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An infrared optical tomography based on independent component analysis for measurement in turbid liquid

机译:基于独立成分分析的红外光学层析成像技术在浑浊液体中的测量

摘要

Process tomography is a tool that provides an unperturbed way to examine and investigate the internal behaviour of flow process. The tool has successfully made a beneficial contribution in measuring parameters such as mass flow rate, concentration profile and particle sizing. Among the parameters that can be inspected using tomography technique is the turbidity level of water. Most of the turbidimeters in the market are in the form of point sensor, which means the meter needs to be put on the water sample. This kind of measurement is unsuitable for industrial flow since it disturbs the flow. The investigation in distinguishing the spatial distribution in two-phase flow attracts a major interest in industry. In beverage industry, the existing of gas bubble in opaque liquid such as milk has degraded the quality of product. This thesis presents an investigation into the application of optical tomography through the use of Independent Component Analysis (ICA) method to estimate turbidity level of water and explore the presence of gas bubble in contaminated water. The system consists of eighteen infrared transmitters and eighteen receivers in which the light projection is designed in fan beam mode. An ICA algorithm has been implemented to analyse the data and the LabVIEW software was used to construct 18 x 18 pixels of concentration profile. In water turbidity experiment, several volumes of green colour ingredients were mixed together with pure water for varying the turbidity level of the water. For gas bubble's investigation, three types of flow conditions were studied: low bubble flow, medium bubble flow and high bubble flow. The behaviour of gas bubbles was investigated in contaminated water in which the water sample was prepared by adding 25 ml of colour ingredients into 3 liters of pure water. The result shows that the application of ICA has enabled the system to estimate the turbidity level and detect the presence of gas bubbles in contaminated water. This information is expected to provide vital information on the flow inside the pipe and hence, could be very significant in increasing the accuracy of the process industries.
机译:过程层析成像是一种工具,它提供了一种不受干扰的方式来检查和调查流过程的内部行为。该工具已成功地在测量参数(例如质量流量,浓度分布和颗粒大小)方面做出了有益的贡献。可以使用断层扫描技术检查的参数包括水的浊度。市场上的大多数浊度计都是点传感器的形式,这意味着仪表需要放在水样上。由于这种测量会干扰流量,因此不适合工业流量。区分两相流中的空间分布的研究引起了工业界的极大兴趣。在饮料工业中,牛奶等不透明液体中气泡的存在降低了产品质量。本文通过独立分量分析(ICA)方法对光学层析成像技术的应用进行了研究,以估计水的浊度水平并探讨受污染水中气泡的存在。该系统由十八个红外发射器和十八个接收器组成,其中的光投射以扇形光束模式设计。已经实施了ICA算法来分析数据,并且使用LabVIEW软件构建了18 x 18像素的浓度分布图。在水浊度实验中,将几种体积的绿色成分与纯净水混合在一起,以改变水的浊度水平。为了研究气泡,研究了三种流动条件:低气泡流量,中气泡流量和高气泡流量。在受污染的水中研究了气泡的行为,在受污染的水中,通过将25毫升有色成分添加到3升纯水中来制备水样品。结果表明,ICA的应用使系统能够估计浊度水平并检测污水中气泡的存在。预计该信息将提供有关管道内部流动的重要信息,因此,在提高加工行业的准确性方面可能非常重要。

著录项

  • 作者

    Mohd. Khairi Mohd. Taufiq;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
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