Fault detection and diagnosis in a heat exchanger

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

Producción científica

3 Citas (Scopus)

Resumen

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.
Idioma originalEnglish
Páginas265-270
Número de páginas6
EstadoPublished - 1 dic 2009
Publicado de forma externa
EventoICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics, Proceedings -
Duración: 1 dic 2009 → …

Conference

ConferenceICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics, Proceedings
Período1/12/09 → …

All Science Journal Classification (ASJC) codes

  • Inteligencia artificial
  • Visión artificial y reconocimiento de patrones
  • Ingeniería de control y sistemas

Huella

Profundice en los temas de investigación de 'Fault detection and diagnosis in a heat exchanger'. En conjunto forman una huella única.

Citar esto