The performance monitoring system for a hydrostatic turntable: an improved intelligent algorithm based on the IPSO-NN model

Abstract

Purpose The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable. Design/methodology/approach This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables. Findings The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel. Originality/value Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/