Title of article :
Feature Extraction by PCA in Unit 106 Compressors in South Pars Gas Refinery
Author/Authors :
rasaienia, abbas islamic azad university, north tehran branch - department of electrical and computer engineering, Tehran, Iran , shams shamsabad farahani, shoorangiz islamic azad university, islamshahr branch - department of electrical engineering, Islamshahr, Iran , ghaffarpour, shahriar islamic azad university, north tehran branch - department of electrical and computer engineering, Tehran, Iran
Abstract :
The vast number of sensors, the high volume of data, and the high speed of information storage makes data analysis difficult. Moreover, due to the high volume of data, analysis and information extraction is very complex and sometimes impossible. In order to increase the analysis speed and minimize the analysis period, information processing methods are employed. Principal Component Analysis (PCA) is one of the methods used for feature extraction, dimensional reduction, and analysis speed. In this paper, feature extraction and dimensional reduction is studied in phases 20 and 21 of unit 106 compressors of south Pars gas refinery. The efficiency of our proposed approach is demonstrated on SGT-600 Siemens compressors.
Keywords :
Feature extraction , Principal Component Analysis (PCA) , Compressor , South Pars phases 20 and 21
Journal title :
Majlesi Journal of Mechatronic Systems
Journal title :
Majlesi Journal of Mechatronic Systems
