基于方向领导粒子群算法的Bragg光栅测量土壤水分研究

Research on Soil Moisture Measurement Using Bragg grating Based on Directional Leader Particle Swarm Optimization

为提高Bragg光栅测量土壤水分效果,提出方向领导粒子群算法。首先建立光纤Bragg光栅反射谱中心波长与温度变化关系。接着通过粒子适应度标准差选择领导粒子,采用不同的策略调整方向领导粒子飞行速度,收缩因子限制粒子离开搜索空间的可能性。然后以最小化最大折射率调制深度为优化目标,最后给出算法流程。实验显示方向领导粒子群算法对粉壤土、细砂土测量比较接近真实值,评价指标较优。

In order to improve the effectiveness of Bragg grating in measuring soil moisture,the directional leader particle swarm optimization is proposed in this research.Firstly,the relationship between the central wavelength of fiber Bragg grating reflection spectrum and temperature variation is established.Secondly,the leader particle is selected based on the standard deviation of particle fitness,and different strategies are used to adjust the flight velocity of directional leader particle,with a shrinking factor to limit the possibility of particles leaving the search space.Thirdly,the optimization objective is to minimize the maximum refractive index modulation depth.Finally,the algorithm process is presented.The experimental results show that the directional leader particle swarm optimization provides measurements closer to the true values for silt loam soil and fine sand soil,with better evaluation indicator.