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Detecting the fault from spectrograms by using genetic algorithm techniques

Amin A. E., El-Geheni A. S., El-Hawary I. A., El-Beali R. A.

Autex Research Journal

2007

Vol. 7, no. 2

80--88

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.

Mathematical model for virtual draft system simulation (VDSS)

Amin A. E., Al-Geiheini A. S., El-Hawary I. A.

Autex Research Journal

2006

Vol. 6, no. 2

72--80

The textile sliver drafting process has a decisive influence on the quality of yarn produced, and from the point of view of system theory it is marked by non-linearity, distributed delays and highly oscillatory disturbance response. As with most other textile manufacturing processes, this process has received almost no attention in control engineering literature. Motivated by the current needs of textile manufacturing, this paper introduces a suitable mathematical model of virtual draft system simulation.