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Wyszukujesz frazę "steel industry" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
The Reasons of Steam Pipeline Elbow Rupture
Autorzy:
Mesjasz, A.
Piątkowski, J.
Powiązania:
https://bibliotekanauki.pl/articles/383031.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
pipeline steam
rupture
materials in power industry
degradation
microstructure
steel 13CrMo4-5
mechanical properties
rurociąg parowy
pęknięcie
materiały w energetyce
degradacja
mikrostruktura
stal 13CrMo4-5
właściwości mechaniczne
Opis:
In the paper the reasons for steam pipeline’s elbow material rupture, made of steel 13CrMo4-5 (15HM) that is being used in the energetics. Based on the mechanical properties in the ambient temperature (Rm, Rp0,2 and elongation A5) and in the increased temperature (Rp0,2t) it was found, that the pipeline elbow’s material sampled from the ruptured area has lower Rp0,2t by around 2% than it is a requirement for 13CrMo4-5 steel in it’s base state. The damage appeared as a result of complex stress state, that substantially exceeded the admissible tensions, what was the consequence of considerable structure degradation level. As a result of the microstructure tests on HITACHI S4200 microscope, the considerable development of the creeping process associates were found. Also the advances progress of the microstructure degradation was observed, which is substantial decomposition of bainite and multiple, with varied secretion size, and in most cases forming the micro cracks chains. With the use of lateral micro sections the creeping voids were observed, that creates at some places the shrinkage porosities clusters and micro pores.
Źródło:
Archives of Foundry Engineering; 2016, 16, 3; 67-70
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Time-Series Analysis for Predicting Defects in Continuous Steel Casting Process
Autorzy:
Rodziewicz, A.
Perzyk, M.
Powiązania:
https://bibliotekanauki.pl/articles/380643.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
information technology
foundry industry
quality management
continuous steel casting
time series analysis
naïve Bayesian classifier
technologia informatyczna
przemysł odlewniczy
zarządzanie jakością
ciągłe odlewanie stali
analiza szeregów czasowych
naiwny klasyfikator Bayesa
Opis:
The purpose of this paper was testing suitability of the time-series analysis for quality control of the continuous steel casting process in production conditions. The analysis was carried out on industrial data collected in one of Polish steel plants. The production data concerned defective fractions of billets obtained in the process. The procedure of the industrial data preparation is presented. The computations for the time-series analysis were carried out in two ways, both using the authors’ own software. The first one, applied to the real numbers type of the data has a wide range of capabilities, including not only prediction of the future values but also detection of important periodicity in data. In the second approach the data were assumed in a binary (categorical) form, i.e. the every heat(melt) was labeled as ‘Good’ or ‘Defective’. The naïve Bayesian classifier was used for predicting the successive values. The most interesting results of the analysis include good prediction accuracies obtained by both methodologies, the crucial influence of the last preceding point on the predicted result for the real data time-series analysis as well as obtaining an information about the type of misclassification for binary data. The possibility of prediction of the future values can be used by engineering or operational staff with an expert knowledge to decrease fraction of defective products by taking appropriate action when the forthcoming period is identified as critical.
Źródło:
Archives of Foundry Engineering; 2016, 16, 4; 125-130
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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