TITLE

FUZZY BASED NONLINEAR PRINCIPAL COMPONENT ANALYSIS FOR PROCESS MONITORING

AUTHOR(S)
Derakhshandeh, Ahmad; Sadjadian, Hooman; Poshtan, Javad
PUB. DATE
May 2012
SOURCE
International Journal of Control Theory & Computer Modeling;May2012, Vol. 2 Issue 3, p1
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Nowadays, process monitoring to improve product quality and safety has become an important issue in control engineering. One of the most used methods in process monitoring is principal component analysis. This method uses process data to make process model with lower dimension than original dimension. In this paper, a new PCA based monitoring is proposed that uses fuzzy logic capability. The reason to use fuzzy logic is its good ability to approximate nonlinear function with arbitrary accuracy. The new method is tested on Tennessee Eastman Process.
ACCESSION #
79920339

 

Related Articles

  • Knowledge discovery in steel bar rolling mills using scheduling data and automated inspection. Agarwal, Kuldeep; Shivpuri, Rajiv // Journal of Intelligent Manufacturing;Dec2014, Vol. 25 Issue 6, p1289 

    There are various surface defects which occur during the hot rolling of steels. It is difficult to correctly identify and control these defects due to the different inspection techniques on different materials and sizes. Also, the statistical data analysis techniques typically used like the...

  • Variable structure control of electrohydraulic servo systems using fuzzy CMAC neural network. Jiang Zhiming; Wang Shengwei; Lin Tingqi // Transactions of the Institute of Measurement & Control;2003, Vol. 25 Issue 3, p185 

    This paper presents a novel variable structure control (VSC) scheme based on the use of fuzzy cerebellar model articulation controller (FCMAC) for the control of electrohydraulic position servo systems. FCMAC is used to develop an adaptive equivalent control law by learning the uncertainties...

  • Model-based fault diagnosis in technical processes. Frank, P.M.; Ding, S.X.; Marcu, T. // Transactions of the Institute of Measurement & Control;2000, Vol. 22 Issue 1, p57 

    In this paper the state-of-the-art developments model-based fault diagnosis in technical processes are reviewed. Attention is focused upon both the analytical approaches that make use of the quantitative models and the knowledge-based approaches using qualitative models. Basic concepts and the...

  • Robust chemical process monitoring based on CDC‐MVT‐PCA eliminating outliers and optimally selecting principal component. Huang, Junping; Yan, Shifu; Yan, Xuefeng // Canadian Journal of Chemical Engineering;Jun2019, Vol. 97 Issue 6, p1848 

    In chemical process monitoring based on principal component analysis (PCA), sampling data with outliers and optimally select principal components are two challenging problems that have a main effect on monitoring performance. Given this situation, firstly, a novel outlier detection method, i.e.,...

  • Online incipient fault diagnosis based on Kullback‐Leibler divergence and recursive principle component analysis. Chai, Yi; Tao, Songbing; Mao, Wanbiao; Zhang, Ke; Zhu, Zhiqin // Canadian Journal of Chemical Engineering;May2018, Vol. 96 Issue 5, p1236 

    A correction to the article "Online Incipient Fault Diagnosis Based on Kullback-Leibler Divergence and Recursive Principal Component Analysis" in the October 2017 issue is presented.

  • Early Quality Prediction: A Case Study in Telecommunications. Khoshgoftaar, Taghi M.; Allen, Edward B.; Kalaichelvan, Kalai S.; Goel, Nishith // IEEE Software;Jan96, Vol. 13 Issue 1, p65 

    Deals with the quality prediction in software development. Classification techniques used to identify fault-prone software; Description of a software-quality model; Standardization of software metrics; Discussion of principal components analysis.

  • An approach to the development of commonsense knowledge modeling systems for disaster management. Mendis, D.; Karunananda, Asoka; Samaratunga, Udaya; Ratnayake, Uditha // Artificial Intelligence Review;Aug2007, Vol. 28 Issue 2, p179 

    Knowledge is the fundamental resource that allows us to function intelligently. Similarly, organizations typically use different types of knowledge to enhance their performance. Commonsense knowledge that is not well formalized modeling is the key to disaster management in the process of...

  • A Robust Segmentation Approach for Noisy Medical Images Using Fuzzy Clustering With Spatial Probability. Beevi, Zulaikha; Sathik, Mohamed // International Arab Journal of Information Technology (IAJIT);Jan2012, Vol. 9 Issue 1, p74 

    Image segmentation plays a major role in medical imaging applications. During last decades, developing robust and efficient algorithms for medical image segmentation has been a demanding area of growing research interest. The renowned unsupervised clustering method, Fuzzy C-Means (FCM) algorithm...

  • A Video Based Indian Sign Language Recognition System (INSLR) Using Wavelet Transform and Fuzzy Logic. Kishore, P. V. V.; Rajesh Kumar, P. // International Journal of Engineering & Technology (0975-4024);Oct/Nov2012, Vol. 4 Issue 5, p537 

    This paper proposes a complete skeleton of isolated Video Based Indian Sign Language Recognition System (INSLR) that integrates various image processing techniques and computational intelligence techniques in order to deal with sentence recognition. The system is developed to improve...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics