1. Machine Learning Applied in the Detection of Faults in Pipes by Acoustic Means
- Author
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Fábio Roberto Chavarette, Igor Feliciani Merizio, Roberto Outa, Thiago Carreta Moro, Vishnu Narayan Mishra, Universidade Estadual Paulista (Unesp), Faculdade de Tecnologia de São Paulo 'Prof. Fernando Amaral de Almeida Prado', and Indira Gandhi National Tribal University
- Subjects
0209 industrial biotechnology ,Measure (data warehouse) ,Training set ,Artificial immune system ,Computer science ,020209 energy ,Mechanical Engineering ,education ,Structural failure ,Preventive diagnosis ,Aerospace Engineering ,Sampling (statistics) ,Ocean Engineering ,02 engineering and technology ,Industrial and Manufacturing Engineering ,Fault detection and isolation ,Reliability engineering ,020901 industrial engineering & automation ,Negative selection algorithm ,Structural Health Monitoring ,0202 electrical engineering, electronic engineering, information engineering ,Structural health monitoring ,Decision making ,Structural monitoring - Abstract
Made available in DSpace on 2021-06-25T11:15:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 The Structural Health Monitoring evaluates the situation of aeronautical, civil or mechanical structures and provides a forecast of its remaining useful life, acting in decision making, being able to intervene in critical situations. It has emerged as a viable economic alternative for monitoring structures and preventing failures. Thus, this system is defined as a prophylactic measure, reliable and effective against structural failure. This work exposes the theoretical basis and a new technique for detection of failures in pipes by acoustic means, following the International Standard ISO10534-1 (1996) in the sampling. This method of fault detection using acoustic means requires considerably less training data than is usually used in the literature, with approximately 85% less data. The results presented in this work showed how it is possible and effective to detect failure in pipes by acoustic means using an artificial immune system for structural monitoring, with a 100% precision in the detection of failure. Mechanical Engineering Department UNESP São Paulo State University “Julio de Mesquita Filho”, Av. Brasil Sul, 56, Donwtonw Department of Engineering Physics and Mathematics Institute of Chemistry UNESP São Paulo State University “Julio de Mesquita Filho”, Rua Prof. Francisco Degni, 55, Quitandinha Civil Engineering Department UNESP São Paulo State University “Julio de Mesquita Filho”, Av. Brasil Sul, 56, Donwtonw FATEC Faculdade de Tecnologia de São Paulo “Prof. Fernando Amaral de Almeida Prado”, Av. Prestes Maia 1764 - Jd. Ipanema Department of Mathematics Indira Gandhi National Tribal University, Lalpur, Amarkantak Mechanical Engineering Department UNESP São Paulo State University “Julio de Mesquita Filho”, Av. Brasil Sul, 56, Donwtonw Department of Engineering Physics and Mathematics Institute of Chemistry UNESP São Paulo State University “Julio de Mesquita Filho”, Rua Prof. Francisco Degni, 55, Quitandinha Civil Engineering Department UNESP São Paulo State University “Julio de Mesquita Filho”, Av. Brasil Sul, 56, Donwtonw
- Published
- 2021