A Spatial Model and Multiobjective Fuzzy Inference-Based Clustering Routing Algorithm for Bridge Monitoring

Wireless sensors have the advantages of distributed and flexible deployment, real-time monitoring, multisensor collaboration, self-organization, and self-adaptation. They can be widely used in bridge structural health monitoring systems (BHMSs). At the same time, wireless sensors are still limited b...

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Bibliographic Details
Published in:IEEE sensors journal Vol. 25; no. 1; pp. 1669 - 1681
Main Authors: Yang, Jiguang, Huo, Jiuyuan, Mu, Cong
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Battery cycles
Bridge space model
bridge structural health monitoring system (BHMS)
Bridges
Clustering
Clustering algorithms
fuzzy inference system
Fuzzy logic
Inference
Inference algorithms
Monitoring
multiobjective optimization
Multiple objective analysis
Optimization
Pareto optimization
Pareto optimum
Real time
Routing
Sensor phenomena and characterization
Sensors
Simulation
Structural health monitoring
Wireless communication
Wireless communications
wireless sensor network (WSN)
Wireless sensor networks
ISSN:1530-437X, 1558-1748
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Summary:Wireless sensors have the advantages of distributed and flexible deployment, real-time monitoring, multisensor collaboration, self-organization, and self-adaptation. They can be widely used in bridge structural health monitoring systems (BHMSs). At the same time, wireless sensors are still limited by battery life and communication distance; extending the life cycle of wireless sensor networks (WSNs) employing optimal deployment and effective improvement of routing algorithms is a research hotspot for domestic and foreign engineering and academic circles. In this article, a WSN clustering routing algorithm based on bridge spatial model and multiobjective fuzzy inference (BSMOFC) is proposed to solve the problem that the existing research has not considered the spatial characteristics of bridges and the reasonable choice of cluster head (CH) in the clustering routing algorithm. First, a bridge space model is designed to simulate the 3-D deployment of WSN nodes; second, the CH selection process of the WSN clustering routing algorithm is defined as a multiobjective optimization problem, and the multiobjective non-dominated sorted whale optimization algorithm (NSWOA) is used to solve the set of Pareto solutions. All the solutions are defined as the candidate CHs (C-CHs), and then a fuzzy inference system is used to choose the final CHs (F-CHs). Finally, the simulation platform MATLAB completes the performance verification of the BSMOFC algorithm. The simulation results show that the BSMOFC algorithm can effectively extend the WSN lifetime and provide a new practical method for selecting a Pareto optimal solution.
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ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2024.3498056