基于气体扩散模型的信息趋向搜索方法研究
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河北工业大学电子信息工程学院 天津 300401

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TP273

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国家自然科学基金(42075129);河北省省级科技计划(19210404D);河北省高等学校科学研究项目(ZD2019010)


Research on Location Method of Infotaxis Research Algorithm on Gas Diffusion Model[ 基金项目:国家自然科学基金(42075129);河北省省级科技计划(19210404D);河北省高等学校科学研究项目(ZD2019010)]
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School of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China

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    摘要:

    释放源定位技术在防治有害气体泄漏与扩散中具有极其重要的意义。传统的定位算法依靠气味浓度梯度或风向进行搜索,在应对气味稀疏的湍流环境时则容易丢失目标而导致搜索失败,而信息趋向算法以搜索过程中获得的信息作为线索,在方向选择时追求熵降最大,搜索性能更好。首先,研究分析了常用气体扩散模型,后依其特点选择以气体湍流扩散模型为基础对信息趋向定位算法进行了仿真实现,验证了算法可行性。之后,通过对比实验研究了搜索距离长度对算法的影响,证明了信息趋向算法的鲁棒性。为进一步提升算法性能,分析了基本四边形路径单元、六边形路径单元及八点路径单元下的搜索特性,提出了改进型的四边形搜索路径单元,并通过大量对比实验验证其增强了算法的适应性,减小了搜索时间,提升了搜索效率。

    Abstract:

    The technology of release source location is of great significance in the prevention and control of harmful gas leakage and diffusion. The traditional location algorithm relies on the odor concentration gradient or wind direction to search, but when dealing with the turbulent environment with sparse odor, it is easy to lose the target and lead to the search failure, while the infotaxis algorithm takes the information obtained in the search process as a clue to maximize the entropy reduction when choosing the direction, and the search performance is better. First of all, the commonly used gas diffusion model is studied and analyzed, and then according to its characteristics, the infotaxis algorithm is simulated based on the gas turbulent diffusion model, and the feasibility of the algorithm is verified. After that, the influence of the search distance length on the algorithm is studied through comparative experiments, and the robustness of the infotaxis algorithm is proved. In order to further improve the performance of the algorithm, the search characteristics of basic quadrilateral path unit, hexagonal path unit and eight-point path unit are analyzed, and an improved quadrilateral search path unit is proposed. A large number of comparative experiments are carried out to verify that the proposed search path unit enhances the adaptability of the algorithm, reduces the search time and improves the search efficiency.

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邓思丹,范书瑞,张 艳.基于气体扩散模型的信息趋向搜索方法研究[J].电子测量技术,2022,45(12):58-65

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  • 在线发布日期: 2024-04-17
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