Optimal Sensor Placement for Substructural Response Reconstruction

2014 ◽  
Vol 81 (6) ◽  
Author(s):  
Q. Ye ◽  
S. S. Law
Keyword(s):  
Degrees Of Freedom ◽  
Sensor Placement ◽  
Dynamic Responses ◽  
Reconstruction Method ◽  
Optimal Sensor Placement ◽  
Reconstruction Process ◽  
Response Reconstruction ◽  
Sensor Configuration ◽  
The Time Domain ◽  
Interface Forces

In an existing substructural dynamic response reconstruction method (Li, J., and Law, S.S., 2011. “Substructural Response Reconstruction in Wavelet Domain,” ASME J. Appl. Mech., 78(4), p. 041010) developed by Law, two sets of sensors are needed for the reconstruction of dynamic responses at selected degrees-of-freedom. A method to find the optimal sensor placement is presented in this paper for the substructural response reconstruction. It is based on the effective independence method but in the time domain. Unlike previous methods on sensor placement, two sets of optimal sensor placement are needed with the first set for estimating the interface forces between substructures, and the second set for reconstructing the responses. Sensors that capture the most information of the interface forces will be selected into the first set, and the subsequently estimated interface forces are used to reconstruct the responses at the second set of selected degrees-of-freedom. The selection of the second set of sensors is based on the least measurement noise effect in the response reconstruction process. A box-section bridge deck is adopted in the simulation studies. Numerical simulations with the forward and backward sequential sensor placement methods show that the proposed method could give reasonable predictions with smaller error in the reconstructed responses, and sensor locations along the major directions of the interface forces should be selected into the first or the second set of sensor configuration.

Computational methodologies for optimal sensor placement in structural health monitoring: A review

2019 ◽  
Vol 19 (4) ◽  
pp. 1287-1308 ◽  
Author(s):  
Yi Tan ◽  
Limao Zhang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sensor Placement ◽  
Evaluation Criteria ◽  
Problem Formulation ◽  
Optimal Sensor Placement ◽  
Structural Health ◽  
Sensor Configuration ◽  
Comprehensive Reference

Structural health monitoring plays an increasingly significant role in detecting damages for large and complex structures to ensure their serviceability and sustainability. Optimal sensor placement is critical in the structural health monitoring system as the sensor configuration directly impacts the quality of collected data used for structural health diagnosis. Therefore, this study presents a comprehensive review of computational methodologies for optimal sensor placement in structural health monitoring. The problem formulation of optimal sensor placement is first introduced, including commonly used evaluation criteria for sensor configurations. Then, various existing optimization methodologies for sensor placement are summarized and introduced in detail, especially for the evolutionary algorithms and their improved variants. Finally, the suitability of computational methods for specific structural health monitoring applications is also discussed. The main goal of this study is to deliver a comprehensive reference of computational methodologies for optimal sensor placement in structural health monitoring studies and applications. This article is concluded by highlighting the most widely utilized evaluation criteria and optimization methodologies for sensor configuration determination.

Acceleration sensor placement technique for vibration test in structural health monitoring using microhabitat frog-leaping algorithm

2017 ◽  
Vol 17 (2) ◽  
pp. 169-184 ◽  
Author(s):  
Shuo Feng ◽  
Jinqing Jia
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sensor Placement ◽  
Optimal Placement ◽  
Vibration Test ◽  
Acceleration Sensor ◽  
Optimal Sensor Placement ◽  
Structural Health ◽  
Acceleration Sensors ◽  
Sensor Configuration

In this article, a microhabitat frog-leaping algorithm is proposed based on original shuffled frog-leaping algorithm and effective independence method to make the algorithm more efficient to optimize the 3-axis acceleration sensor configuration in the vibration test of structural health monitoring. Optimal sensor placement is a vital component of vibration test in structural health monitoring technique. Acceleration sensors should be placed such that all of the important information is collected. The resulting sensor configuration should be optimal such that the testing resources are saved. In addition, sensor configuration should be calculated automatically to facilitate engineers. However, most of the previous methods focus on the sensor placement of 1-axis sensors. Then, the 3-axis acceleration sensors are calculated by the method of 1-axis sensors, which results in non-optimal placement of many 3-axis acceleration sensors. Moreover, the calculation precisions and efficiencies of most of the previous methods cannot meet the requirement of practical engineering. In this work, the microhabitat frog-leaping algorithm is proposed to solve the optimal sensor placement problems of 3-axis acceleration sensors. The computation precision and efficiency are improved by microhabitat frog-leaping algorithm. Finally, microhabitat frog-leaping algorithm is applied and compared with other algorithms using Dalian South Bay Cross-sea Bridge.

scholarly journals Optimal sensor placement through expansion of static strain measurements to static displacements

2021 ◽  
Vol 17 (1) ◽  
pp. 155014772199171
Author(s):  
Jun-Hyeok Song ◽  
Eun-Taik Lee ◽  
Hee-Chang Eun
Keyword(s):  
Damage Detection ◽  
Degrees Of Freedom ◽  
Sensor Placement ◽  
Measurement Data ◽  
Element Model ◽  
External Noise ◽  
Truss Structure ◽  
Optimal Sensor Placement ◽  
Placement Method ◽  
The Relationship

Optimal sensor placement is used to establish the optimal sensor quantity and layout. In this study, the minimum quantity and locations of measurement sensors were assumed to satisfy the constraint conditions of the optimal sensor placement. A set of strain data in a truss structure was expanded to another set of displacements corresponding to the entire degrees of freedom from the relationship between the strain and displacement. It indicates to reduce the number of sensors because the strain depends on the displacements in a finite element model. The damaged truss element was traced using the expanded data that satisfied the prescribed constraints. The proposed optimal sensor placement method has a merit to explicitly determine the optimal sensor locations without any numerical scheme and statistical methods. The method was applied to the damage detection of a single-damaged truss structure. It was shown that the optimal sensor placement method depended on the sensor layout irrespective of the same quantity of sensors. In addition, a numerical example was used to compare sensitivities to damage detection based on the sensor placement and the existence of external noise contained in the measurement data.

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 A Data Driven Method for Optimal Sensor Placement in Multi-Zone Buildings

2021 ◽  
pp. 110956
Author(s):  
Gowri Suryanarayana ◽  
Javier Arroyo ◽  
Lieve Helsen ◽  
Jesus Lago
Keyword(s):  
Sensor Placement ◽  
Data Driven ◽  
Optimal Sensor Placement
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