TY - JOUR ID - 127830 TI - Application of Artificial Neural Network and Multi-magnetic NDE Methods to Determine Mechanical Properties of Plain Carbon Steels Subjected to Tempering Treatment JO - International Journal of Engineering JA - IJE LA - en SN - 1025-2495 AU - Ahadi Akhlaghi, I. AU - Kahrobaee, S. AU - Sekhavat, M. AU - Norouzi Sahraei, H. AU - Akhlaghi Modiri, F. AD - Department of Electrical and Bioelectric Engineering, Sadjad University of Technology, Mashhad, Iran AD - Department of Mechanical and Materials Engineering, Sadjad University of Technology, Mashhad, Iran AD - Center of Nondestructive Evaluation (CNDE), Sadjad University of Technology, Mashhad, Iran Y1 - 2021 PY - 2021 VL - 34 IS - 4 SP - 919 EP - 927 KW - mechanical parameters KW - Magnetic hysteresis loop KW - Magnetic Flux Leakage KW - Eddy current KW - Artificial Neural Network DO - 10.5829/ije.2021.34.04a.18 N2 - The present paper shows the results of applying an artificial neural network to three non-destructive magnetic methods including magnetic hysteresis loop (MHL), eddy current (EC), and magnetic flux leakage (MFL) techniques to determine mechanical features of plain carbon steels with unknown carbon contents subjected to tempering treatment. To simultaneously evaluate the effects of carbon content and microstructure on the magnetic and mechanical properties, four grades of hypoeutectoid steel samples containing 0.30, 0.46, 0.54, and 0.71 wt.% carbon were austenitized in the range of 830-925 °C and then subjected to quench-tempering treatments at 200, 300, 400, 500 and 600 °C. In the next step, mechanical properties including tensile strength, elongation, and hardness were measured using tensile and hardness tests, respectively. Finally, to study the electromagnetic parameters, MHL, MFL and EC non-destructive electromagnetic tests were applied to the heat-treated samples and their outputs were fed to a generalized neural network designed in this work. The results revealed that using a proper combination of electromagnetic parameters as the ANN input for each mechanical parameter enables us to determine the hardness, UTS and elongation of hypoeutectic carbon steel parts after tempering treatment with high accuracy. UR - https://www.ije.ir/article_127830.html L1 - https://www.ije.ir/article_127830_f9bdd9c3dc43f2cfb773a82d6a202221.pdf ER -