湖南大学学报（自然科学版）2025，Vol.52Issue(6)：36-43,8.DOI:10.16339/j.cnki.hdxbzkb.2025174
利用卷积自编码器的体压分布数据重构及分析
Reconstruction and Analysis of Body Pressure Distribution Data with Convolutional Autoencoder
摘要
Abstract
To address the noise issue in experimentally acquired body pressure distribution data,this study proposes a convolutional autoencoder-based data reconstruction method to enhance data quality and usability.First,the body pressure distribution data is normalized.And Gaussian noise is added to construct the training set.A convolutional autoencoder model is designed and used for feature extraction and denoising.Subsequently,experimentally collected body pressure distribution data is utilized as the test set to evaluate the accuracy and stability of the reconstruction results.Experimental results demonstrate that the model achieves a mean relative error of 0.010 with a standard deviation of 0.018 across 98 test samples,indicating high accuracy and stability.Finally,the trained model is applied to process experimentally collected body pressure data,revealing the variation patterns of pressure distribution metrics with seat positions.关键词
汽车座椅系统/自编码器/体压分布/乘坐舒适性Key words
automotive seating systems/autoencoders/body pressure distribution/sitting comfort分类
交通运输引用本文复制引用
郭巍,阮金伟,马晓兰,周蒙蒙,彭强..利用卷积自编码器的体压分布数据重构及分析[J].湖南大学学报（自然科学版）,2025,52(6):36-43,8.基金项目
广西重点研发计划项目(AB23026112) （AB23026112）
Key Research and Development Program of Guangxi(AB23026112) （AB23026112）
