Abstract:

Screw conveyor is widely used in chemical industry, metallurgy, grain and transport and other fields, and the movement of its screw blade has a direct impact on the conveying state. Most of the closed transport, and harsh operating environment, after a long time of work, easy to deformation of the spiral blade, or even broken shafts and other accidents, through real-time detection of the movement speed of the spiral blade, can be timely access to the operating status of the screw conveyor. For the lack of effective means of detecting the movement speed of the spiral blade, an electrostatic sensor was designed, and the problem of serious noise interference of the electrostatic signal was proposed based on the empirical mode decomposition (empirical mode decomposition, EMD) of the electrostatic signal filtering method, and the filtered signals could be obtained through the mutual correlation calculation of the rising speed of the spiral blade. The rising speed of the spiral blade could be obtained by the cross-correlation calculation of the filtered signal. The experimental results showed that the electrostatic signal detected at the pipe wall during the spiral conveying process was periodic and consistent with the frequency of the spiral blade passing through the electrodes, and the relative error of the spiral speed measurement was 0.67% after the filtering process based on EMD and the correction of the spiral speed.

Key words: crew conveyor, electrostatic sensor, empirical mode decomposition, measurement, particulate material, multiphase flow

摘要：

螺旋输送机广泛应用于化工、冶金、粮食和运输等领域，其螺旋叶片的运动对输送状态有直接的影响。多采用封闭运输，且运行环境恶劣，经过较长时间工作后，易出现螺旋叶片变形甚至断轴等事故。通过实时检测螺旋叶片的运动速度，可及时获得螺旋输送机的运行状态。针对缺少有效的螺旋叶片运动速度检测手段的问题，本文设计了静电传感器，针对静电信号噪声干扰严重的问题，提出了基于经验模态分解（empirical mode decomposition，EMD）的静电信号滤波处理方法，对滤波处理后的信号通过互相关计算，可以获得螺旋叶片的上升速度。实验结果表明：螺旋输送过程中，管壁处检测到的静电信号具有周期性，且与螺旋叶片经过电极的频次一致，经基于EMD的滤波处理和螺旋转速修正，螺旋转速测量相对误差为0.67%。

关键词: 螺旋输送机, 静电传感器, 经验模态分解, 测量, 颗粒物料, 多相流