Comparative Analysis of Statistical Inference Methods for Fault Detection and Diagnosis Using Nonlinear Models Applied to the Hydraulical Benchmark System

Abstract

This work compares three nonlinear models for a three-tank hydraulic system. From each model, nonlinear predictors are designed for the generation of residuals representing the fault conditions. The residuals feed three different statistical inference modules to be compared in search for the best solution for fault detection and diagnosis.