Optimizing FBG sensor layout of tunnel monitoring using improved multi-objective snow ablation optimizer based on radial basis function

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2024-11-26 DOI:10.1016/j.measurement.2024.116289

Rongjun Xing , Zhongchao Zhao , Chuan He , Pai Xu , Daiqiang Zhu , Yufu Li , Yujun Li , Zewen Yang

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引用次数: 0

Abstract

In order to improve the optimization criterion and optimization algorithm, this study introduced the objective function of monitoring performance combining the reconstruction error of strain based on Radial Basis Function and the sensor deployment cost, and proposed the improved multi-objective snow ablation optimizer (IMOSAO) with external archive and Tent mapping. Firstly, initial solutions with uniform distribution were generated by Tent mapping and decimal coding. Then, they were updated by the dual-population mechanism balancing exploration and exploitation. Secondly, the Pareto frontiers of sensor layouts in the external archive were obtained after stop updating. The effectiveness of the improved parts of IMOSAO were validated in ablation studies, numerical and physical experiments. The optimized layouts achieved promising results with the cost reduction of 39 %, average accuracy above 95.72 %, minimum accuracy 84.61 % and least R² 0.9961. Finally, the algorithm reduced operation time and offered superior convergence compared with others. These findings underscore its significant potential in optimizing sensor layout of tunnel monitoring and provide a new view for other measurement sensors.

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利用基于径向基函数的改进型多目标雪消融优化器优化隧道监测的 FBG 传感器布局

为了改进优化准则和优化算法，本研究引入了基于径向基函数的应变重建误差和传感器部署成本相结合的监测性能目标函数，并提出了具有外部档案和 Tent 映射的改进型多目标雪消融优化器（IMOSAO）。首先，通过 Tent 映射和十进制编码生成均匀分布的初始解。然后，通过兼顾探索和开发的双人口机制对其进行更新。其次，在停止更新后，获得外部档案中传感器布局的帕累托前沿。在烧蚀研究、数值和物理实验中验证了 IMOSAO 改进部分的有效性。优化后的布局取得了很好的效果，成本降低了 39%，平均精度高于 95.72%，最低精度为 84.61%，最小 R2 为 0.9961。最后，与其他算法相比，该算法缩短了操作时间，并提供了卓越的收敛性。这些发现凸显了该算法在优化隧道监测传感器布局方面的巨大潜力，并为其他测量传感器提供了新的视角。

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.