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

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 searc...

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Main Authors: Tao Ma, Shuhai Liu, Huaping Xiao
Format: Article
Language:English
Published: SAGE Publishing 2020-09-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.1177/1729881420959012
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spelling doaj-d5286f7ef9d3427abd9832ed7c0c15032020-11-25T03:56:54ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142020-09-011710.1177/1729881420959012Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimizationTao Ma0Shuhai Liu1Huaping Xiao2 College of Mechanical and Transportation Engineering, , Beijing, China Laboratory of Petroleum and Petrochemical Robot, , Beijing, China Laboratory of Petroleum and Petrochemical Robot, , Beijing, ChinaNatural 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.https://doi.org/10.1177/1729881420959012
collection DOAJ
language English
format Article
sources DOAJ
author Tao Ma
Shuhai Liu
Huaping Xiao
spellingShingle Tao Ma
Shuhai Liu
Huaping Xiao
Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
International Journal of Advanced Robotic Systems
author_facet Tao Ma
Shuhai Liu
Huaping Xiao
author_sort Tao Ma
title Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
title_short Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
title_full Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
title_fullStr Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
title_full_unstemmed Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
title_sort multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8814
publishDate 2020-09-01
description 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.
url https://doi.org/10.1177/1729881420959012
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