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

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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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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An optimal sensor placement design framework for structural health monitoring using Bayes risk

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2021.108618 ◽

2022 ◽

Vol 168 ◽

pp. 108618

Author(s):

Yichao Yang ◽

Mayank Chadha ◽

Zhen Hu ◽

Michael D. Todd

Keyword(s):

Structural Health Monitoring ◽

Health Monitoring ◽

Sensor Placement ◽

Design Framework ◽

Bayes Risk ◽

Optimal Sensor Placement ◽

Structural Health

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Sensor Optimal Placement for Structural Health Monitoring Based on Stabilization Diagram

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.540.47 ◽

2013 ◽

Vol 540 ◽

pp. 47-54 ◽

Cited By ~ 1

Author(s):

Chun Li Wu ◽

Han Bing Liu ◽

Yan Li

Keyword(s):

Structural Health Monitoring ◽

Health Monitoring ◽

Sensor Placement ◽

Energy Criterion ◽

Optimal Placement ◽

Mode Shapes ◽

Diagram Method ◽

Structural Health ◽

Fitness Functions ◽

Stabilization Diagram

A novel stabilization diagram method was presented for sensor placement in structural health monitoring of bridges. The aim of the method is to select the optimal locations which can achieve the best identification of modal frequencies and mode shapes. A single parents genetic algorithm was adopted to optimize the sensor locations from a set of coordinate positions. Five fitness functions taken as the objective function are proposed based on effective independence, modal assurance and modal energy criterion, in which the combined fitness functions can obtain more comprehensive properties to reduce the noise interference. The proposed method puts forward a universal way for sensor placement of the civil engineering structure. The effectiveness of the method was proved by a simply supported beam and a continuous beam bridge in the An Longquan interchange overpass.

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