APPLICATION OF PATTERN RECOGNITION AND ARTIFICIAL NEURAL NETWORK TO IMPROVE THE MECHANICAL PROPERTIES OF CYLINDER BLOCK CAST OF AUTOMOBILE ENGINE

Acta Metall Sin

1998, Vol. 34

Issue (10): 1068-1072 DOI:

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APPLICATION OF PATTERN RECOGNITION AND ARTIFICIAL NEURAL NETWORK TO IMPROVE THE MECHANICAL PROPERTIES OF CYLINDER BLOCK CAST OF AUTOMOBILE ENGINE

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ZHANG Zhaochun; WU Zhu; LI Chonghe; QIN Pei; CHEN Nianyi(Shanghai Institute of Metallurgy; The Chinese Academy of Sciences; Shanghai 200050)Correspondent: WU Zhu; Tel: (021)62511070-8932; Fax: (021)62513510. APPLICATION OF PATTERN RECOGNITION AND ARTIFICIAL NEURAL NETWORK TO IMPROVE THE MECHANICAL PROPERTIES OF CYLINDER BLOCK CAST OF AUTOMOBILE ENGINE. Acta Metall Sin, 1998, 34(10): 1068-1072.

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Abstract By means of pattern recoghtion technique the principal factors affecting thetensile strength and hardness of automobile cylinder block cast are discussed, and their optimizedrange determined also. Aritificial neural network, trained by known data, has been used topredict the values of both tensile strength and hardness. The predicted results agree well withthe experimental ones. It has been demonstrated that the mentioned optidsation techniqueprovides a technical approach to disprove the tensile strength and hardness of cylinder block castof automobile engine.

Key words: pattern recognition multivariate analysis artificial neural network cast tensile strength hardness

Received: 18 October 1998

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https://www.ams.org.cn/EN/ OR https://www.ams.org.cn/EN/Y1998/V34/I10/1068

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