New Computer Method of Derivative Thermal Express Analysis of Cast Iron for Operational Prediction of Quality of Melts and Castings

• Autorzy: Zakharchenko Edvard , Sirenko Ekaterina , Goncharov Alexander , Bogdan Alexander , Burbelko Andriy , Kawalec Magdalena

Identyfikatory

DOI

10.7494/jcme.2019.3.2.31

• Języki publikacji: EN

Abstrakty

EN

This method is based on the determination of similarity criterion Z as the average temperature difference between the reference and analyzed curves in the solidification region. The purpose of this work is to describe the thermal express-analysis (TDA) device created by us and the substantiation of the reliability and sensitivity of the results of the new method, including the definition of a two-sided confidence interval using Student’s t-test. The error of the method was determined with the Student’s criterion taken into account. The high sensitivity of the method to the metallurgical prehistory of the gray and white cast iron melts was confirmed. The method has been successfully tested under laboratory and experimental-industrial conditions on induction melting cast iron. The new method uses a disposable environmentally friendly submersible steel sampler with a heat-resistant coating inside and out. The method allows for the quick adaptation to the conditions of specific foundries (especially with the frequent changes of classes and types of cast iron) due to replenishing the database of the reference samples. The basic features of the new method are its universality, self-adaptability, speed, relative simplicity, and high sensitivity to the metallurgical prehistory of molten iron.

Słowa kluczowe

EN

derivative thermal express-analysis; reference and analyzed cooling curve similarity criterion; gray iron; white iron,; immersion sample cup

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Journal of Casting & Materials Engineering
• Rocznik: 2019
• Tom: Vol. 3, no. 2
• Strony: 31--42
• Opis fizyczny: Bibliogr. 13 poz., fot., rys., tab., wykr.

Twórcy

autor

Zakharchenko Edvard

• a Physico-Technological Institute of Metals and Alloys of the National Academy of Sciences of Ukraine, Blvd. Vernadsky 34/1, 03142 Kiev, Ukraine

autor

Sirenko Ekaterina

• Physico-Technological Institute of Metals and Alloys of the National Academy of Sciences of Ukraine, Blvd. Vernadsky 34/1, 03142 Kiev, Ukraine

autor

Goncharov Alexander

• Physico-Technological Institute of Metals and Alloys of the National Academy of Sciences of Ukraine, Blvd. Vernadsky 34/1, 03142 Kiev, Ukraine

autor

Bogdan Alexander

• Physico-Technological Institute of Metals and Alloys of the National Academy of Sciences of Ukraine, Blvd. Vernadsky 34/1, 03142 Kiev, Ukraine

autor

Burbelko Andriy

• AGH University of Science and Technology, Faculty of Foundry Engineering, 23 Reymonta St., 30–059 Krakow, Poland

autor

Kawalec Magdalena

• AGH University of Science and Technology, Faculty of Foundry Engineering, 23 Reymonta St., 30–059 Krakow, Poland

Bibliografia

• [1] Binczyk F. (2007). An Assessment of the Derivative Thermal Analysis of Gray Cast Iron. Archives of Foundry Engineering, 7(3), 21–24.
• [2] Li Y., Hu X. & Xu X. (2001). Pattern Recognition on Thermal Analysis. Journal of Materials Science & Technology, 17(1), 73–74.
• [3] Pustyl'nik Ye.I. (1968). Statisticheskiye metody analiza i obrabotki nablyudeniy. Moskva: Nauka [Пустыльник Е.И. (1968). Статистические методы анализа и обработки наблюдений. Москва: Наука].
• [4] Li Y. & Wang Q. (2005). Intelligent evaluation of melt iron quality by pattern recognition of thermal analysis cooling curves. Journal of Materials Processing Technology, 161, 430–434.
• [5] Wang Q., Li Y.X. & Li X.C. (2003). Grain Refinement of Al-Si Alloys and the Efficiency Assessment by Recognition of Cooling Curves. Metallurgical and Materials Transactions A, May, 1175–1182.
• [6] Li D.-Y., Xu Z.-Y., Ma X.-L. & Shi D.-Y. (2015). Review of current research and application of ductile cast iron quality monitoring technologies in Chinese foundry industry. China Foundry, 12 (N4), 239–249.
• [7] Dawson S. & Popelar P. (2013). Thermal Analysis and Process Control for Compacted Graphite Iron and Ductile Iron. Keith Millis Symposium on Ductile Cast Iron: Oct. 15–17 2013. Nashville, TN, US. Red Hook: Curran Associates, 59–66.
• [8] Dawson S. (2002). Process Control for the Production of Compacted Graphite Iron. Based on a presentation made at the 106th AFS Casting Congress. Kansas City: May 4–7 2002, http://www.cintercast.com, 1–11.
• [9] Zakharchenko E.V., Zhukov L.F., Sirenko Ye.A., Bogdan A.V., Goncharov A.L., Kravchenko Ye.V. (2015). Usovershenstvovaniye universal'nogo metoda termicheskogo ekspress-analiza zhidkikh chugunov, osnovannogo na raspoznavanii formy krivykh okhlazhdeniya. Protsessy lit'ya, 2, 3–9 [Захарченко Э.В., Жуков Л.Ф., Сиренко Е.А., Богдан А.В., Гончаров А.Л., Кравченко Е.В. (2015). Усовершенствование универсального метода термического экспресс-анализа жидких чугунов, основанного на распознавании формы кривых охлаждения. Процессы литья, 2, 3–9].
• [10] Zakharchenko E.V., Sirenko K.A., Goncharov A.L. & Bogdan A.V. (2015). Pat. Ukraine N99968.
• [11] Sun Y.Z., An G.Y. (1995). The influence of structure parameters of cast iron sample cup on shape of cooling curve. Research Studies on Foundry Equipment, April, 35–38.
• [12] Sun Y.Z. & An G.Y. (1995). The influence of structure parameters of cast iron sample on carbon equivalent. China Foundry Machinery and Technology, February, 48–50.
• [13] Sun Y.Z., Che S.X. & Chen H.S. (1995). The influence of structure parameters of sampling cup on the precision of forecasting silicon content of cast iron. Foundry Technology, March, 6–8.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).