Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm

High-speed motorized spindle heating will produce thermal error, which is an important factor affecting the machining accuracy of machine tools. The thermal error model of high-speed motorized spindles can compensate for thermal error and improve machining accuracy effectively. In order to confirm t...

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Autores principales:	Zhaolong Li, Bo Zhu, Ye Dai, Wenming Zhu, Qinghai Wang, Baodong Wang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	high-speed motorized spindle thermal drift temperature-sensitive points Beetle antennae search algorithm thermal error modeling Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/1dbf381e1c264211bc89e6790375098f
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id	oai:doaj.org-article:1dbf381e1c264211bc89e6790375098f
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spelling	oai:doaj.org-article:1dbf381e1c264211bc89e6790375098f2021-11-25T18:12:18ZResearch on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm10.3390/machines91102862075-1702https://doaj.org/article/1dbf381e1c264211bc89e6790375098f2021-11-01T00:00:00Zhttps://www.mdpi.com/2075-1702/9/11/286https://doaj.org/toc/2075-1702High-speed motorized spindle heating will produce thermal error, which is an important factor affecting the machining accuracy of machine tools. The thermal error model of high-speed motorized spindles can compensate for thermal error and improve machining accuracy effectively. In order to confirm the high precision thermal error model, Beetle antennae search algorithm (BAS) is proposed to optimize the thermal error prediction model of motorized spindle based on BP neural network. Through the thermal characteristic experiment, the A02 motorized spindle is used as the research object to obtain the temperature and axial thermal drift data of the motorized spindle at different speeds. Using fuzzy clustering and grey relational analysis to screen temperature-sensitive points. Beetle antennae search algorithm (BAS) is used to optimize the weights and thresholds of the BP neural network. Finally, the BAS-BP thermal error prediction model is established. Compared with BP and GA-BP models, the results show that BAS-BP has higher prediction accuracy than BP and GA-BP models at different speeds. Therefore, the BAS-BP model is suitable for prediction and compensation of spindle thermal error.Zhaolong LiBo ZhuYe DaiWenming ZhuQinghai WangBaodong WangMDPI AGarticlehigh-speed motorized spindlethermal drifttemperature-sensitive pointsBeetle antennae search algorithmthermal error modelingMechanical engineering and machineryTJ1-1570ENMachines, Vol 9, Iss 286, p 286 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	high-speed motorized spindle thermal drift temperature-sensitive points Beetle antennae search algorithm thermal error modeling Mechanical engineering and machinery TJ1-1570
spellingShingle	high-speed motorized spindle thermal drift temperature-sensitive points Beetle antennae search algorithm thermal error modeling Mechanical engineering and machinery TJ1-1570 Zhaolong Li Bo Zhu Ye Dai Wenming Zhu Qinghai Wang Baodong Wang Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm
description	High-speed motorized spindle heating will produce thermal error, which is an important factor affecting the machining accuracy of machine tools. The thermal error model of high-speed motorized spindles can compensate for thermal error and improve machining accuracy effectively. In order to confirm the high precision thermal error model, Beetle antennae search algorithm (BAS) is proposed to optimize the thermal error prediction model of motorized spindle based on BP neural network. Through the thermal characteristic experiment, the A02 motorized spindle is used as the research object to obtain the temperature and axial thermal drift data of the motorized spindle at different speeds. Using fuzzy clustering and grey relational analysis to screen temperature-sensitive points. Beetle antennae search algorithm (BAS) is used to optimize the weights and thresholds of the BP neural network. Finally, the BAS-BP thermal error prediction model is established. Compared with BP and GA-BP models, the results show that BAS-BP has higher prediction accuracy than BP and GA-BP models at different speeds. Therefore, the BAS-BP model is suitable for prediction and compensation of spindle thermal error.
format	article
author	Zhaolong Li Bo Zhu Ye Dai Wenming Zhu Qinghai Wang Baodong Wang
author_facet	Zhaolong Li Bo Zhu Ye Dai Wenming Zhu Qinghai Wang Baodong Wang
author_sort	Zhaolong Li
title	Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm
title_short	Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm
title_full	Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm
title_fullStr	Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm
title_full_unstemmed	Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm
title_sort	research on thermal error modeling of motorized spindle based on bp neural network optimized by beetle antennae search algorithm
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1dbf381e1c264211bc89e6790375098f
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Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm

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