽  
pp. 339-356 ◽  
Author(s):  
Balamonica K ◽  
Jothi Saravanan T ◽  
Bharathi Priya C ◽  
Gopalakrishnan N
Keyword(s):  
Damage Detection ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Structural Damage ◽  
Data Retrieval ◽  
Lead Zirconate ◽  
Structural Damage Detection ◽  
Retrieval Process ◽  
Zirconate Titanate ◽  
In Series

Structural damage detection using unmanned Structural Health Monitoring techniques is becoming the need of the day with the technologies available presently. Sensors made of Lead Zirconate Titanate materials, due to their simplicity and robustness, are increasingly used as an effective monitoring sensor in Structural Health Monitoring. Continuous monitoring of the structures using Lead Zirconate Titanate sensors often results in a laborious data retrieval process due to the large amount of signal generated. To speed up the data retrieval process, a multi-sensing technique in which the Lead Zirconate Titanate patches are connected in series and parallel is proposed for structural damage detection. The proposed method is validated using an experimental investigation carried out on a reinforced concrete beam embedded with smart Lead Zirconate Titanate sensor units. The beam is subjected to damage, and the location of damage is identified using conductance signatures obtained from patches sensed individually and through multiplexing. This article proposes an effective methodology for selection of patches to be connected in series/parallel to maximise the efficiency of damage detection. Damage quantification using conventional statistical metrics such as root mean square deviation, mean absolute percentage deviation and cross correlations are found to be ineffective in identifying the location of damage from the multiplexed signatures. In turn, dynamic metrics such as moving root mean square deviation, moving mean absolute percentage deviation and moving cross correlation with overlapped moving blocks of data are proposed in the present work and their ability to detect the damage location from multiplexed signatures is discussed.

STRUCTURAL DAMAGE DETECTION BASED ON CHANGES IN DYNAMIC PARAMETERS

2017 ◽  
Vol 166 (46) ◽  
pp. 75-84
Author(s):  
Dominika Ziaja ◽  
Bartosz Miller
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Single Layer ◽  
Dynamic Parameters ◽  
Structural Damage Detection ◽  
Dynamic Excitation ◽  
Portal Frame

The article presents the idea of structural health monitoring as a supporting action to protect the environment. The preliminary proposal of a procedure enabling the damage detection of the joints is shown on the example of a two-storey portal frame. Conclusions, presented in the paper, based on the measurement of accelerations in selected points of structure, subjected to dynamic excitation. Single-layer, feed-forward artificial neural networks were used as a tool for the analysis of changes in the dynamic parameters.

scholarly journals Structural damage detection based on improved frequency change ratio

2019 ◽  
Vol 272 ◽  
pp. 01010
Author(s):  
Jian WANG ◽  
Huan JIN ◽  
Xiao MA ◽  
Bin ZHAO ◽  
Zhi YANG ◽  
...  
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Detection Method ◽  
Mode Shapes ◽  
Frequency Change ◽  
Damage Localization ◽  
Structural Damage Detection ◽  
Practical Application ◽  
Slight Damage

Frequency Change Ratio (FCR) based damage detection methodology for structural health monitoring (SHM) is analyzed in detail. The effectiveness of damage localization using FCR for some slight damage cases and worse ones are studied on an asymmetric planar truss numerically. Disadvantages of damage detection using FCR in practical application are found and the reasons for the cases are discussed. To conquer the disadvantages of FCR, an Improved Frequency Change Ratio (IFCR) based damage detection method which takes the changes of mode shapes into account is proposed. Verification is done in some damage cases and the results reveal that IFCR can identify the damage more efficiently. Noisy cases are considered to assess the robustness of IFCR and results indicate that the proposed method can work well when the noise is not severe.

Structural Damage Detection Based on Fuzzy LS-SVM Integrated Quantum Genetic Algorithm

2010 ◽  
Vol 20-23 ◽  
pp. 1365-1371 ◽  
Author(s):  
Jian Hong Xie
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Fuzzy Logic ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Least Square ◽  
Support Vector ◽  
Structural Damage Detection ◽  
Quantum Genetic Algorithm

Structural damage detection and health monitoring is very important in many applications, and a key related issue is the method of damage detection. In this paper, Fuzzy Least Square Support Vector Machine (FLS-SVM) is constructed by combining Fuzzy Logic with LS-SVM, and a real-coded Quantum Genetic Algorithm (QGA) is applied to optimize parameters of FLS-SVM. Then, the method of FLS-SVM integrated QGA is used to detect damages for fiber smart structures. The testing results show FLS-SVM possesses the higher detecting accuracy and the bitter dissemination ability than LS-SVM under the same conditions, and the parameters of FLS-SVM can be effectively optimized by the real-coded QGA. The proposed method of FLS-SVM integrated QGA is effective and efficient for structural damage detection.

Detection of Small Damage of Beam Structures Based on the Slope of Proper Orthogonal Mode

2010 ◽  
Vol 97-101 ◽  
pp. 4457-4460
Author(s):  
Dan Sheng Wang ◽  
Ying Bo Zhang ◽  
Hai Ping Yang ◽  
Hong Ping Zhu
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Detection Method ◽  
Numerical Study ◽  
Structural Damage Detection ◽  
Beam Structures ◽  
Study Results ◽  
The Difference ◽  
Proper Orthogonal

In recent two decades, the issues on structural damage detection and health monitoring have been paid considerable attention in mechanical and civil engineering communities. A lot of researchers have developed many methods to try to resolve the problems. To this day, detection of the small damage of structures, however, has still been a difficulty. The correlation theories of proper orthogonal decomposition (POD) and the basic principle of a new structural damage detection method based on the slope of POD are introduced in this paper. Numerical study on beam structures for small damage detection based on the proposed method is implemented. From the study results one can find that the method based on the slope of the difference of proper orthogonal modes (POMs) has the abilities to localize the small damage of beam structures.

1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

2018 ◽  
Vol 275 ◽  
pp. 1308-1317 ◽  
Author(s):  
Osama Abdeljaber ◽  
Onur Avci ◽  
Mustafa Serkan Kiranyaz ◽  
Boualem Boashash ◽  
Henry Sodano ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Structural Damage Detection ◽  
Structural Health ◽  
Benchmark Data

Comparison of Several Methods for Optimal Sensor Placement in Structural Health Monitoring

2011 ◽  
Vol 250-253 ◽  
pp. 3254-3257
Author(s):  
Xiao Meng Sun ◽  
Zi Cai Yan ◽  
Da Yong Zhu
Keyword(s):  
Damage Detection ◽  
Fisher Information ◽  
Health Monitoring ◽  
Optical Sensor ◽  
Structural Damage ◽  
The Other ◽  
Structural Damage Detection ◽  
The Difference ◽  
Methods Numerical ◽  
Sensor Locations

This paper begins with an introduction of two existing methods of prioritizing sensor locations, effective independence (EI) method and damage sensitivity (DS) method, followed by a new method (DRS) based on the harmony between damage identifiability and modal observability. For the comparison of these methods, the difference and relationship between these Fisher information matrixes (FIMs) is examined by a quasi-analytical mode. In addtion, this approach discusses the adaptability of the three methods. Numerical example indicates the limitation of EI method and DS method, and DRS method effectively avoids the contradiction between the two different optimization criterions. Finally, utilizing the result of the optical sensor locations, the results of structural damage detection by DRS method are much more accurate comparing with the other two methods on the whole.This template explains and demonstrates how to prepare your camera-ready paper for Trans Tech Publications. The best is to read these instructions and follow the outline of this text.

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