Sensor placement optimization applied to laminated composite plates under vibration

Gomes, Guilherme Ferreira; Cunha, Sebastião Simões da; Alexandrino, Patrícia da Silva Lopes; Sousa, Bruno Silva de; Ancelotti, Antônio Carlos

doi:10.1007/s00158-018-2024-1

Cited by 41 publications

(22 citation statements)

References 34 publications

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“…GA is one of the commonly used heuristics methodologies to solve NP-hard problems. Both original GA 26–28,38,51,55,57,77,85–93 and improved GA 33,37,42,94–104 had been used in OSP problems.…”

Section: Optimization Methodologiesmentioning

confidence: 99%

“…Vibration-based damage detection approaches monitor changes in natural frequencies, vibration modes, and related derivatives. 90 Besides, as most of the structural elements of civil infrastructures are natural waveguides, ultrasonic-based damage detection methods are also utilized in SHM. 54 For these two specific damage detection methodologies in SHM, evolutionary algorithms are mainly used to obtain the optimal sensor configuration.…”

Section: Optimization Methodologiesmentioning

confidence: 99%

“…For example, Rao and Anandakumar 115 proposed a PSO-based positioning algorithm for sensor in large-scale structures, where the best identification of frequencies and modals was achieved. Gomes et al 90 employed GA to locate the best sensor configuration to cover a specific number of low-frequency modes for laminated composite plates under vibration. As for ultrasonic-based SHM application, Gao and Rose 54 used covariance matrix adaptation evolutionary strategy (CMAES) to determine the sensor number and sensor distribution in SHM.…”

Section: Optimization Methodologiesmentioning

confidence: 99%

See 2 more Smart Citations

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

Tan

Zhang

2019

Structural Health Monitoring

109

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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.

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Section: Optimization Methodologiesmentioning

confidence: 99%

Section: Optimization Methodologiesmentioning

confidence: 99%

Section: Optimization Methodologiesmentioning

confidence: 99%

See 1 more Smart Citation

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

Tan

Zhang

2019

Structural Health Monitoring

109

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“…For the OSP problem, different techniques as discussed above have been developed, taking into consideration a large number of CFs. Many researchers 38,[48][49][50] have compared the performance of the newly developed techniques with the techniques found in references. The comparison of the performance can be characterized as follows:…”

Section: Sequential Placement Algorithmsmentioning

confidence: 99%

Optimization of sensor placement for structural health monitoring: a review

Ostachowicz

Soman

Malinowski

2019

Structural Health Monitoring

258

154

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The deployment cost of the structural health monitoring (SHM) system is the major argument against the more widespread use of the structural health monitoring techniques. Optimization of sensor placement offers an opportunity to reduce the cost of the SHM system without compromising on the quality of the monitoring approach. Several studies in the area of optimization of sensor placement for SHM applications have been undertaken but the approach has been rather application specific. This article is an attempt to present an unbiased state of the art of the work carried out in the area. The article is targeted towards researchers working in the field of structural health monitoring and optimization of sensor placement as well as practising engineers. This article reviews the work in the area of optimization of sensor placement. It first presents the definition of the optimization problem and then describes each step of the optimization. The current state of the art is then classified based on the techniques for which the optimization of sensor placement has been optimized. The article covers vibration-based monitoring, strain monitoring and elastic wave-based monitoring, as in the eyes of the authors these three techniques are most commonly used and accepted in the SHM community. The article later discusses the different optimization algorithms that have been applied in the literature. The article highlights the different pitfalls of the optimization algorithms and the countermeasures different researchers have proposed to overcome the known shortcomings. In the later section, the multi-objective optimization or the problem definition, keeping in mind the structural as well as executional demands, is discussed. A section has also been developed to showcase the use of optimization of sensor placement techniques’ data fusion–based systems.

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“…As we all know, the number of sensors is also a very important factor for the economic cost of an SHM system. But for the large-scale complex structure, there are so many locations where sensors can be placed and current research works mainly focus on location optimization under different certain number of sensors (Gomes et al, 2018; Guo et al, 2004). For the complex mechanical structures such as QCC, the sensors will be embodied inside the structure.…”

Section: Objective Functionmentioning

confidence: 99%

Health monitoring sensor placement optimization based on initial sensor layout using improved partheno-genetic algorithm

Qin

Zhan

Chen

et al. 2020

Advances in Structural Engineering

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Optimal sensor placement is an important component of a reliability structural health monitoring system for a large-scale complex structure. However, the current research mainly focuses on optimizing sensor placement problem for structures without any initial sensor layout. In some cases, the experienced engineers will first determine the key position of whole structure must place sensors, that is, initial sensor layout. Moreover, current genetic algorithm or partheno-genetic algorithm will change the position of the initial sensor locations in the iterative process, so it is unadaptable for optimal sensor placement problem based on initial sensor layout. In this article, an optimal sensor placement method based on initial sensor layout using improved partheno-genetic algorithm is proposed. First, some improved genetic operations of partheno-genetic algorithm for sensor placement optimization with initial sensor layout are presented, such as segmented swap, reverse and insert operator to avoid the change of initial sensor locations. Then, the objective function for optimal sensor placement problem is presented based on modal assurance criterion, modal energy criterion, and sensor placement cost. At last, the effectiveness and reliability of the proposed method are validated by a numerical example of a quayside container crane. Furthermore, the sensor placement result with the proposed method is better than that with effective independence method without initial sensor layout and the traditional partheno-genetic algorithm.

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Sensor placement optimization applied to laminated composite plates under vibration

Cited by 41 publications

References 34 publications

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

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

Optimization of sensor placement for structural health monitoring: a review

Health monitoring sensor placement optimization based on initial sensor layout using improved partheno-genetic algorithm

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