ERA

Download the full-sized PDF of Data Driven Methods for Analysis and Design of Industrial Alarm SystemsDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R33R0Q71P

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Graduate Studies and Research, Faculty of

Collections

This file is in the following collections:

Theses and Dissertations

Data Driven Methods for Analysis and Design of Industrial Alarm Systems Open Access

Descriptions

Other title
Subject/Keyword
Alarm systems
Time-deadbands
Markov processes
Delay-timers
Process monitoring
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Afzal, Muhammad Shahzad
Supervisor and department
Tongwen Chen
Examining committee member and department
Zhao, Qing (Department of Electrical and Computer Engineering)
Li, Zukui (Department of Chemical and Materials Engineering)
Chen, Tongwen (Department of Electrical and Computer Engineering)
Wu, Fangxiang (Department of Mechanical Engineering, University of Saskatchewan)
Jing, Yindi (Department of Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization
Control Systems
Date accepted
2017-09-01T09:18:08Z
Graduation date
2017-11:Fall 2017
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
An alarm system is an integral part of process monitoring and safety. A poorly configured alarm system can sometimes cause more harm than good, by introducing many false and nuisance alarms for the operators. Various standards on alarm system management and rationalization suggest many configuration methods to help in improving the overall performance of alarm monitoring systems. In this thesis, the problem of analyzing and designing alarm systems for both single- and multi-mode processes is considered. A design procedure of a multivariate alarm system for multi-mode processes is developed. A hidden Markov model based modeling approach is adopted to capture the multi-modality of data and the mode-reachability constraints of a multi-mode process. A monitoring index utilizing the proposed two-step Viterbi algorithm is developed, and for fault isolation, reconstruction based contribution plots are used. The utility of delay-timers in improving existing univariate alarm systems for multi-mode processes is studied. A mathematical model is developed to calculate analytical expressions for different performance indices (the false alarm rate, missed alarm rate, and expected detection delay). A particle swarm optimization based method is proposed for designing delay-timers, while satisfying the constraints on the performance indices and delay-timer lengths for various modes of the operation of a process. The analysis and design of time-deadbands for univariate alarm systems is also considered in this thesis. In particular, a Markov chain process based mathematical model is developed to capture the time-deadband configurations for single mode processes. Analytical expressions for the performance indices are calculated, and design procedures based on process data and alarm data are developed.
Language
English
DOI
doi:10.7939/R33R0Q71P
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Afzal, M.S., Tan, W., Chen, T., "Process Monitoring for Multimodal Processes with Mode-Reachability Constraints", IEEE Transactions on Industrial Electronics, vol. 64, pp. 4325-4335, 2017.Afzal, M.S., Chen, T., "Analysis and Design of Multimode Delay-Timers", Chemical Engineering and Research Design, vol. 120, pp. 179-193, 2017.Afzal, M.S., Chen, T., Bandehkhoda, A., Izadi, I., "Performance Assessment of Time-deadbands", Proceedings of the American Control Conference (ACC), pp. 4815-4820, Seattle, WA, USA, 2017.

File Details

Date Uploaded
Date Modified
2017-09-01T15:18:08.673+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (PDF/A)
Mime type: application/pdf
File size: 2313440
Last modified: 2017:11:08 16:44:26-07:00
Filename: Afzal_MuhammadShahzad_201708_PhD.pdf
Original checksum: dfb9d1054ff80735a3461cc862938470
Activity of users you follow
User Activity Date