Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems

Hydrostatic lead screw is a key transmission component of ultra-precision machine tools, yet the induced thermal errors present a major hurdle to maintaining positioning accuracy. Existing thermal analysis methods are often limited by the empirical placement of temperature sensors, leading to an inc...

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Main Authors: Jun Zha, Xiaofei Peng, Zhiyan Cai, Fei Xue
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Results in Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025022959
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author Jun Zha
Xiaofei Peng
Zhiyan Cai
Fei Xue
author_facet Jun Zha
Xiaofei Peng
Zhiyan Cai
Fei Xue
author_sort Jun Zha
collection DOAJ
description Hydrostatic lead screw is a key transmission component of ultra-precision machine tools, yet the induced thermal errors present a major hurdle to maintaining positioning accuracy. Existing thermal analysis methods are often limited by the empirical placement of temperature sensors, leading to an incomplete understanding of the complex temperature field. To address this gap, this research proposes a novel method that integrates simulation with a data-driven optimization strategy. The core of our approach involves using the K-means clustering algorithm to optimize the selection of temperature measurement points on the hydrostatic screw nut, ensuring a more representative thermal characterization. Simulations and experimental verification were conducted to assess the temperature rise characteristics of the helical oil film using this optimized configuration. Results indicate that rotational speed has a minimal effect on the temperature rise, while the thermal positioning error escalates with the temperature of these critical points. This research provides a robust methodology for thermal analysis, supporting the wider application of hydrostatic lead screws in ultra-precision machine tools.
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institution DOAJ
issn 2590-1230
language English
publishDate 2025-09-01
publisher Elsevier
record_format Article
series Results in Engineering
spelling doaj-art-b4feee35e50242f7b28751504d26febb2025-08-20T03:12:56ZengElsevierResults in Engineering2590-12302025-09-012710622310.1016/j.rineng.2025.106223Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed SystemsJun Zha0Xiaofei Peng1Zhiyan Cai2Fei Xue3School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710000, China; State Key Laboratory of Mechanical Transmission for Advanced Equipment, Chongqing University, China; Corresponding author. Tel.: +86-18392186598.School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710000, ChinaSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710000, ChinaSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710000, China; Corresponding author. Tel.: +86-18392186598.Hydrostatic lead screw is a key transmission component of ultra-precision machine tools, yet the induced thermal errors present a major hurdle to maintaining positioning accuracy. Existing thermal analysis methods are often limited by the empirical placement of temperature sensors, leading to an incomplete understanding of the complex temperature field. To address this gap, this research proposes a novel method that integrates simulation with a data-driven optimization strategy. The core of our approach involves using the K-means clustering algorithm to optimize the selection of temperature measurement points on the hydrostatic screw nut, ensuring a more representative thermal characterization. Simulations and experimental verification were conducted to assess the temperature rise characteristics of the helical oil film using this optimized configuration. Results indicate that rotational speed has a minimal effect on the temperature rise, while the thermal positioning error escalates with the temperature of these critical points. This research provides a robust methodology for thermal analysis, supporting the wider application of hydrostatic lead screws in ultra-precision machine tools.http://www.sciencedirect.com/science/article/pii/S2590123025022959Hydrostatic lead screwtemperature risetemperature sensitive pointthermal positioning error
spellingShingle Jun Zha
Xiaofei Peng
Zhiyan Cai
Fei Xue
Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems
Results in Engineering
Hydrostatic lead screw
temperature rise
temperature sensitive point
thermal positioning error
title Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems
title_full Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems
title_fullStr Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems
title_full_unstemmed Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems
title_short Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems
title_sort analysis and prediction of thermally induced positioning error in hydrostatic lead screw feed systems
topic Hydrostatic lead screw
temperature rise
temperature sensitive point
thermal positioning error
url http://www.sciencedirect.com/science/article/pii/S2590123025022959
work_keys_str_mv AT junzha analysisandpredictionofthermallyinducedpositioningerrorinhydrostaticleadscrewfeedsystems
AT xiaofeipeng analysisandpredictionofthermallyinducedpositioningerrorinhydrostaticleadscrewfeedsystems
AT zhiyancai analysisandpredictionofthermallyinducedpositioningerrorinhydrostaticleadscrewfeedsystems
AT feixue analysisandpredictionofthermallyinducedpositioningerrorinhydrostaticleadscrewfeedsystems