基于ECT技术的充填管道内固液两相流仿真方法研究

矿山充填过程中,管道中产生的结块和充填料浆中夹杂的废石会造成堵管或爆管等严重安全事故,制约了矿山充填技术的应用与发展,所以及时对管道内堵塞结块及废石的方位和大小进行检测,对矿山充填的安全稳定有着重要意义。以电容层析成像(ECT)技术为基础,研究了矿山充填管道的检测方法。针对传统ECT重建算法成像质量差、精度低等问题,提出了一种适用于充填管道内固液两相流检测的基于极限学习机和卷积神经网络的ECT图像重建方法。该图像重建网络由单隐藏层前馈神经网络和图像预测网络两部分组成。利用极限学习机建立电容数据与介电常数值的映射关系,并通过图像预测网络完成对图像的重建。通过充填管道仿真试验,证明了该方法不仅能够有效减少重建图像的伪影和变形,提高图像重建准确度,而且对充填管道中可能出现的复杂情况有较好的重建效果。所提出的ECT图像重建方法对于矿山充填管道内存在的堵塞结块及废石的检测有很好的效果,可以有助于推动ECT技术在充填管道检测领域的应用和推广。

Study on the Simulation Method of Solid-liquid Two-Phase Flow of Filling Pipeline Based on ECT Technology

In the process of mine filling,the pipe of agglomeration and inclusions of waste rock filling pulp causes blocking pipe or tube and so on serious safety accidents,restricted the application and development of mine filling technology,so in a timely manner to the pipe blockage agglomerate and detect the location and size of waste rock has great significance to the security and stability of mine filling.Based on the technology of Electrical Capacitance Tomography (ECT),the detection method of mine filling pipeline was studied.Aiming at the problems of poor imaging quality and low accuracy of the traditional ECT reconstruction algorithm,a new ECT image reconstruction method based on extreme learning machine and convolutional neural network was proposed,which was suitable for the detection of solid-liquid two-phase flow in filling pipes.The image reconstruction network consists of two parts:a hidden layer feedforward neural network and an image prediction network.The mapping relationship between capacitance data and dielectric constant value was established by using extreme learning machine,and the image was reconstructed by image prediction network.Through the simulation experiment of filling pipe,it is proved that this method can not only effectively reduce the artifact and deformation of reconstructed image,improve the reconstruction accuracy,but also have a good reconstruction effect for the complex situation that may occur in filling pipe.The ECT image reconstruction method proposed in this study has a good effect on the detection of clogging and caking and waste rock existing in the mine filling pipeline,which can improve the application and promotion of ECT technology in the filling pipeline detection.