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

IF 1.5 4区工程技术 Q3 ENGINEERING, MECHANICAL Industrial Lubrication and Tribology Pub Date : 2024-09-06 DOI:10.1108/ilt-03-2024-0081

Yongsheng Zhao, Jiaqing Luo, Ying Li, Caixia Zhang, Honglie Ma

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引用次数: 0

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/

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静压转台性能监测系统：基于 IPSO-NN 模型的改进型智能算法

目的将改进的 PSO（IPSO）算法与人工神经网络（ANN）模型相结合，对静压转台的承载性能进行智能监测。研究结果本文提出的理论模型提高了静压转台工作性能的准确性，为静压转台的智能监测提供了新的方向。原创性/价值理论新颖性：设计了基于IPSO算法的ANN模型，对静压转台的承载性能进行智能监测；研究表明，IPSO-NN模型的收敛精度和收敛速度分别比IPSO-NN模型提高了52.55%和10%；提出的模型可用于解决静压转台智能监测中的多维非线性问题。同行评议本文的同行评议记录可在以下网址查阅：https://publons.com/publon/10.1108/ILT-03-2024-0081/。

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来源期刊

Industrial Lubrication and Tribology 工程技术-工程：机械

CiteScore

3.00

自引率

18.80%

发文量

129

审稿时长

1.9 months

期刊介绍： Industrial Lubrication and Tribology provides a broad coverage of the materials and techniques employed in tribology. It contains a firm technical news element which brings together and promotes best practice in the three disciplines of tribology, which comprise lubrication, wear and friction. ILT also follows the progress of research into advanced lubricants, bearings, seals, gears and related machinery parts, as well as materials selection. A double-blind peer review process involving the editor and other subject experts ensures the content''s validity and relevance.