A Real-Valued Genetic Algorithm for Optimization of Sensor Placement for Guided Wave-Based Structural Health Monitoring

Soman, Rohan; Malinowski, Paweł

doi:10.1155/2019/9614630

Cited by 19 publications

(12 citation statements)

References 22 publications

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“…The simple phased array is linear in shape and has been successfully used for locating damage in aluminium specimens both with and without surface curvature [45], as well as in composites [46]. In summary, based on the achievements presented within the scope of this book and in published studies on sensor networks [35][36][37][38][39][40], we suggest that the same sensor networks may be used for both damage and adhesive bond assessment. Only the signal processing approaches are different for both applications and need to be tailored to the specific task.…”

Section: Sensor Systems Arrays and Network For Assessing Mol Datamentioning

confidence: 87%

“…Although such ideas do not provide an answer to the problem of how the sensors should be deployed on the structure, the placement of the sensors can be tackled by various approaches. Some of the popular strategies are based on evolutionary algorithms, such as genetic algorithms [37], whereby elliptic-based damage localisation algorithms may be used as a basis for optimisation. Here, the locations of actuating and recording transducers correspond to the ellipse foci, and the circumference of the ellipse informs about the source of wave reflection.…”

Section: Sensor Systems Arrays and Network For Assessing Mol Datamentioning

confidence: 99%

See 1 more Smart Citation

Integrating Extended Non-destructive Testing in the Life Cycle Management of Bonded Products—Some Perspectives

Cavalcanti

Moutsompegka

Τσερπές

et al. 2021

Adhesive Bonding of Aircraft Composite Structures

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In this chapter, we outline some perspectives on embracing the datasets gathered using Extended Non-destructive Testing (ENDT) during manufacturing or repair process steps within the life cycle of bonded products. Ensuring that the ENDT data and metadata are FAIR, i.e. findable, accessible, interoperable and re-usable, will support the relevant stakeholders in exploiting the contained material-related information far beyond a stop/go decision, while a shorter time-to-information will facilitate a prompter time-to-decision in process and product management. Exploiting the value of ENDT (meta)data will contribute to increased performance by integrating all defined, measured, analyzed and controlled aspects of material transformation across process and company boundaries. This will facilitate the optimization of manufacturing and repair operations, boosting their energy efficiency and productivity. In this regard, some aspects that are currently driving activities in the field of pre-process, in-process and post-process quality assessment will be addressed in the following. Furthermore, some requirements will be contemplated for harmonized and conjoint data transfer ranging from a bonded product’s beginning-of-life through its end-of-life, the customization of stand-alone or linked ENDT tools, and the implementation of sensor arrays and networks in joints, devices and structural parts to gather material-related data during a product’s middle-of-life application phase, thereby fostering structural health monitoring (SHM).

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Section: Sensor Systems Arrays and Network For Assessing Mol Datamentioning

confidence: 87%

Section: Sensor Systems Arrays and Network For Assessing Mol Datamentioning

confidence: 99%

Integrating Extended Non-destructive Testing in the Life Cycle Management of Bonded Products—Some Perspectives

Cavalcanti

Moutsompegka

Τσερπές

et al. 2021

Adhesive Bonding of Aircraft Composite Structures

View full text Add to dashboard Cite

show abstract

“…In the family of heuristic optimization algorithms used in sensor placement problems, genetic algorithm-based (GA) methods are widely adopted [45][46][47][48][49] and thus is also used in this study. Holland [50,51] introduced the concept of GA which is a population-based stochastic search technique based on the principles of natural selection and genetics.…”

Section: Genetic Algorithm-based Sensor Placementmentioning

confidence: 99%

“…All the GA results shown in this study are based on these settings. However, it is possible to further fine-tune the accuracy and computational cost of GA by suitably adjusting these parameters [47][48][49]58] and is not attempted here as it is beyond the scope of this paper. Figure 8 shows the variation of C and G for varying from 4 to 10.…”

Section: Fig 5 Cantilever Beam Showing Possible Sensor Locations To Keep Uniaxial Accelerometers In Directionmentioning

confidence: 99%

An optimal sensor placement strategy for reliable expansion of mode shapes under measurement noise and modelling error

Jaya

Ceravolo

Fragonara

et al. 2020

Journal of Sound and Vibration

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Modal expansion techniques are typically used to expand the experimental modal displacements at sensor positions to all unmeasured degrees of freedom. Since in most cases, sensors can be attached only at limited locations in a structure, an expansion is essential to determine mode shapes, strains, stresses, etc. throughout the structure which can be used for structural health monitoring. Conventional sensor placement algorithms are mostly aimed to make the modal displacements at sensor positions of different modes as linearly independent as possible. However, under the presence of modelling errors and measurement noise, an optimal location based on this criterion is not guaranteed to provide an expanded mode shape which is close to the real mode shape. In this work, the expected value of normal distance between the real mode shape and the expanded mode shape is used as a measure of closeness between the two entities. Optimal sensor locations can be determined by minimizing this distance. This new criterion is applied on a simple cantilever beam and an industrial milling tower. In both cases, by using an exhaustive search of all possible sensor configurations it was possible to find sensor locations which resulted in a significant reduction in the distance when compared to a conventional optimal sensor placement strategy. Sufficiently accurate sub-optimal sequential sensor placement algorithm is also suggested as an alternative to the exhaustive search which is then compared with a genetic algorithmbased search. The efficiency of this new sensor placement criterion is further verified using Monte Carlo simulations for some realistic modelling error conditions.

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“…To obtain the damage degree, scholars have investigated the application of many intelligent algorithms in the field of structural damage identification [9,10]. e beetle antennae search algorithm (BAS) [11][12][13] is a novel biology-inspired intelligent optimization algorithm proposed by Jiang, which arises from the simulation of foraging behavior of beetle.…”

Section: Introductionmentioning

confidence: 99%

Damage Identification of Structures Based on Smooth Orthogonal Decomposition and Improved Beetle Antennae Search Algorithm

Zhang

2021

Advances in Civil Engineering

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A novel damage identification method that utilizes the smooth orthogonal decomposition (SOD) combined with the improved beetle antennae search algorithm (BAS) presented by previous scholars is proposed. Firstly, the damage index which can track the curvature changing of mode shape identified by the SOD method is generated by an adaptive polynomial fit method. The locations of structure damages are determined according to the damage index. Thus, the number of possible damaged elements needed to be taken into account can be reduced when calculating the degree of damage. Then, the reduction in the stiffness at the damage location of the structure is calculated by the improved BAS in which the fitness function is constructed by calculated frequencies of the damaged structure in each iteration and the modal frequencies obtained by SOD. The BAS algorithm is improved through a fusion strategy of simulated annealing theory. Thus, the improved BAS algorithm is efficient and adaptive. The effect of this combined application in damage identification has been verified by numerical examples of a simply supported beam with single damage and a cantilever beam with double damage. The numerical results show that this combined algorithm exhibits high reliability in damage identification of beam-like structures.

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A Real-Valued Genetic Algorithm for Optimization of Sensor Placement for Guided Wave-Based Structural Health Monitoring

Cited by 19 publications

References 22 publications

Integrating Extended Non-destructive Testing in the Life Cycle Management of Bonded Products—Some Perspectives

Integrating Extended Non-destructive Testing in the Life Cycle Management of Bonded Products—Some Perspectives

An optimal sensor placement strategy for reliable expansion of mode shapes under measurement noise and modelling error

Damage Identification of Structures Based on Smooth Orthogonal Decomposition and Improved Beetle Antennae Search Algorithm

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