西北工程技术学报2025，Vol.24Issue(1)：1-7,7.
基于联合稀疏表示的调相机振动信号数据压缩方法
A Phase Compensator Vibration Signal Data Compression Method Based on Joint Sparse Representation
摘要
Abstract
With the increasing volume of vibration signal data from phase compensators,the challenges of data storage and real-time monitoring are becoming more significant.Phase compensator fault vibration signals typically contain multiple frequency components,and the frequency characteristics of different fault signals can vary considerably,leading to a significant reduction in signal sparsity and increasing the difficulty of compression and storage.To address this issue,this paper proposes a joint sparse representation-based method for the compression and storage of phase compensator vibration signals.The method combines a greedy iterative algorithm and the K-SVD(K-singular value decomposition)dictionary learning algorithm to introduce a framework for adaptive joint sparse representation,which allows for effective analysis of the dictionary atoms and measurements to achieve efficient compression and storage of the phase compensator vibration signals.Experimental results show that the proposed method not only saves storage space but also achieves a Pearson correlation coefficient greater than 0.9 between the original and reconstructed time-domain signals for different fault types.Furthermore,the method maintains high signal recovery accuracy in noisy environments and demonstrates superior robustness and applicability compared to traditional methods.关键词
调相机/K-SVD(K均值奇异值分解)算法/联合稀疏表示/压缩感知Key words
phase compensator/K-singular value decomposition(K-SVD)algorithm/joint sparse representation/com-pressive sensing分类
机械工程引用本文复制引用
丁子杨,赵文强,周军,王正伟,李富才..基于联合稀疏表示的调相机振动信号数据压缩方法[J].西北工程技术学报,2025,24(1):1-7,7.基金项目
国网青海省电力公司科技项目(522807230005) （522807230005）
