郑钢丰, 夏皖东, 周凯峰, 闫迎春. 基于超声相控阵技术的重介旋流器内壁磨损研究[J]. 北京工业大学学报, 2018, 44(5): 796-800. DOI: 10.11936/bjutxb2017090003
    引用本文: 郑钢丰, 夏皖东, 周凯峰, 闫迎春. 基于超声相控阵技术的重介旋流器内壁磨损研究[J]. 北京工业大学学报, 2018, 44(5): 796-800. DOI: 10.11936/bjutxb2017090003
    ZHENG Gangfeng, XIA Wandong, ZHOU Kaifeng, YAN Yingchun. Research on the Inwall Wear of Heavy Medium Cyclone Based on Ultrasonic Phased Array Technology[J]. Journal of Beijing University of Technology, 2018, 44(5): 796-800. DOI: 10.11936/bjutxb2017090003
    Citation: ZHENG Gangfeng, XIA Wandong, ZHOU Kaifeng, YAN Yingchun. Research on the Inwall Wear of Heavy Medium Cyclone Based on Ultrasonic Phased Array Technology[J]. Journal of Beijing University of Technology, 2018, 44(5): 796-800. DOI: 10.11936/bjutxb2017090003

    基于超声相控阵技术的重介旋流器内壁磨损研究

    Research on the Inwall Wear of Heavy Medium Cyclone Based on Ultrasonic Phased Array Technology

    • 摘要: 针对重介旋流器内壁受物料磨损而常规检测方式无法实时、高效检出缺陷的问题,详细地介绍了超声相控阵技术的工作过程及成像原理,通过对重介旋流器模型的试验研究,可知检测设备显示屏调色板上的不同颜色代表反射回波的强弱,即用不同颜色代表扫查区域各处的声压强弱,而声压的强弱所反映的被检测构件内部缺陷形态是实时显示的,因而超声相控阵技术能对重介旋流器内壁磨损缺陷实时成像显示且检测项目的误差均在8%以内.

       

      Abstract: As the main equipment selected by coal separation plant, for dense-medium cyclone, its inner-wall abrasion directly influences its separation efficiency and continuity of production. In the paper, to solve the problem that conventional detection methods cannot efficiently check out real-time flaws in heavy medium cyclone inwall which is worn by ore pulp, the working process and imaging principle of ultrasonic phased array technology were described in detail. Furthermore, through the experimental study on heavy medium cyclone model, it demonstrated that the color palette on the detection device used different colors to represent strength of reflected signals, i.e. different colors were used to represent sound pressures in all scanning regions and the components of internal defects reflected by sound pressures were real-time display. So it is concluded that ultrasonic phased array technology can present wearing flaws in heavy medium cyclone inwall by real-time imaging and the error of test items is less than 8%.

       

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