液压与气动2026,Vol.50Issue(1):1-10,10.DOI:10.11832/j.issn.1000-4858.2026.01.001
融合小波变换与多模态大模型的液压泵仿真信号一致性评估
A Simulation Signal Consistency Assessment of Hydraulic Pump Based on Wavelet Time-frequency and Emergence of Multimodal Large Model
摘要
Abstract
The effectiveness of digital twin systems relies on the dynamic consistency between virtual models and physical entities.As the core power component of hydraulic systems,hydraulic pumps exhibit strongly non-stationary operating signals,such as pressure pulsations and vibration shocks.Traditional consistency assessment methods based on mean squared error or frequency-domain statistics struggle to effectively capture structural dynamic deviations like transient impacts and parameter drifts.To address this,a consistency assessment method integrating continuous wavelet transform and a multimodal large model is proposed.This method involves collecting simulation and measured signals from the hydraulic pump,constructing residual and real noise signals,and converting them into time-frequency images via continuous wavelet transform to highlight dynamic features.Subsequently,the image encoder of a domain-adapted multimodal large model is utilized to extract deep semantic features,and consistency is quantified using feature cosine similarity.Experimental results demonstrate that the proposed method possesses a significant ability to discriminate differences in non-stationary dynamic responses,outperforming traditional evaluation metrics.It can accurately identify model structural deviations under working conditions such as internal leakage and bearing wear,providing reliable technical support for the verification,optimization,and engineering application of hydraulic pump digital twin models.关键词
液压泵/连续小波变换/多模态大模型/一致性评估/特征相似度/数字孪生Key words
hydraulic pump/continuous wavelet transform/the emergence of multimodal large model/consistency assessment/feature similarity/digital twin分类
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范亚利,石健,韩剑,方家玥,司瑾,周阳..融合小波变换与多模态大模型的液压泵仿真信号一致性评估[J].液压与气动,2026,50(1):1-10,10.基金项目
国家重点研发计划(2022YFC2204102) (2022YFC2204102)