Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer

Jafar Zarei,Javad Poshtan

doi:10.3390/mca16010031

Abstract

In this paper, a robust sensor fault detection and isolation (FDI) method based on the unknown input observer (UIO) approach is presented. The basic principle of unknown input observers is to decouple disturbances from the state estimation error. A single full-order observer is designed to detect sensor faults in the presence of unknown inputs (disturbances). By doing so, we generate a residual, a weighted output of the state estimation error, decoupled from disturbances. The resulting robust (in the sense of disturbances) residual can be used for fault detection. Although this scheme has successful fault detection, using one observer is not successful in fault isolation. Therefore, a robust sensor fault isolation observer scheme is proposed. In order to evaluate its ability, the presented method is adopted to detect and isolate sensor faults of a highly nonlinear dynamic system. The faulty behavior of output sensors in a jacketed continuous stirred tank reactor (CSTR), around operating point, is investigated. Simulation results show that model uncertainties and disturbances can be distinguished from a response to a sensor fault.

Highlights

IntroductionIn chemical plants faulty sensors may cause process performance degradation (e.g., lower product quality) or fatal accidents (e.g., temperature run away) [1]
In the real world, no system can work perfectly at all time under all conditions
It is essential that a fault detection scheme can be developed so as to be able to detect and identify possible faults in the system as early as possible [3]

Summary

Introduction

In chemical plants faulty sensors may cause process performance degradation (e.g., lower product quality) or fatal accidents (e.g., temperature run away) [1]. A report estimates that the loss to petrochemical industries in the U.S alone is $20 billion/year [2]. Petrochemical plants are becoming larger, loss and maintenance costs will increase. It is essential that a fault detection scheme can be developed so as to be able to detect and identify possible faults in the system as early as possible [3]. The system can be maintained and kept reliable by means of this early warning enabling repair or replacement to take place at the earliest or most convenient time, with the minimum of loss of time or productivity. Fault detection and diagnosis have become inseparable parts of modern complex systems

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