Object

Title: Converter end-point prediction model using spectrum image analysis and improved neural network algorithm

Creator:

Wen, Hong-yuan ; Zhao, Qi ; Chen, Yan-ru ; Zhou, Mu-chun ; Zhang, Meng ; Xu, Ling-fei

Contributor:

Gaj, Miron. Redakcja ; Urbańczyk, Wacław. Redakcja

Description:

Optica Applicata, Vol. 38, 2008, nr 4, s. 693-704

Abstrakt:

Aiming at the present situation of the steelmaking end-point control at home and abroad, a neural network model was established to judge the end-point. Based on the colour space conversion and the fiber spectrum division multiplexing technology, a converter radiation multi-frequency information acquisition system was designed to analyze the spectrum light and image characteristic information, and the results indicate that they are similar at early-middle stage but dissimilar when approach the steelmaking blowing end. The model was trained and forecasted by using an improved neural network correction coefficient algorithm and some appropriate variables as the model parameters. The experimental results show the proposed algorithm improves the prediction accuracy by 15.4% over the conventional algorithm in 5s errors and the respond time is about 1.688s, which meets the requirements of end-point judgment online.

Publisher:

Oficyna Wydawnicza Politechniki Wrocławskiej

Place of publication:

Wrocław

Date:

2008

Resource Type:

artykuł

Resource Identifier:

oai:dbc.wroc.pl:62978

Source:

<sygn. PWr A3481II> ; click here to follow the link ; click here to follow the link

Language:

eng

Relation:

Optica Applicata ; Optica Applicata, Vol. 38, 2008 ; Optica Applicata, Vol. 38, 2008, nr 4 ; Politechnika Wrocławska. Wydział Podstawowych Problemów Techniki

Rights:

Wszystkie prawa zastrzeżone (Copyright)

Access Rights:

Dla wszystkich w zakresie dozwolonego użytku

Location:

Politechnika Wrocławska

Group publication title:

Optica Applicata

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