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Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization

机译:使用蚁群优化在海上平台上天然气泄漏来源的多罗频搜索方法

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摘要

Natural gas leakage on offshore platforms has a great impact on safety production, and effective and reasonable leakage detection methods can prevent the harm caused by natural gas leakage. This article proposes a method based on ant colony optimization (ACO) for multirobots to collaboratively search for leaking natural gas sources on offshore platforms. First, analyze the structure and environment of the offshore platform, use Fluent software to simulate the diffusion process of natural gas leaked from the platform, and establish a diffusion model of natural gas leaked from various aspects, such as the layout of different platforms, the number of leaked gas sources, and the concentration of leaked gas sources. In terms of multirobot cooperative control, we analyzed and improved the ant colony algorithm and proposed a multirobot cooperative search strategy for gas search, gas tracking, and gas source positioning. The multirobot search process was simulated using MATLAB software, and the robot on the detection effect of multirobots was analyzed in many aspects, such as quantity, location of leak source, and a number of leak sources, which verified the feasibility and effectiveness of the multirobot control strategy based on optimized ACO. Finally, we analyze and compare the two control algorithms based on ACO and cuckoo search algorithm (CSA). The results show that the ACO-based multirobot air source positioning effect is significantly better than CSA.
机译:海上平台上的天然气泄漏对安全生产产生了很大影响,有效和合理的泄漏检测方法可以防止天然气泄漏造成的伤害。本文提出了一种基于蚁群优化(ACO)的方法,用于多机罗管,协同搜索海上平台上的天然气源。首先,分析海上平台的结构和环境,使用流畅的软件来模拟从平台泄漏的天然气的扩散过程,并建立了从各个方面泄露的天然气的扩散模型,例如不同平台的布局,泄漏的气体源数,以及泄漏气体源的浓度。在多罗频协作控制方面,我们分析和改进了蚁群算法,提出了一种用于天然气搜索,气体跟踪和气体源定位的多机罗协同搜索策略。使用MATLAB软件模拟多机罗管搜索过程,并且在多个方面分析了多机罗多波特检测效果的机器人,例如泄漏源的数量,位置,以及许多泄漏来源,这验证了多机罗的可行性和有效性基于优化ACO的控制策略。最后,我们基于ACO和Cuckoo搜索算法(CSA)分析和比较了两个控制算法。结果表明,基于ACO的多摩托车空气源定位效果明显优于CSA。

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