A study of a two phases medium in pipe vessel using gaussian filter method and k-NN classifier

  • Authors:

  • Mohd Rizal Manan;Muhammad Naufal Mansor;Mohd Hafiz Fazalul Rahiman;Ruzairi Abdul Rahim;Sazali Yaacob

  • Affiliations:

  • Intelligent Signal Processing Group ISP, Universiti Malaysia Perlis, Jalan Kangar-Alor Setar, Seriab, Kangar, Perlis, Malaysia;Intelligent Signal Processing Group ISP, Universiti Malaysia Perlis, Jalan Kangar-Alor Setar, Seriab, Kangar, Perlis, Malaysia;Process Tomography Research Group PROTOM, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia;Process Tomography Research Group PROTOM, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia;Intelligent Signal Processing Group ISP, Universiti Malaysia Perlis, Jalan Kangar-Alor Setar, Seriab, Kangar, Perlis, Malaysia

  • Venue:
  • Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we present the existence and uniqueness of solutions to the stochastic problem to determine two phase level of gas and water in the industrial pipeline. In order to distinguish the level phase in a vessel such as high, medium, and low a mechanism of Gaussian Filter Method was proposed in this study. The k-weights of the statistical features were adjusting by the k-NN Classifier and separate the categories for training from the various parameters. Within this study, 6 statistical used features were employed for training. In addition, a time-frequency parameter obtained by continuous signal was also used to identify the pulse during the recognition process. For the classification of all phase level, the average accuracy was higher than 90.0% for the whole data set. Finally, in order to provides the opportunity of obtaining quantitative and real time data on two phase media within a full scale industrial process, such as filtration, without the need of processes interruption, tomography methods answer it all.