Structural damage identification using image-based pattern recognition on event-based binary data generated from self-powered sensor networks

2018 ◽  
Vol 25 (4) ◽  
pp. e2135 ◽  
Author(s):  
Hadi Salehi ◽  
Saptarshi Das ◽  
Shantanu Chakrabartty ◽  
Subir Biswas ◽  
Rigoberto Burgueño
Keyword(s):  
Pattern Recognition ◽  
Sensor Networks ◽  
Binary Data ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Damage Identification ◽  
Self Powered ◽  
Event Based

scholarly journals A Shannon entropy approach for structural damage identification based on self-powered sensor data

2019 ◽  
Vol 200 ◽  
pp. 109619 ◽  
Author(s):  
Mohsen Mousavi ◽  
Damien Holloway ◽  
J.C. Olivier ◽  
Amir H. Alavi ◽  
Amir H. Gandomi
Keyword(s):  
Shannon Entropy ◽  
Structural Damage ◽  
Damage Identification ◽  
Sensor Data ◽  
Structural Damage Identification ◽  
Self Powered

Sensor placement and structural damage identification from minimal sensor information

AIAA Journal ◽  
1997 ◽  
Vol 35 ◽  
pp. 369-374 ◽  
Author(s):  
Richard G. Cobb ◽  
Brad S. Liebst
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Sensor Placement ◽  
Structural Damage Identification ◽  
Sensor Information

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.

scholarly journals Bridge structural damage identification based on parallel CNN-GRU

2021 ◽  
Vol 626 ◽  
pp. 012017
Author(s):  
J Z Zou ◽  
J X Yang ◽  
G P Wang ◽  
Y L Tang ◽  
C S Yu
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Structural Damage Identification
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