Detecting the fault from spectrograms by using genetic algorithm techniques

• Autorzy: Amin, A. E. , El-Geheni, A. S. , El-Hawary, I. A. , El-Beali, R. A.
• Języki publikacji: EN

Abstrakty

EN

During the last thirty years there has been a rapidly growing interest in the field of genetic algorithms (GAs). The field is at a stage of tremendous growth, as evidenced by the increasing number of conferences, workshops, and papers concerning it, as well as the emergence of a central journal for the field. With their great robustness, genetic algorithms have proven to be a promising technique for many optimisation, design, control, and machine learning applications. This paper presents a new technique for detecting the source of fault in spinning mills from spectrograms by using genetic algorithm.

Słowa kluczowe

PL

spektogram tekstylny; algorytm genetyczny; błąd

EN

textile spectrogram; genetic algorithm; fault

• Czasopismo: Autex Research Journal
• Rocznik: 2007
• Tom: Vol. 7, no. 2
• Strony: 80--88
• Opis fizyczny: Bibliogr. 4 poz.

Twórcy

autor

Amin, A. E.

• Mansoura University, Textile Department

autor

El-Geheni, A. S.

• Alexandria University, Textile Department

autor

El-Hawary, I. A.

• lexandria University, Textile Department

autor

El-Beali, R. A.

• Mansoura University, Textile Department

Bibliografia

• 1. Application handbook for evenness testers of the Uster type; Determination of periodic mass variations (spectrum).
• 2. Karl Sims, Evolving Virtual Creatures, http://www.genarts.com/karl/papers/siggraph94.pdf (7.2002).
• 3. Sami Khuri, ‘Genetic Algorithms’, course handouts, Helsinki University of Technology, August 2002.
• 4. Amin. A. E., ‘Development of a simulation draft system model applied in virtual educational environment’, under publication.