轻工机械2024，Vol.42Issue(4)：69-74,81,7.DOI:10.3969/j.issn.1005-2895.2024.04.010
基于盲源分离的纱线张力信号去噪研究
Study on Denoising Yarn Tension Signal Based on Blind Source Separation
摘要
Abstract
To address the problem of low accuracy of the collected yarn tension signal and the difficulty in reading the tension value,a blind source separation method of the yarn tension signal combined with empirical modal decomposition(EMD),singular value decomposition(SVD)and fast independent component analysis(FastICA)was proposed.The empirical modal decomposition method was applied to adaptive decomposition of tension signal to obtain intrinsic modal function(IMF)components which have smooth and linear characteristics.The intrinsic modal function and the tension signal were formed into a multidimensional observation signal,and covariance matrix was decomposed by singular value decomposition to calculate the adjacent singular value differences and determine the number of source signals.The correlation coefficients between the IMF components and the tension signals were calculated,and the IMF components were selected to be reconstructed with the tension signals to obtain new multichannel signals.Fast independent component analysis was performed on the obtained multichannel observation signals to achieve noise separation of the yarn tension signals.The experimental platform denoising experiment was built to verify the algorithm.The results show that the method can effectively separate the yarn tension signal and improve the signal-to-noise ratio.The signal-to-noise ratio is improved by 2.678 1 dB compared with the 15-layer wavelet decomposition denoising method,which completes the noise removal of the yarn tension free vibration signal.关键词
纺织机械/纱线张力/经验模态分解/快速独立成分分析/盲源分离Key words
textile machinery/yarn tension/EMD(empirical modal decomposition)/FastICA(fast independent component analysis)/blind source separation分类
轻工纺织引用本文复制引用
董晓洁,贾江鸣,贺磊盈,万昌江..基于盲源分离的纱线张力信号去噪研究[J].轻工机械,2024,42(4):69-74,81,7.基金项目
浙江省科学技术厅重点研发计划项目选定委托项目(2022C01065). （2022C01065）
