郭敬东. 基于差分海洋捕食者优化算法的FBG重叠谱解调方法[J]. 应用光学, 2023, 44(6): 1317-1323. DOI: 10.5768/JAO202344.0602001
引用本文: 郭敬东. 基于差分海洋捕食者优化算法的FBG重叠谱解调方法[J]. 应用光学, 2023, 44(6): 1317-1323. DOI: 10.5768/JAO202344.0602001
GUO Jingdong. FBG overlapping spectrum demodulation method based on differential marine predator optimization algorithm[J]. Journal of Applied Optics, 2023, 44(6): 1317-1323. DOI: 10.5768/JAO202344.0602001
Citation: GUO Jingdong. FBG overlapping spectrum demodulation method based on differential marine predator optimization algorithm[J]. Journal of Applied Optics, 2023, 44(6): 1317-1323. DOI: 10.5768/JAO202344.0602001

基于差分海洋捕食者优化算法的FBG重叠谱解调方法

FBG overlapping spectrum demodulation method based on differential marine predator optimization algorithm

  • 摘要: 随着光纤布拉格光栅(fiber Bragg grating,FBG)传感网络应用越来越广泛,对其复用性的要求也日益提高,但FBG复用可能会导致光谱重叠。针对重叠光谱影响FBG解调精度问题,提出了一种基于差分海洋捕食者优化算法的重叠谱解调方法。采用差分进化算法优化海洋捕食者个体更新位置策略,增强了其跳出局部最优解的能力。对2~4个FBG重叠谱进行了仿真研究,并对2个FBG重叠谱解调进行了实验验证。将所提方法与粒子群算法和海洋捕食者算法进行了性能比较,结果表明:本文方法可以有效降低陷入局部最优的概率,提高了算法的稳定性和可靠性。

     

    Abstract: Since the fiber Bragg grating (FBG) sensor networks have been used more and more widely, the requirements for their multiplexing are increasing;however, the FBG multiplexing may lead to spectral overlap. Aiming at the problem that the overlapping spectra could affect the demodulation accuracy of FBG sensor network, an overlapping spectrum demodulation method based on differential marine predator optimization algorithm was proposed. This method adopted the differential evolution algorithm to optimize the individual updating position strategy, which could enhance the ability to jump out of the local optimal solution. 2~4 FBG overlapping spectra were simulated, and 2 FBG overlapping spectrum demodulations were experimentally verified. Furthermore,the performance of the proposed algorithm was compared with the particle swarm optimization algorithm and the marine predator algorithm.Results show that the proposed algorithm can effectively reduce the probability of falling into local optimum, and improve the stability and reliability of the algorithm.

     

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