Fault Detection in a Heat Exchanger, Comparative Analysis between Dynamic Principal Component Analysis and Diagnostic Observers
Detección de fallas en un intercambiador de calor, análisis comparativo entre análisis de componentes principales dinámico y observadores de diagnóstico
Juan C. Tudón Martínez1*, Rubén Morales Menéndez1**, Ricardo A. Ramírez Mendoza1***, Luis E. Garza Castañón1**** and Adriana Vargas Martínez1*****
1 Tecnológico de Monterrey, Campus Monterrey, Monterrey N.L., México (A00287756@itesm.mx*, rmm@itesm.mx**, ricardo.ramirez@itesm.mx***, legarza@itesm.mx****, A00777924@itesm.mx*****
]]> Article received on September 01, 2009
Abstract
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.
Keywords: Fault Detection and Diagnosis, Model Classification, Computer Application, Dynamic Principal Component Analysis, Diagnostic Observers.
Resumen
El artículo presenta una comparación entre dos métodos de detección de fallas, Análisis de Componentes Principales Dinámico (DPCA por sus siglas en inglés) y Observadores de Diagnóstico (DO por sus siglas en inglés), bajo los mismos datos experimentales extraídos de un intercambiador de calor industrial de tubo y coraza. El análisis comparativo muestra las propiedades de detección de ambos métodos cuando sensores y/o actuadores fallan en línea, incluyendo fallas múltiples. Para ambos métodos se definen métricas similares: robustez, tiempo de detección, capacidad de aislamiento y explicación de propagación de fallas, tasa de falsas alarmas y capacidad de identificar fallas múltiples. Los resultados experimentales muestran las ventajas y desventajas de ambos métodos. DO detecta más rápido las fallas de sensores y actuadores, presenta menor tasa de falsas alarmas y puede aislar fallas múltiples. DPCA requiere menor esfuerzo de entrenamiento; sin embargo, no puede identificar 2 o más fallas secuenciales.
Palabras clave: Detección y Diagnóstico de Fallas, Clasificación de modelos, Aplicación Computacional, Análisis de Componentes Principales Dinámico, Observadores de Diagnóstico.
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