Development of non-linear fault detection system using Cusum-based technique applied to a pilot distillation column

Yahya Chetouani

International Journal of Industrial and Systems Engineering, 2011, vol. 7, issue 4, 498-517

Abstract: Early detection of faults (FD) is important in chemical industry since a lot of damage and loss can result before a fault present in the system is detected. In this paper, a real-time system for detecting changes in dynamic systems is designed. The main contribution consists in the design of a simplified procedure of the incident detection scheme through a combination of the optimisation property of cumulative sum and a neural adaptive black-box identification. The simplicity of the developed neural model, under all regimes (i.e. steady-state and unsteady state), used in this case is realised by means of a non-linear auto-regressive with exogenous input model and by an experimental design. The performance of the proposed FD system has been tested on a real plant as a distillation column. Then, the FD system has been tested under real anomalous conditions. The experimental results demonstrate the robustness of the FD method.

Keywords: safety; reliability; functioning risk; fault detection; Cusum; cumulative sum; neural networks; dynamic systems; distillation column; chemical industry. (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=39672 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:7:y:2011:i:4:p:498-517

Access Statistics for this article

More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().