An Effective Independence-Improved Modal Strain Energy Method for Optimal Sensor Placement of Bridge Structures

In this study, an effective independence-improved modal strain energy (EI-IMSE) method is proposed for the optimal sensor placement (OSP) problem in the field of the structural health monitoring and moving force identification. The improved modal strain energy (IMSE) is used to modify optimal sensor placement results obtained by the effective independence (EI) method. The EI-IMSE OSP method is verified by some numerical simulations on a 2D planar truss bridge model. Based on the criteria of modal assurance criterion (MAC), trace of fisher matrix, matrix condition number, and the least mean square error, the EI-IMSE OSP method is assessed through comparing with those of EI, EI-driving point residue (EI-DPR), EI-average driving DOF velocity (EI-ADDOFV), and EI-average acceleration amplitude (EI-AAA). The illustrated results show that the proposed EI-IMSE OSP method is feasible with a higher accuracy.

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Optimal Sensor Placement Based on Tabu Search Algorithms

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.578-579.1069 ◽

2014 ◽

Vol 578-579 ◽

pp. 1069-1072 ◽

Cited By ~ 1

Author(s):

Jie Zi Zhan ◽

Ling Yu

Keyword(s):

Tabu Search ◽

Sensor Placement ◽

Least Mean Square ◽

Optimal Sensor Placement ◽

Modal Assurance Criterion ◽

Mean Values ◽

Moving Force ◽

Matrix Condition Number ◽

The Mean ◽

Matrix Condition

In this study, the Tabu search (TS) algorithm is introduced into the optimal sensor placement (OSP) problem in the field of the structural health monitoring and moving force identification. A TS-based OSP procedure is proposed and further evaluated by some numerical simulations on a 2D planar truss model. The mean values of off-diagonal elements in a modal assurance criterion (MAC) matrix are used as the optimization objective function. Based on the criteria of MAC, determinant of fisher matrix, matrix condition number, and the least mean square error, the TS-based OSP procedure is evaluated through comparing with ones due to both of the energy coefficient-effective independence (ECEFI) and the effective independence (EFI) algorithms. The results show that the proposed TS-based OSP procedure is feasible with a higher accuracy.

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A New Optimal Sensor Placement Strategy Based on Modified Modal Assurance Criterion and Improved Adaptive Genetic Algorithm for Structural Health Monitoring

Mathematical Problems in Engineering ◽

10.1155/2015/626342 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 5

Author(s):

Can He ◽

Jianchun Xing ◽

Juelong Li ◽

Qiliang Yang ◽

Ronghao Wang ◽

...

Keyword(s):

Genetic Algorithm ◽

Structural Health Monitoring ◽

Health Monitoring ◽

Sensor Placement ◽

Adaptive Genetic Algorithm ◽

Optimal Sensor Placement ◽

Modal Assurance Criterion ◽

Modal Strain Energy ◽

Structural Health ◽

Computation Efficiency

Optimal sensor placement (OSP) is an important part in the structural health monitoring. Due to the ability of ensuring the linear independence of the tested modal vectors, the minimum modal assurance criterion (minMAC) is considered as an effective method and is used widely. However, some defects are present in this method, such as the low modal energy and the long computation time. A new OSP method named IAGA-MMAC is presented in this study to settle the issue. First, a modified modal assurance criterion (MMAC) is proposed to improve the modal energy of the selected locations. Then, an improved adaptive genetic algorithm (IAGA), which uses the root mean square of off-diagonal elements in the MMAC matrix as the fitness function, is proposed to enhance computation efficiency. A case study of sensor placement on a numerically simulated wharf structure is provided to verify the effectiveness of the IAGA-MMAC strategy, and two different methods are used as contrast experiments. A comparison of these strategies shows that the optimal results obtained by the IAGA-MMAC method have a high modal strain energy, a quick computational speed, and small off-diagonal elements in the MMAC matrix.

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Optimal Sensors Placement Based on Modal Strain Energy

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.166-169.1164 ◽

2012 ◽

Vol 166-169 ◽

pp. 1164-1169 ◽

Cited By ~ 1

Author(s):

Heng Bin Zheng ◽

Quan Sheng Yan ◽

Jun Liang Hu ◽

Zhou Chen

Keyword(s):

Strain Energy ◽

Random Vibration ◽

Distance Matrix ◽

Element Model ◽

Optimal Placement ◽

Acceleration Response ◽

Modal Strain Energy ◽

Simply Supported ◽

Bridge Model ◽

Truss Bridge

For a space simply supported truss bridge model, a method named element modal strain energy (MSE) was firstly adopted in the field of the optimal sensors placement. By taking nodes MSE, nodes distance matrix reciprocal as weights, and combining with optimal matching in graph theory, how to apply the method for optimal sensors placement was stated. Through analyzing on the random vibration property of the bridge finite element model, the nodes position of larger acceleration response was compared with the optimal placement got from the above method, which could verified the effectiveness of optimal sensors placement.

