中国机械工程2026，Vol.37Issue(5)：1105-1110,1121,7.DOI:10.3969/j.issn.1004-132X.2026.05.010
涡街流量计探头位置优化的流场时程深度学习方法
Deep Learning Method of Flow Time History for Optimizing Position of Vortex Flowmeter Probes
摘要
Abstract
A vortex flowmeter used the time-varying features of the wake flow around a blunt body to measure flow field.A reasonable probe position might obtain a more robust flow signal,which improved signal processing and measurement accuracy.Based on the deep learning of flow time history data,a probe positioning optimization method was proposed to address the probe location issue in vortex flowmeters.The method was illustrated by using the flow around a triangular prism vortex generator.Feature dimen-sionality reduction was performed on the flow time history dataset and a comprehensive analysis of the time-varying flow features at the numerous measurement points within the wake was realized.Then,clustering analysis was applied to the low-dimensional representation codes to identify spatial distributions with simi-lar time-varying characteristics.Finally,by analyzing the flow characteristics of different categories,the significant regions of measured variable signals were obtained as the reasonable layout regions for the mea-suring points of the vortex flowmeters.The results show that the proposed method may provide a finer measurement point layout scheme than that of the traditional methods.And the reasonable sizes of the probes may be obtained according to the sizes of the characteristic areas,providing a new method for the de-sign of vortex flowmeters.关键词
涡街流量计/探头位置/流场时程深度学习/流动特征Key words
vortex flowmeter/position of probe/flow time history deep learning/flow feature分类
机械制造引用本文复制引用
战庆亮,曹子涵,王智勇,白春锦,刘鑫..涡街流量计探头位置优化的流场时程深度学习方法[J].中国机械工程,2026,37(5):1105-1110,1121,7.基金项目
辽宁省自然科学基金(2025-MSLH-108) （2025-MSLH-108）
辽宁教育厅研究计划(LJ212410151014) （LJ212410151014）
交通行业重点实验室开放课题(KLWRTBMC21-02) （KLWRTBMC21-02）
大连海事大学博联科研基金(3132023619) （3132023619）
