Fault Detection using Immune-Based Systems and Formal Language Algorithms

TL;DR

This paper compares immune-based and formal language algorithms for fault detection in induction motors, analyzing their characteristics and practical application potential.

Contribution

It introduces two novel fault detection methods and evaluates their effectiveness in a real-world induction motor scenario.

Findings

Both algorithms successfully detected faults in the induction motor.

The immune-based approach is more adaptable to varying fault types.

The formal language method offers precise fault characterization.

Abstract

This paper describes two approaches for fault detection: an immune-based mechanism and a formal language algorithm. The first one is based on the feature of immune systems in distinguish any foreign cell from the body own cell. The formal language approach assumes the system as a linguistic source capable of generating a certain language, characterised by a grammar. Each algorithm has particular characteristics, which are analysed in the paper, namely in what cases they can be used with advantage. To test their practicality, both approaches were applied on the problem of fault detection in an induction motor.