Noise pattern recognition of airplanes taking off: Task for a monitoring system

Luis Pastor Sánchez Fernández, Oleksiy Pogrebnyak, José Luis Oropeza Rodríguez, Sergio Suárez Guerra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

This paper presents an original work for aircraft noise monitoring systems and it analyzes the airplanes noise signals and a method to identify them. The method uses processed spectral patterns and a neuronal network feed-forward, programmed by means of virtual instruments. The obtained results, very useful in portable systems, make possible to introduce redundancy to permanent monitoring systems. The noise level in a city has fluctuations between 50 dB (A) and 100 dB (A). It depends on the population density and its activity, commerce and services in the public thoroughfare, terrestrial and aerial urban traffic, of the typical activities of labor facilities and used machinery, which give varied conditions that must be faced of diverse ways within the corresponding normalization. The sounds or noises that exceed the permissible limits, whichever the activities or causes that originate them, are considered events susceptible to degrade the environment and the health.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Proceedings
Pages831-840
Number of pages10
StatePublished - 2007
Event12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 - Vina del Mar-Valparaiso, Chile
Duration: 13 Nov 200716 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4756 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Iberoamerican Congress on Pattern Recognition, CIARP 2007
Country/TerritoryChile
CityVina del Mar-Valparaiso
Period13/11/0716/11/07

Keywords

  • Aircraft
  • Monitoring
  • Noise
  • Pattern
  • Recognition

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