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针对隧道内运输危险品(天然气)车辆在行驶过程中发生小孔泄漏导致天然气扩散的情况,提出一种机器人主动嗅觉定位算法。采用赋值的方法随机搜索气体,并根据进化梯度搜索算法来跟踪气体,保证移动机器人一直沿着由低浓度烟羽到高浓度烟羽运动并最终定位到泄漏点。烟羽环境采用基于Fluent的天然气扩散物理数学模型。模型采用基于雷诺时均方程和标准k-ε方程的湍流模拟,用SIMPLEC算法对N-S方程进行求解,并采用组分输运来解决多组分流体的扩散问题,完成二维动态烟羽模型的建立后将烟羽数据导入Matlab,将烟羽模型产生的数据与模拟移动机器人相结合,依据设计所提出的主动嗅觉定位算法进行气味源搜索及气味源确认的仿真,为隧道内车辆运输危险品泄漏事故的抢救及最大限度地减少损失提供了参考。
Aimed at the diffusion of natural gas caused by leakage of small holes during the driving of dangerous goods (natural gas) in tunnel, an active olfactory localization algorithm for robot is proposed. The method of assignment is used to search the gas randomly and track the gas according to the evolutionary gradient search algorithm to ensure that the mobile robot always moves along the plume of low concentration plume to high concentration plume and finally locates the leak point. Smoke plume environment based on Fluent gas diffusion physics mathematical model. The model uses the turbulence simulation based on the Reynolds averaged equation and the standard k-ε equation. The SIM equation is solved by the SIMPLEC algorithm, and the component transport is used to solve the diffusion problem of the multi-component fluid. The two-dimensional dynamic plume model After the establishment of the smoke plume data into Matlab, the smoke plume model generated data combined with the simulation of mobile robots, according to the design of the active olfactory localization algorithm for odor source search and odor source confirmation simulation for the tunnel transport of dangerous goods Provide a reference for rescuing the spill accident and minimizing the loss.