eprintid: 16477
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/64/77
datestamp: 2023-12-19 03:22:59
lastmod: 2023-12-19 03:22:59
status_changed: 2023-12-19 03:06:19
type: conference_item
metadata_visibility: show
creators_name: Ali, H.
creators_name: Maulud, A.S.
creators_name: Zabiri, H.
creators_name: Nawaz, M.
creators_name: Ismail, L.
title: Fault diagnosis by using multi-scale signed directed graph
ispublished: pub
note: cited By 2; Conference of 5th Innovation and Analytics Conference and Exhibition, IACE 2021 ; Conference Date: 23 November 2021 Through 24 November 2021; Conference Code:182132
abstract: In the chemical process industry, product quality and plant safety are maintained by controlling process variables. A massive number of state variables are involved in decision making the characteristics of propagating failures in the chemical system. The Signed Directed Graph (SDG) is a qualitative graphical model that has been widely applied in chemical process industries for fault diagnosis. It describes and represents the causal relations between the process variables and their effect relations in systems. The conventional SDG fault diagnosis algorithm is a single-scale fault representation origin, and it cannot effectively solve multiple fault representation origins. Due to the qualitative nature of SDG, it produces spurious and erroneous interpretations when the process variable is going through a non-single transition. The wavelet-based SDG (MSSDG) method is a successful methodology because it effectively separates determinist and stochastic characteristics. The MSSDG fault diagnosis modelling is applied to a continuous stirred tank reactor system (CSTR) to discuss thoroughly. In short, new model studies on processes from the petrochemical industries and research on implementing the multilevel modelling approach of signed directed graphs are intended. © 2022 Author(s).
date: 2022
publisher: American Institute of Physics Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137677329&doi=10.1063%2f5.0093249&partnerID=40&md5=f54e15562ea833e5225df90f94e3a18e
id_number: 10.1063/5.0093249
full_text_status: none
publication: AIP Conference Proceedings
volume: 2472
refereed: TRUE
isbn: 9780735443877
issn: 0094243X
citation:   Ali, H. and Maulud, A.S. and Zabiri, H. and Nawaz, M. and Ismail, L.  (2022) Fault diagnosis by using multi-scale signed directed graph.  In: UNSPECIFIED.