Page 184 - 《应用声学》2024年第6期
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第 43 卷 第 6 期                                                                       Vol. 43, No. 6
             2024 年 11 月                         Journal of Applied Acoustics                 November, 2024

             ⋄ 研究报告 ⋄



                 一种声速识别空气成分波动的自监督学习方法






                                                  滕旭东     1†   滕博欣     2


                                         (1 上海工程技术大学电子电气工程学院           上海   201620)
                                                (2 上海市松江二中      上海  201620)

                摘要:实际空气成分比较复杂,其声速的大小与标准空气的计算值有较大差异。文中根据维里展开式推导的
                声速方程,分析实际空气成分的浓度微量波动与声速变化定量关系。基于理论计算值,对比声速实测值,提出
                一种基于声速差值的自监督学习方法分析空气成分波动。该方法首先计算各个时刻声速差值的分布距离,接
                着确定分布最聚集区域,进行统计声速差发生比例,最后利用概率分布变化来发现空气成分,尤其微量成分的
                波动。实测结果表明:声速差发生概率曲线较好地反映空气成分浓度变化的起始、扩散和累积等阶段,通过发
                生概率 P 值分布能够对空气成分波动状态进行识别和实时监控。
                关键词:声速;维里展开式;成分波动;概率分布
                中图法分类号: O422.1          文献标识码: A          文章编号: 1000-310X(2024)06-1360-06
                DOI: 10.11684/j.issn.1000-310X.2024.06.019




                Self-supervised learning for identifying variations of air composition base on
                                                    speed of sound



                                             TENG Xudong   1   TENG Boxin  2


                (1 School of Electronic and Electric Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)
                                    (2 Shanghai Songjiang No. 2 High School, Shanghai 201620, China)

                 Abstract: As the actual composition of air is quite complex, the value of its speed of sound differs significantly
                 from the calculated value for standard air. This article discusses the calculation of the speed of sound for
                 standard air, furthermore analyze quantitative relationship between actural air composition and changes in the
                 speed of sound. Theoretical results show that air composition, especially trace components, have a very small
                 contribution to variation of the speed, thus making it difficult to discern slight fluctuations in the composition.
                 To address this, a supervised algorithm for monitoring speed of sound error distribution is proposed to analyze
                 air composition fluctuations. Firstly, the distance matrix of the difference between the measured and calculated
                 values of the speed of sound is calculated, then the proportion of error values is determined, and finally, the
                 distribution probability is analyzed to determine changes in air composition. This algorithm effectively tracks
                 the beginning, diffusion, and accumulation of concentration changes and enables prediction and monitoring of
                 air composition fluctuations quite pricisely.
                 Keywords: Speed of sound; Virial expansions; Composition fluctuations; Probability distributions


             2023-08-07 收稿; 2023-09-13 定稿
             作者简介: 滕旭东 (1971– ), 男, 上海人, 博士, 研究方向: 声传播与检测。
              通信作者 E-mail: txd19@163.com
             †
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