Placement Optimization of Distributed-Sensing Fiber Optic Sensors Using Genetic Algorithms

Li, Jing; Kapania, Rakesh K.; Spillman, William B.

doi:10.2514/1.25090

Cited by 19 publications

(6 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One is the appropriate placement of fibers, to get the best coverage of the structure that has to be monitored and the best sensitivity to observed phenomena or identified parameters. Some preliminary studies in this direction can be found [6,39,141]. For instance, it was shown in [121] that sinusoidal positioning was a good option for various direction strain sensing.…”

Section: Challengesmentioning

confidence: 99%

An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring

Chamoin¹,

Farahbakhsh²,

Poncelet³

2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

This paper is a review on distributed optic fiber sensing for structural health monitoring applications, with a deeper focus on technologies relying on the Rayleigh backscattering phenomenon. It addresses the basic physical principles which are involved, the implementation and instrumentation of the measurement techniques, as well as recent practical applications, current performance, and remaining challenges. Being written at an elementary level and integrating relevant theoretical and technical details, we hope the document can be useful for researchers and engineers looking for an up-to-date overview on a field which currently undergoes significant development and increasing attractiveness, in particular for damage tracking in complex mechanical structures.

show abstract

Section: Challengesmentioning

confidence: 99%

An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring

Chamoin¹,

Farahbakhsh²,

Poncelet³

2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…In [11] a unified sensor performance metric is defined for vibrations monitoring and fault detection as the integration of a weighted functional of some strain measures over the optical fiber length for both discrete and distributed sensors. The optical fiber is represented by a non-uniform rational B-spline curve.…”

Section: Introductionmentioning

confidence: 99%

Archive of Mechanical Engineering

Ameduri

Ciminello

Dimino

et al. 2019

View full text Add to dashboard Cite

An optimal sensor placement methodology is implemented and herein proposed for SHM model-assisted design and analysis purposes. The kernel of this approach analysis is a genetic-based algorithm providing the sensor network layout by optimizing the probability of detection (PoD) function while, in this preliminary phase, a classic strain energy approach is adopted as well established damage detection criteria. The layout of the sensor network is assessed with respect to its own capability of detection, parameterized through the PoD. A distributed fiber optic strain sensor is adopted in order to get dense information of the structural strain field. The overall methodology includes an original user-friendly graphical interface (GUI) that reduces the time-to-design costs needs. The proposed methodology is preliminarily validated for isotropic and anisotropic elements.

show abstract

“…However, there are still some shortcomings in this field: relapsing into local optimal solution and low efficiency convergence. To overcome these limitations existed in conventional optimization methods, modern intelligent optimization algorithms have been widely applied in OSP field, such as particle swarm optimization algorithms, simulated annealing algorithm, genetic algorithms (GAs), and other intelligent optimization algorithms . As one key component of the optimization problems, the fitness function, namely, performance index or objective function, can directly determine the results and convergences of OSP.…”

Section: Introductionmentioning

confidence: 99%

Sensor placement for structural health monitoring using hybrid optimization algorithm based on sensor distribution index and FE grids

Yang

2018

Struct Control Health Monit

View full text Add to dashboard Cite

Summary Considering the adjustments for sensor selections attributed by different finite element (FE) grids, a hybrid optimization algorithm including FE grids updating for optimal sensor placement is proposed based on effective independence method and sensor distribution index, in order to improve the algorithm efficient and reduce the redundancy information simultaneously. This study takes into account of the relationship of FE grids, redundancy information, and optimal sensor placement performance by detailed statements. Furthermore, in order to reduce the redundancy information caused by too fine FE grids and too near measurements, the proposed sensor distribution index can synthetically deal with both cases of the nearer nodes and overall sensor distribution ranges. Moreover, by means of normalization and weighted factor, the constituted fitness function, which consists of Fisher information and sensor distribution index, can be more competitive by eliminating the gap of orders caused by the different fitness functions. Therefore, the economical FE grids are suggested, and the corresponding optimum sensor locations are simultaneously obtained by the hybrid optimization algorithm. Finally, the proposed method is verified by a deployable antenna module of space solar power satellite and a wing of reusable launch vehicle, respectively.

show abstract

Placement Optimization of Distributed-Sensing Fiber Optic Sensors Using Genetic Algorithms

Cited by 19 publications

References 55 publications

An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring

An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring

Archive of Mechanical Engineering

Sensor placement for structural health monitoring using hybrid optimization algorithm based on sensor distribution index and FE grids

Contact Info

Product

Resources

About