Result: Application of impoved BP algorithm based on information entropy of signal in recognizing defects of seamless tube
Title:
Application of impoved BP algorithm based on information entropy of signal in recognizing defects of seamless tube
Authors:
Source:
2004 7th International Conference on Signal Processing (ICSP'04). :1585-1588
Publisher Information:
Piscataway NJ; Beijing: IEEE, Pub. House of Electronics Industry, 2004.
Publication Year:
2004
Physical Description:
print, 6 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Connexionnisme. Réseaux neuronaux, Connectionism. Neural networks, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Entropie, Entropy, Entropía, Matrice Jacobi, Jacobi matrix, Matriz Jacobi, Modèle 2 dimensions, Two dimensional model, Modelo 2 dimensiones, Modèle dynamique, Dynamic model, Modelo dinámico, Monitorage, Monitoring, Monitoreo, Méthode domaine fréquence, Frequency domain method, Método dominio frecuencia, Réseau neuronal, Neural network, Red neuronal
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Mechanical Engineering Tianjin University, Tianjin 300072, China
Beijng Institute of Metrology, Beijng 100029, China
Beijng Institute of Metrology, Beijng 100029, China
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.18163512
Database:
PASCAL Archive
Further Information
Flaw signals of seamless tube are investigated in frequency domain. These flaws are internal flaws, outside flaws, and holes. Two-dimension spectrum entropy indexes, which are regarded as character indexes, are practical in feature ion of defects, and the seamless tube flaws are recognized by the improved BP neural networks algorithm according lo analyzing deeply the forward neural network dynamics model and its Jacobian matrix. The experiments have demonstrated that the recognition algorithm is of a perfect precision which could leaches as higher as 100 percent, and it is suitable to real time monitoring. It will have a wide application prospects.