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/
Keywords
Acknowledgements
Funding: The research presented in this article was financially supported by the National Natural Science Fund (Grant No. 52075012) and Key Technologies of hydrostatic Workbench and Rotary Table (Grant No. TC210H035).
Authors' contributions: All authors contributed to the conceptualization and design of the study, and Jiaqing Luo completed the first draft of the manuscript, including algorithm programming, simulation operations and data result processing. Yongsheng Zhao analyzed the calculation results and revised the manuscript to form the final submitted version. Ying Li, Caixia Zhang and Honglie Ma reviewed and approved the manuscript. All authors have extensively revised and approved the final manuscript.
Competing interests: The author declares that there are no competing interests.
Data availability: The data used to support the findings of this study are available from the corresponding authors upon request.
Citation
Zhao, Y., Luo, J., Li, Y., Zhang, C. and Ma, H. (2024), "The performance monitoring system for a hydrostatic turntable: an improved intelligent algorithm based on the IPSO-NN model", Industrial Lubrication and Tribology, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ILT-03-2024-0081
Publisher
:Emerald Publishing Limited
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