基于图像识别的微细粒子静电捕集效率评价方法

发布时间：2018-01-14 13:28

  本文关键词：基于图像识别的微细粒子静电捕集效率评价方法　出处：《高电压技术》2016年05期 　论文类型：期刊论文

  更多相关文章： 电除尘器 图像识别 粒子荷电 捕集效率 供电形式

【摘要】：通过采集并分析电除尘器内部流场和粒子分布动态和静态图像的方法,对微细粒子捕集效率进行评价。实验电除尘器箱体采用有机玻璃材质,放电极为芒刺型,测试粒子源为人工烟气,烟气入口流速为0.4 m/s。实验中对放电极分别施加直流和脉冲高电压,采集相应流场变化的图像和电除尘器入风口与出风口粒子分布的图像进行处理和分析。实验结果表明:提出的动静态图像处理方法能够实时、有效地实现微细粒子观测和荷电状态评价。直流供电下,流场在电压升至 8 kV开始呈现漩涡变化;而施加脉冲高压时,峰值电压达到 30 kV时产生漩涡。电压在 22 kV以下时,直流供电粒子捕集效率较高;电压超过 22 kV后,脉冲供电粒子捕集效率高于直流,最终捕集效率可达91.23%。
[Abstract]:By collecting and analyzing the dynamic and static images of the flow field and particle distribution in the electrostatic precipitator, the collection efficiency of fine particles is evaluated. The chamber of the experimental electrostatic precipitator is made of plexiglass, and the discharge is extremely burr. The particle source is artificial smoke, and the flue gas inlet velocity is 0.4 m / s. In the experiment, DC and pulse high voltage are applied to the discharge electrode, respectively. The images of the corresponding flow field changes and the distribution of particles in the air inlet and outlet of the electrostatic precipitator are processed and analyzed. The experimental results show that the proposed dynamic and static image processing method can be used in real time. The micro-particle observation and charge state evaluation are realized effectively. Under DC power supply, the flow field begins to appear whirlpool change when the voltage rises to 8 kV. When the peak voltage reaches 30 kV and the voltage is below 22 kV, the particle trapping efficiency of DC power supply is higher. When the voltage exceeds 22 kV, the particle trapping efficiency of pulse supply is higher than that of DC, and the final trapping efficiency can reach 91.23.
【作者单位】： 大连理工大学电气工程学院;
【基金】：国家国际科技合作专项(2014DFR50880)~~
【分类号】：X701.2;TP391.41
【正文快照】： 0引言1电除尘器作为一种高效的除尘设备,被广泛应用于大气颗粒物的控制中。然而,由于粒子荷电机理等原因,使得电除尘器针对微细粒子(平均粒径10μm)的捕集效率很低[1-4]。因此很多研究者采用不同供电形式来提高粒子捕集率[5-7]。放电极施加高电压时,电离气体中的带电粒子在外，

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