Multi-ocular sensor with fiber bragg grating

Alwin, Tony

doi:10.1007/s11082-020-02654-5

Opt Quant Electron

2021

DOI: 10.1007/s11082-020-02654-5

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Multi-ocular sensor with fiber bragg grating

Tony Alwin¹

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Cited by 2 publications

References 15 publications

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Multimodal LSPR-enhanced crayfish-type optical fiber sensor for ultra-sensitive detection of Shigella sonnei using hybrid nanomaterials

Zhang,

Singh,

Nedoma

et al. 2024

APL Photonics

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This paper designs a biophotonic sensor that utilizes the localized surface plasmon resonance (LSPR) effect to detect Shigella sonnei (S. sonnei) with high sensitivity, featuring a novel crayfish-type optical fiber structure. Diseases and food safety caused by S. sonnei have become a public health issue of common concern around the world. This sensor is specifically designed for the detection of S. sonnei. This sensor has the advantage of being easy to operate, requires no labeling, and has high specificity. Excite the LSPR effect using gold nanoparticles (AuNPs). To enhance the LSPR effect, a fusion structure of multimode fiber and seven-core fiber was utilized, as was a crayfish-type optical fiber structure. Using Rsoft to simulate the crayfish-type optical fiber structure, it is concluded that the structure has excellent evanescent field. S. sonnei antibodies were used to improve the specificity of the sensor. Tungsten disulfide thin layer (WS2-thin layer) and zinc oxide nanowires were used to increase the surface area for antibody attachment. The linear range of the sensor was 1 × 100–1 × 107 CFU/ml, the sensitivity was 0.378 nm/lg (CFU/ml), and the limit of detection was 4.78 CFU/ml. The reproducibility, reusability, selectivity, and stability of the sensor were tested. The test results showed that the sensor had excellent performance. In addition, the sensor was tested with real food samples. This research has far-reaching significance for biophotonic sensors and human health.

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Multimodal LSPR-enhanced crayfish-type optical fiber sensor for ultra-sensitive detection of Shigella sonnei using hybrid nanomaterials

Zhang,

Singh,

Nedoma

et al. 2024

APL Photonics

View full text Add to dashboard Cite

show abstract

Delphi Collaboration Strategy for Multiagent Optical Fiber Intelligent Health Monitoring System

et al. 2022

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Optical fiber sensors are very attractive in mechanical structure intelligent health monitoring system due to some unique characteristics, such as immunity to electromagnetic interference and to aggressive environments, high sensitive and fast response, small physical dimension, excellent resolution and range, and so on. For improving the accuracy and reliability of the optical fiber intelligent health monitoring system in practical engineering application, the collaboration and decision-making strategy based on Delphi method for multiagent optical fiber intelligent health monitoring system is studied in this paper. The proposed system is mainly composed of optical fiber sensing agent, intelligent evaluation agent, and system collaborative decision-making agent. The intelligent evaluation agent is used to evaluate the health status of the monitored mechanical structures. Delphi method is used by the system collaborative decision-making agent to consult each intelligent evaluation agent. Meanwhile, the collaborative partner selection algorithm is used to select the intelligent evaluation agent participating in the collaboration, and the intelligent evaluation agent that does not participate in the decision-making is dynamically modified by the decision result. The experiment for an aircraft wing box as the typical engineering structure is carried out and the verification system is designed, the decision result is compared with that without dynamic correction of the evaluation result. The comparative results indicate that the evaluation accuracy and reliability of the monitored mechanical structural damage are improved significantly after multiple rounds of collaboration and decision making.

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Multi-ocular sensor with fiber bragg grating

Cited by 2 publications

References 15 publications

Multimodal LSPR-enhanced crayfish-type optical fiber sensor for ultra-sensitive detection of Shigella sonnei using hybrid nanomaterials

Multimodal LSPR-enhanced crayfish-type optical fiber sensor for ultra-sensitive detection of Shigella sonnei using hybrid nanomaterials

Delphi Collaboration Strategy for Multiagent Optical Fiber Intelligent Health Monitoring System

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