The paper presents the application results concerning the fault diagnosis of a chemical process using dynamic system identification and model-based residual generation techniques. The considered approach consists of identifying different families of models for the monitored system. Then, dynamic output observers or Kalman filters are used as residual generators. The proposed fault diagnosis and identification scheme has been tested on a real chemical process in the presence of both sensor, actuator, component faults and disturbance.

Fault Diagnosis of a Chemical Process using Identification Techniques

SIMANI, Silvio
2002

Abstract

The paper presents the application results concerning the fault diagnosis of a chemical process using dynamic system identification and model-based residual generation techniques. The considered approach consists of identifying different families of models for the monitored system. Then, dynamic output observers or Kalman filters are used as residual generators. The proposed fault diagnosis and identification scheme has been tested on a real chemical process in the presence of both sensor, actuator, component faults and disturbance.
2002
fault diagnosis; chemical process; dynamic system identification; model-based residual generation; Kalman filters.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1195679
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