Noise prediction of axial piston pump based on different valve materials using a modified artificial neural network model

Hassan A. Babikir; Mohamed Abd Elaziz; Ammar H. Elsheikh; Ezzat A. Showaib; M. Elhadary; Defa Wu; Yinshui Liu

Alexandria Engineering Journal (Sep 2019)

Noise prediction of axial piston pump based on different valve materials using a modified artificial neural network model

Hassan A. Babikir,
Mohamed Abd Elaziz,
Ammar H. Elsheikh,
Ezzat A. Showaib,
M. Elhadary,
Defa Wu,
Yinshui Liu

Affiliations

Hassan A. Babikir: State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Faculty of Engineering, University of Sinnar, Sinnar, Sudan
Mohamed Abd Elaziz: Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt
Ammar H. Elsheikh: State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Department of Production Engineering and Mechanical Design, Tanta University, Tanta 31527, Egypt
Ezzat A. Showaib: Department of Production Engineering and Mechanical Design, Tanta University, Tanta 31527, Egypt
M. Elhadary: Department of Mechanical Engineering, Faculty of Engineering, Alexandria University, Alexandria, Egypt
Defa Wu: State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Yinshui Liu: State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Corresponding authors.

Journal volume & issue: Vol. 58, no. 3
pp. 1077 – 1087

Abstract

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In this paper, an alternative method to predict the noise of a submersible Axial Piston Pump (APP) for different valve seat materials is presented. The proposed method is composed of an Artificial Neural Network (ANN) model trained using experimental data and integrated with a hybrid algorithm consists of Cat Swarm Optimization (CSO) and Firefly Algorithm (FA) algorithms. The hybrid CSFA algorithm is used as a subroutine in the ANN model to estimate the ANN weights. The FA is used as local operator to improve the exploitation ability of CSO. The obtained results prove the excellence of the proposed method in predicting the noise of APP considering four different valve seat materials (Polytetrafluoroethylene (PTFE), Polyetheretherketone (PEEK), Aliphatic polyamides (NYLON), and stainless steel (316 L)), five speed levels, and six system pressures. Moreover, the effects of different mechanical properties of the valve seat materials as well as operating conditions (speed and system pressure) have been investigated. Keywords: Axial piston pump, Valve seat materials, Noise prediction, Artificial neural network

Published in Alexandria Engineering Journal

ISSN: 1110-0168 (Print); 2090-2670 (Online)
Publisher: Elsevier
Country of publisher: Egypt
LCC subjects: Technology: Engineering (General). Civil engineering (General)
Website: http://www.journals.elsevier.com/alexandria-engineering-journal/

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