A novel Artificial Immune System for fault behavior detection

Authors:
C. A. Laurentys;R. M. Palhares;W. M. Caminhas
Affiliations:
Department of Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-010 Belo Horizonte, MG, Brazil;Department of Electronics Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-010 Belo Horizonte, MG, Brazil;Department of Electronics Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-010 Belo Horizonte, MG, Brazil
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 13
Cited 1

Fundamentals of Natural Computing (Chapman & Hall/Crc Computer and Information Sciences)

Fundamentals of Natural Computing (Chapman & Hall/Crc Computer and Information Sciences)
Statistical Comparisons of Classifiers over Multiple Data Sets

The Journal of Machine Learning Research
Design of mixed H2/H∞ control systems using algorithms inspired by the immune system

Information Sciences: an International Journal
Editorial: Special Issue on "Nature Inspired Problem-Solving"

Information Sciences: an International Journal
A hybrid artificial immune system and Self Organising Map for network intrusion detection

Information Sciences: an International Journal
Vibration-based fault diagnosis of spur bevel gear box using fuzzy technique

Expert Systems with Applications: An International Journal
An architecture for fault detection and isolation based on fuzzy methods

Expert Systems with Applications: An International Journal
An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network

Expert Systems with Applications: An International Journal
Induction machine fault detection using clone selection programming

Expert Systems with Applications: An International Journal
Design and analysis of stochastic local search for the multiobjective traveling salesman problem

Computers and Operations Research
V-detector: An efficient negative selection algorithm with "probably adequate" detector coverage

Information Sciences: an International Journal
BAIS: A Bayesian Artificial Immune System for the effective handling of building blocks

Information Sciences: an International Journal
Design of experiments: overview

Proceedings of the 40th Conference on Winter Simulation

Adaptive fault detection and diagnosis using an evolving fuzzy classifier

Information Sciences: an International Journal

Quantified Score

Hi-index	12.05

Visualization

Abstract

This paper presents an error detection methodology to enable fault detection inspired on recent immune theory. The fault detection problem is a challenging problem due to processes increasing complexity and agility necessary to avoid malfunction or accidents. The key challenge is determining the difference between normal and potential harmful activities. A promising solution is emerging in the form of Artificial Immune System (AIS). In this article, Natural Killer (NK) immune cells mechanisms inspired an AIS. The AIS proposed uses recent biological mechanism such as: NK activation and education machinery. DAMADICS benchmark was applied to compare the proposed AIS performance to others fault detection algorithms. The results show that the novel approach developed provides better detection rate and false alarms tradeoff when compared to other methods in literature.