个人信息Personal Information
副教授
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:电气工程学院
学科:电工理论与新技术. 电力系统及其自动化
办公地点:静电与特种电源研究所305室
联系方式:wangjinjun@dlut.edu.cn
基于图像识别的微细粒子静电捕集效率评价方法
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发表时间:2022-10-10
发表刊物:高电压技术
卷号:42
期号:5
页面范围:1455-1462
ISSN号:1003-6520
摘要:Fine particle collection efficiency is evaluated by obtaining and
analyzing dynamic flow field inside electrostatic precipitator (ESP) and
dynamic/static images of particles distribution. The side-wall of
electrostatic precipitator consists of acrylic material, and the
discharge electrodes are spike-type. The man-made smoke is considered to
be the particle source for testing, and the flow velocity of the inlet
is 0.4 m/s. In the experiment, the discharge electrode is energized with
DC and short pulsed high voltage, respectively. Then, the images which
contain the flow field changing and smoke particles distribution of
inlet and outlet of ESP are processed and analyzed. The experimental
results indicate that the method of processing dynamic and static images
can be used to observe fine particles and evaluate particles charging
status timely and effectively. Energized with negative DC high voltage,
the vortexes of the flow field begin to appear when the voltage value
rises to -8 kV. While energized with negative short impulses high
voltage, the vortexes appear when the peak voltage value rises to -30
kV. The particles collection efficiency with DC energization is higher
when the voltage value is lower than -22 kV. While the voltage value
exceeds -22 kV, the particles collection efficiency energized by
impulses high voltage is higher than that by DC energization, and the
final collection efficiency can be up to 91.23%.
备注:新增回溯数据