Fault Detection in a Heat Exchanger, Comparative Analysis between Dynamic Principal Component Analysis and Diagnostic Observers
Fuente:
Redalyc
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Instituto Politécnico Nacional
2011
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1876443783060520960 |
|---|---|
| author | Juan C. Tudón Martínez |
| author_facet | Juan C. Tudón Martínez |
| contents | Fault Detection in a Heat Exchanger, Comparative Analysis between Dynamic Principal Component Analysis and Diagnostic Observers Juan C. Tudón Martínez Rubén Morales Menéndez Ricardo A. Ramírez Mendoza Luis E. Garza Castañón Adriana Vargas Martínez Computación Model Classification Computer Application Diagnostic Observers Fault Detection and Diagnosis Dynamic Principal Component Analysis A comparison between the Dynamic Principal Component Analysis (DPCA) method and a set of Diagnostic Observers (DO) under the same experimental data from a shell and tube industrial heat exchanger is presented. The comparative analysis shows the detection properties of both methods when sensors and/or actuators fail online, including scenarios with multiple faults. Similar metrics are defined for both methods: robustness, quick detection, isolability capacity, explanation facility, false alarm rates and multiple faults identifiability. Experimental results show the principal advantages and disadvantages of both methods. 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 can not identify two or more sequential faults. 2011 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61520765006 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.14 |
| format | Artículo científico |
| id | redalyc_61520765006 |
| institution | Redalyc |
| language | en |
| publishDate | 2011 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Fault Detection in a Heat Exchanger, Comparative Analysis between Dynamic Principal Component Analysis and Diagnostic Observers Juan C. Tudón Martínez Computación Model Classification Computer Application Diagnostic Observers Fault Detection and Diagnosis Dynamic Principal Component Analysis Fault Detection in a Heat Exchanger, Comparative Analysis between Dynamic Principal Component Analysis and Diagnostic Observers Juan C. Tudón Martínez Rubén Morales Menéndez Ricardo A. Ramírez Mendoza Luis E. Garza Castañón Adriana Vargas Martínez Computación Model Classification Computer Application Diagnostic Observers Fault Detection and Diagnosis Dynamic Principal Component Analysis A comparison between the Dynamic Principal Component Analysis (DPCA) method and a set of Diagnostic Observers (DO) under the same experimental data from a shell and tube industrial heat exchanger is presented. The comparative analysis shows the detection properties of both methods when sensors and/or actuators fail online, including scenarios with multiple faults. Similar metrics are defined for both methods: robustness, quick detection, isolability capacity, explanation facility, false alarm rates and multiple faults identifiability. Experimental results show the principal advantages and disadvantages of both methods. 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 can not identify two or more sequential faults. 2011 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61520765006 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.14 |
| title | Fault Detection in a Heat Exchanger, Comparative Analysis between Dynamic Principal Component Analysis and Diagnostic Observers |
| topic | Computación Model Classification Computer Application Diagnostic Observers Fault Detection and Diagnosis Dynamic Principal Component Analysis |
| url | https://www.redalyc.org/articulo.oa?id=61520765006 |