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Dynamic risk assessment and fault detection using a multivariate technique

journal contribution
posted on 2023-05-19, 10:44 authored by Zadakbar, O, Imtiaz, S, Faisal KhanFaisal Khan
In the context of process safety, significant improvements are needed in fault detection methods, especially, in the areas of early detection and warning. In this article, a multivariate risk-based fault detection and diagnosis technique is proposed. The key elements of this technique are to eliminate faults that are not serious and to provide a dynamic process risk indication at each sampling instant. A multivariable residual generation process based on the Kalman filter has been combined with a risk assessment procedure. The use of the Kalman filter makes the method more robust to false alarms, which is an important aspect of any fault detection algorithm that targets the safety of a process. In addition, we consider significant differences in the severity of the faults associated with different process variables. We also take into account the varying intensity of damage caused by the increasing and decreasing rates of fault and the need to treat those cases differently.

History

Publication title

Process Safety Progress

Volume

32

Issue

4

Pagination

365-375

ISSN

1066-8527

Department/School

Australian Maritime College

Publisher

John Wiley & Sons, Inc.

Place of publication

USA

Rights statement

Copyright 2013 American Institute of Chemical Engineers

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in engineering