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An NSGA-II-Based Multiobjective Optimization Method for FBG Sensor Placement
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DOI：10.1109/JSEN.2026.3673289.png)
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Abstract
En 中文
Rational placement of fiber Bragg grating (FBG) sensor is critical for aircraft structural health monitoring (SHM), as it directly influences overall monitoring performance. This article addresses the optimization of FBG sensor placement on aircraft wing skins and proposes an NSGA-II-based multiobjective optimization method that comprehensively considers measurement accuracy, fatigue life, and the uniformity-coverage metric. The theoretical framework is established for these performance indicators, and their corresponding analytical expressions are derived. A finite element analysis (FEAs) model of a 7075-T6 aluminum alloy sheet is developed to obtain simulated strain, displacement, and stress fields. An improved nondominated sorting genetic algorithm (NSGA-II) is employed to construct the optimization framework and obtain the Pareto-optimal placement schemes. A 3-D Pareto front is generated, where the solution $P_{1}$ (0.0143, 46.7079, 0.3736) achieves the highest measurement accuracy, $P_{2}$ (0.1659, 82.6056, 0.3026) yields the longest fatigue life, and $P_{3}$ (0.0465, 57.3441, 0.3898) provides the best uniformity-coverage metric. To validate the proposed method, a deformation-sensing experimental system was established. Ten FBG strain sensors were installed according to the respective placement schemes, with an additional temperature-compensating grating introduced to correct for thermal effects. Experimental results showed good agreement with simulation trends, demonstrating that the proposed NSGA-II-based multiobjective optimization method effectively balances multiple performance evaluation metrics, offering a practical optimization strategy for the placement of airborne FBG sensing networks with high comprehensive performance requirements.
Keywords:
Deformation measurement
fiber Bragg grating (FBG) sensor
multiobjective optimization
nondominated sorting genetic algorithm (NSGA)-II
Pareto front
sensor placement
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