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A Multiobjective Perspective to Optimal Sensor Placement by Using a Decomposition-Based Evolutionary Algorithm in Structural Health Monitoring

Applied Sciences ◽

10.3390/app10217710 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7710

Author(s):

Tsung-Yueh Lin ◽

Jin Tao ◽

Hsin-Haou Huang

Keyword(s):

Structural Health Monitoring ◽

Evolutionary Algorithm ◽

Health Monitoring ◽

Sensor Placement ◽

Frame Structure ◽

Mode Shapes ◽

Beam Model ◽

Optimal Sensor Placement ◽

Modal Assurance Criterion ◽

Structural Health

The objective of optimal sensor placement in a dynamic system is to obtain a sensor layout that provides as much information as possible for structural health monitoring (SHM). Whereas most studies use only one modal assurance criterion for SHM, this work considers two additional metrics, signal redundancy and noise ratio, combining into three optimization objectives: Linear independence of mode shapes, dynamic information redundancy, and vibration response signal strength. A modified multiobjective evolutionary algorithm was combined with particle swarm optimization to explore the optimal solution sets. In the final determination, a multiobjective decision-making (MODM) strategy based on distance measurement was used to optimize the aforementioned objectives. We applied it to a reduced finite-element beam model of a reference building and compared it with other selection methods. The results indicated that MODM suitably balanced the objective functions and outperformed the compared methods. We further constructed a three-story frame structure for experimentally validating the effectiveness of the proposed algorithm. The results indicated that complete structural modal information can be effectively obtained by applying the MODM approach to identify sensor locations.

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Coverage intensity of optimal sensors for common, isolated, and integrated steel structures using novel approach of FEM-MAC-TTFD

International Journal of Distributed Sensor Networks ◽

10.1177/1550147719857568 ◽

2019 ◽

Vol 15 (8) ◽

pp. 155014771985756 ◽

Cited By ~ 1

Author(s):

Mehdi Firoozbakht ◽

Hamidreza Vosoughifar ◽

Alireza Ghari Ghoran

Keyword(s):

Base Isolation ◽

Sensor Placement ◽

Time History ◽

Shear Wall ◽

Optimal Sensor Placement ◽

Modal Assurance Criterion ◽

Moment Resisting Frame ◽

Steel Shear Wall ◽

Significant Difference ◽

Moment Resisting

The coverage intensity of sensors is the most important issue on structural health monitoring technique. The geometric configuration of sensors must be optimized based on coverage intensity with proper objectives. In this article, a novel algorithm for optimal sensor placement in various steel frames was evaluated. These frames including moment-resisting frame, moment-resisting frame with base isolation, and moment-resisting frame with base isolation with steel shear wall were selected for case studies. This approach was proposed based on combination of common optimal sensor placement algorithm and nonlinear time history analysis. A new method called transformed time history to frequency domain approach was evaluated to transform nonlinear time history analysis results to frequency domain and then the effective frequencies according the maximum range of Fourier amplitude were selected. The modified type of modal assurance criterion values can be achieved from modal assurance criterion with the exact seismic displacement. All of novel optimal sensor placement processes were done through FEM-MAC-TTFD code modeled and developed in MATLAB by authors of this article. The results show that there is good relative correlation between the sensors number and coverage intensity obtained with modal and modified modal assurance criterion approaches for moment-resisting frame system, but for integrated frame such as moment-resisting frame with base isolation and moment-resisting frame with base isolation with steel shear wall, the modified modal assurance criterion approach is better approach. There is no significant difference between coverage intensity of sensors for top joints between modal assurance criterion and modified modal assurance criterion approaches for moment-resisting frame, moment-resisting frame with base isolation, and moment-resisting frame with base isolation with steel shear wall systems ( R2 = 0.994, 0.986, and 0.724, respectively). It was found that if reference point is located in center of frame, there is significant difference between modal assurance criterion and modified modal assurance criterion approaches, and modified modal assurance criterion generated slightly better results.

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Optimal Sensor Placement and Minimum Number Selection of Sensors for Health Monitoring of Transmission Towers

Shock and Vibration ◽

10.1155/2020/2375947 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Chuandi Zhou ◽

Yibing Liu ◽

Ji Wu ◽

Chao Zhou

Keyword(s):

Health Monitoring ◽

Sensor Placement ◽

Transmission Tower ◽

Optimal Sensor Placement ◽

Modal Assurance Criterion ◽

Transmission Towers ◽

Minimum Number ◽

The Right ◽

The Relationship ◽

Head Type

Transmission towers are structurally complex, which makes it challenging to choose the right place and number of sensors for health monitoring. In this paper, optimal sensor placement of a cat-head-type transmission tower is conducted by using the Effective Independent Method (EIM) and a method is proposed for calculating the minimum number of sensors for structural health monitoring by combining EIM and Modal Assurance Criterion (MAC). The method for calculating the number of sensors prescribed in this paper derives a curve that shows the relationship between MAC value and the number of sensors. It is found that the MAC value decreases with increase in the number of sensors. When the number of sensors reaches a certain threshold, the curve tends to stabilize. Then, the number of sensors corresponding to the minimum MAC is proposed as the minimum number of sensors. Through calculation, the minimum number of sensors of the cat-head-type transmission tower is obtained. Also, the optimal sensor placement results show that the position of a large number of sensors includes the position of a smaller number of sensors.

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Optimal Sensor Placement Algorithm for Structural Damage Identification

Recent Patents on Engineering ◽

10.2174/1872212113666190110124551 ◽

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.

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