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Gas leakage source positioning method based on improved artificial fish swarm algorithm

An artificial fish swarm algorithm and gas leakage technology, applied in the direction of calculation, calculation model, artificial life, etc., can solve problems such as prone to oscillation, insufficient precision, and reduced search efficiency, so as to increase the possibility of jumping out of local optimum, Efficient positioning, reducing the effect of the search area

Pending Publication Date: 2021-03-05
CHINA JILIANG UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The standard artificial fish swarm algorithm uses a fixed field of view and step size. The accuracy of the solution in the later stage of the algorithm is not enough, and oscillation is prone to occur. The search areas between individual fish overlap, which reduces the search efficiency. value

Method used

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  • Gas leakage source positioning method based on improved artificial fish swarm algorithm
  • Gas leakage source positioning method based on improved artificial fish swarm algorithm
  • Gas leakage source positioning method based on improved artificial fish swarm algorithm

Examples

Experimental program
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Effect test

specific Embodiment 1

[0047] In the first embodiment, five unmanned aerial vehicles are used to search for the source of gas leakage. combine figure 1 , the specific implementation steps are as follows:

[0048] Step 1: Set up 5 drones in the area to be monitored;

[0049] Step 2: Use the divergence strategy to quickly find the plume;

[0050] Step 3: Determine whether the drone has found a plume, if found, go to step 4, otherwise go back to step 2;

[0051] Step 4: Use the improved artificial fish swarm algorithm to search for the source of gas leakage;

[0052] Step 5: update the position of each drone;

[0053] Step 6: Determine whether the location of the gas leakage source is successful, if successful, perform step 7, otherwise go back to step 4;

[0054] Step 7: Output the location of the gas leakage source.

[0055] The improved artificial fish swarm algorithm based on the curiosity model proposed in step 4, such as figure 2 shown, including the following steps:

[0056] Step 1: Ini...

specific Embodiment 2

[0068] In the second embodiment, the gas leakage concentration field is constructed by MATLAB software, and the standard artificial fish swarm algorithm and the improved artificial fish swarm algorithm are used to search for leakage sources.

[0069] like image 3 As shown, since the field of view and step size of the standard artificial fish swarm algorithm are fixed values, the oscillation phenomenon occurs in the later stage of the search, which cannot meet the problem of solution accuracy. like Figure 4 As shown, using the improved artificial fish swarm algorithm to search for leakage sources, the curiosity factor α 1 Under the effect of , as the search time increases, the field of view and step size gradually decrease, and the optimization is carried out with a smaller field of view and step size in the later stage of the search to avoid the phenomenon of oscillation.

[0070] like Figure 5 As shown, the fixed field of view and step size of the standard artificial fi...

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Abstract

The improved artificial fish swarm algorithm is creatively combined with an unmanned aerial vehicle cluster, and rapid and efficient positioning of a gas leakage source is achieved. A traditional fixed monitoring network method has limitation and is difficult to meet the positioning requirement of an existing positioning gas leakage source, a system with multiple unmanned aerial vehicle clusters has the advantages of maneuverability, flexibility, wide monitoring range and the like, the defects of an existing fixed monitoring station can be overcome by using the system as an environment monitoring platform, and active tracking and positioning of the harmful gas leakage source are facilitated. According to the smoke plume search strategy, an improved artificial fish swarm algorithm is adopted, a curiosity model is introduced on the basis of the standard artificial fish swarm algorithm, the search visual field and the moving step length of the unmanned aerial vehicle can be adjusted in aself-adaptive mode, and algorithm defects caused by the fact that the visual field and the step length are constant values in the standard artificial fish swarm algorithm are avoided.

Description

technical field [0001] The invention belongs to the field of environmental monitoring, and in particular relates to gas leakage positioning technology. Background technique [0002] With the rapid development of industrialization, the problem of urban air pollution is becoming more and more serious. Hazardous gas leakage accidents in chemical industry parks occur from time to time, seriously endangering people's lives. How to quickly and accurately locate the leakage source is the key to realize the targeted treatment of harmful gas leakage accidents in chemical plants. The existing leakage source location technology is based on fixed monitoring stations, vehicle-mounted monitoring stations and wireless sensor networks, and estimates the location of the leakage source based on the location of the monitoring station and the pollutant concentration information. Due to the limitation of ground conditions, the distribution of monitoring stations is often uneven or the source of...

Claims

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Application Information

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IPC IPC(8): G06N3/00G01M3/04
CPCG06N3/006G01M3/04
Inventor 刘振国丁涛孔凡玉
Owner CHINA JILIANG UNIV
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