Veri madenciliği kümeleme algoritmaları kullanarak arıza dayanımlı denetim sistemi tasarımı

Umut Altınışık; Mehmet Yıldırım

doi:10.16984/saufbed.70344

Research Article

Fault tolerant control system design by using clustering algorithms of data mining

Year 2013, Volume: 17 Issue: 1, 9 - 16, 01.04.2013

Umut Altınışık Mehmet Yıldırım

Abstract

In this study, two clustering algorithms and their success in fault isolation have been investigated in order to use in our fault tolerant control (FTC) system. With so many applications used today, the mathematical model of the system cannot be completely established. Therefore, in this study, fault detection and isolation (FDI) is realized by using knowledge-based methods, without the need for any mathematical model. Sensor data, which are taken offline by FDI, are clustered to create knowledge base by means of k-means and farthest first traversal algorithm (FFTA), respectively. The results obtained by the two algorithms are compared and FFTA has found to be more successful in fault tolerance.

Keywords

Fault tolerant control, fault detection and identification, k-means, three tank, data mining

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