Fault detection and diagnosis in a heat exchanger

Juan C. Tudon Martinez, Ruben Morales-Menendez, Luis E. Garza Castañon

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

A comparison between the Dynamic Principal Component Analysis (DPCA) method and a bank of Diagnostic Observers (DO) under the same experimental data from a shell and tube industrial heat exchanger is presented. The comparative analysis shows the performance of both methods when sensors and/or actuators fail. Different metrics are discussed (i.e. robustness, quick detection, isolability capacity, explanation facility, false alarm rates and multiple faults identifiability). DO showed quicker detection for sensor and actuator faults with lower false alarm rate. Also, DO can isolate multiple faults. DPCA required a minor training effort; however, it cannot identify two or more sequential faults.
Original languageEnglish
Pages265-270
Number of pages6
Publication statusPublished - 1 Dec 2009
Externally publishedYes
EventICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics, Proceedings -
Duration: 1 Dec 2009 → …

Conference

ConferenceICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics, Proceedings
Period1/12/09 → …

Bibliographical note

Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Fault detection and diagnosis in a heat exchanger'. Together they form a unique fingerprint.

Cite this