Publication detail

Signal Detection Based on Similarity Measures

ŠEDA, M. JIRKŮ, J.

Czech title

Detekce signálů založená na mírách podobnosti

English title

Signal Detection Based on Similarity Measures

Type

conference paper

Language

en

Original abstract

The operation of technical processes requires increasingly advanced supervision and fault diagnosis to improve reliability, safety, and economy. Detection algorithms are generally optimised with respect to a particular set of cost functions chosen for the specific application. In the last few years in the field of detection systems there have been an increasing number of applications based on algorithms using methodologies, which belong to a subclass of Artificial Intelligence called Soft Computing. In this paper we propose a fuzzy similarity measure-based method for the detection of dangerous states based on matching a predefined database of these states with periodically measured or estimated parameter values.

Czech abstract

Provozování technických procesů vyžaduje neustále rostoucí nároky na úroveň diagnostiky chyb, která slouží k zvýšení spolehlivosti, bezpečnosti a hospodárnosti. Detekční algoritmy jsou většinou optimalizovány vzhledem k určité množině cenových funkcí zvolených v závislosti na aplikaci. V posledních několika letech oblast detekčních systémů a jejich aplikací zaznamenala velký růst. Používají se metody soft computingu, které patří do oblasti umělé inteligence. V příspěvku navrhujeme pro detekci nebezpečných stavů zařízení metodu založenou na fuzzy mírách podobnosti periodicky měřených nebo odhadovaných parametrů s kritickými hodnotami sledovaných parametrů uložených v databázi.

English abstract

The operation of technical processes requires increasingly advanced supervision and fault diagnosis to improve reliability, safety, and economy. Detection algorithms are generally optimised with respect to a particular set of cost functions chosen for the specific application. In the last few years in the field of detection systems there have been an increasing number of applications based on algorithms using methodologies, which belong to a subclass of Artificial Intelligence called Soft Computing. In this paper we propose a fuzzy similarity measure-based method for the detection of dangerous states based on matching a predefined database of these states with periodically measured or estimated parameter values.

Keywords in English

fault detection, similarity measure, threshold-based detector, fuzzy detector

RIV year

2004

Released

01.06.2004

Publisher

Slovak University of Technology

Location

Štrbské Pleso (Slovakia)

ISBN

80-227-2059-3

Book

Abstracts of the 6th International Conference Control of Power Systems ’04

Pages count

1

BIBTEX


@inproceedings{BUT12867,
  author="Miloš {Šeda} and Jaroslav {Jirků},
  title="Signal Detection Based on Similarity Measures",
  booktitle="Abstracts of the 6th International Conference Control of Power Systems ’04",
  year="2004",
  month="June",
  publisher="Slovak University of Technology",
  address="Štrbské Pleso (Slovakia)",
  isbn="80-227-2059-3"
}