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DETECTION AND ISOLATION OF A SENSOR

DRIFT FAULT

Yilun Zhou

Prof. Thomas Parisini

Imperial College London

UKACC PhD Presentation Showcase

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Introduction

Background • Complex control systems and demand for fault tolerance• Process fault and sensor fault in nonlinear systems• Model-based fault detection and isolation schemes (FDI) • Time evolution of faults: abrupt and incipient faults

Objectives• A class of nonlinear systems with sensor drift faults• Adaptive and less conservative threshold

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Problem Formulation and Methodology

A class of nonlinear MIMO system with sensor drift faults

Detection Estimators and Isolation Estimators

Residual and Threshold

>> ⋮⋮

s Drift faults, s Isolators.

dcrossing

Any crossing excludes faulty assumption.

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Simulation Result

Detection

At t = 13s, a fault occurs. Then the fault is detected at t = 16.64s

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Simulation Result

Isolation

There is a crossing in isolator 2.

The possibility of fault occurrence in Sensor 2 is excluded.

Drift fault occurred inSensor 3

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Conclusion and Future work

Conclusion:• Adaptive threshold increases robustness and stability• Fault compensation in isolators improves performance

Future Work:• Design a FDI approach for a hybrid sensor fault• Design a distributed fault diagnosis approach• Design a benchmark test using the FDI scheme