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首页» 过刊浏览» 2021» Vol.6» Issue(4) 614-625     DOI : 10.3969/j.issn.2096-1693.2021.04.043
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基于气体扩散模型的天然气泄漏场景下无人机自主飞行 控制算法研究
温凯,王伟 ,谢宜峰 ,韩旭
1 中国石油大学(北京)城市油气输配技术北京市重点实验室,北京 102249 2 深圳市大疆创新科技有限公司,深圳 518108
UAV autonomous flight control in natural gas leakage scenarios based on a gas diffusion model
WEN Kai , WANG Wei , XIE Yifeng, HAN Xu
1 Beijing Key Laboratory of Urban Oil and Gas Transmission and Distribution Technology, China University of Petroleum-Beijing, Beijing 102249, China 2 Shenzhen DJI Innovation Technology Co., Ltd., Shenzhen 518108, China

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摘要  无人机沿着真实的气体泄漏场中的等值面飞行,飞行轨迹比较平滑, 所描绘的轮廓比较完整地包含了设定等值面,解决了之前算法导致的 无人机断飞、倒飞、偏离航线等问题。加入误差分析使得最初理想气 体模型更接近于实际环境的浓度值,但不利于飞机飞行,而再将误差 模型转化为随坐标点变化的理想气体模型,使得仿真过程既没有影响 浓度计算的准确性,也减小了飞行的压力,使得飞机能够达到很好的 飞行效果,实现设定的沿等浓度面飞行的测绘任务。
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关键词 : 无人机;气体泄漏;高斯烟羽模型;路径规划;自主检测
Abstract
As natural gas accounts for an increasing proportion of energy resources, there are more and more natural gas  
supporting facilities, so the demand for emergency equipment is also increasing. When a natural gas leakage accident occurs,  
the traditional detection methods not only have potential safety hazards, but the detection results are also used for post-mortem  
analysis, and there is no real-time feedback of on-site results. In response to the above important problems, drones were used to  
compensate for the poor safety and timeliness of traditional detection methods in this paper. Based on the Gaussian plume gas  
diffusion model, the real-time leakage site can be calculated by concentration distribution, and the autonomous flight algorithm  
was used to control the drone to fly along the on-site dangerous concentration surface to complete concentration surveying and  
mapping or other on-site surveying and mapping tasks. The research also analyzed the influence of each influencing factor on  
the gas concentration distribution in the model and compared the results. In addition, random errors were introduced to simulate  
the gas diffusion distribution under real conditions. In this research, the autonomous flight algorithm of UAVs puts forward a  
concept of "calculating while flying", which uses real-time calculation of the gas diffusion model to guide the flight of the UAVs.  
The gas distribution will be updated and the flight route will be optimized while the UAV is still in flight. The gas diffusion  
model part uses the concentration points measured in real time by drones to correct the error of initial results calculated by the  
Gaussian gas diffusion model. Finally, the UAV autonomous flight control proposed in this paper was verified in an experimental  
case. The UAV autonomous flight algorithm based on the gas diffusion model can realize the task of flying along the dangerous  
concentration surface, and complete the specified dangerous concentration surface surveying and mapping task, which is very  
significant for on-site accident guidance.


Key words: UAV, gas leakage, Gaussian model, path planning, autonomous detection
收稿日期: 2021-12-29     
PACS:    
基金资助:国家重点研发计划( 项目编号 2017YFC0805800) 资助
通讯作者: kewin1983@126.com
引用本文:   
温凯, 王伟, 谢宜峰, 韩旭. 基于气体扩散模型的天然气泄漏场景下无人机自主飞行控制算法研究. 石油科学通报, 2021, 04: 614-625 WEN Kai, WANG Wei, XIE Yifeng, HAN Xu. UAV autonomous flight control in natural gas leakage scenarios based on a gas diffusion model. Petroleum Science Bulletin, 2021, 04: 614-625. doi: 10.3969/j.issn.2096-1693.2021.04.043
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