Abstract
The results of the research concerning development of the technique of metals strength properties diagnostics using combination of the methods of non-destructive control based on the complex use of fuzzy inference system and hybrid neural network are presented in the paper. The acoustic non-destructive control method, the electro-magnetic method and hardness control were used as the control methods within the framework of the proposed technique. The selection of the optimal combination of the methods was performed using fuzzy inference system, in which, the final solution was taken applying Harrington desirability function. The metal strength properties were determined using hybrid neural network the basis of which are fuzzy neurons. The simulation results with the use of samples of Y8 steel have shown that the combination of acoustic and electromegnetic methods of non-destructive testing is an optimal in terms of maximum value of heneral Harrington desiribility index and the hybrid neural network with two layers of neurons and triangular membership functions with combine algorithm of network training is an optimal one in terms of relative error of metals strength properties evaluation. To our mind, the proposed technique may allow us to increase the exactness of metals strength properties determination when the non-destructive methods of control are applied.
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Babichev, S., Durnyak, B., Sharko, O., Sharko, A. (2020). Technique of Metals Strength Properties Diagnostics Based on the Complex Use of Fuzzy Inference System and Hybrid Neural Network. In: Babichev, S., Peleshko, D., Vynokurova, O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. Springer, Cham. https://doi.org/10.1007/978-3-030-61656-4_7
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