An Integration of Neural Network and Shuffled Frog-Leaping Algorithm for CNC Machining Monitoring

• Autorzy: Goli Alireza , Tirkolaee Erfan Babaee , Weber Gerhard-Wilhelm

Identyfikatory

DOI

10.2478/fcds-2021-0003

• Języki publikacji: EN

Abstrakty

EN

This paper addresses Acoustic Emission (AE) from Computer Numerical Control (CNC) machining operations. Experimental measurements are performed on the CNC lathe sensors to provide the power consumption data. To this end, a hybrid methodology based on the integration of an Artificial Neural Network (ANN) and a Shuffled Frog-Leaping Algorithm (SFLA) is applied to the data resulting from these measurements for data fusion from the sensors which is called SFLA-ANN. The initial weights of ANN are selected using SFLA. The goal is to assess the potency of the signal periodic component among these sensors. The efficiency of the proposed SFLA-ANN method is analyzed compared to hybrid methodologies of Simulated Annealing (SA) algorithm and ANN (SA-ANN) and Genetic Algorithm (GA) and ANN (GA-ANN).

Słowa kluczowe

EN

Artificial Neural Network; Shuffled Frog-Leaping Algorithm; Simulated Annealing; genetic algorithm; CNC machining; Multisensor data fusion

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2021
• Tom: Vol. 46, No. 1
• Strony: 28--42
• Opis fizyczny: Bibliogr. 44 poz., rys., tab.

Twórcy

autor

Goli Alireza

• Department of Industrial Engineering, University of Isfahan, Isfahan, Iran

autor

Tirkolaee Erfan Babaee

• Department of Industrial Engineering, Istinye University, Istanbul, Turkey

autor

Weber Gerhard-Wilhelm

• Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland
• Institute of Applied Mathematics, Middle East Technical University, Ankara, Turkey

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).