{"title":"Implementation and Analysis of Compressed Sensing Technology for Wireless Sensor","authors":"Liming Qian, Meng Zha, Feng Guo","doi":"10.1109/IAEAC54830.2022.9929731","DOIUrl":null,"url":null,"abstract":"In view of the characteristics of energy consumption in wireless sensor network nodes in the process of mechanical vibration detection, compression sensing technology (CS) was introduced. The system completed the sparse representation of the signal and the design of the orthogonal measurement matrix in the DSP of the terminal nodes. After wireless transmission of the measurement data to the coordinator node, with the help of CCSLink platform, it realized the reconstruction of the signal in the MATLAB environment. It was found that the sparse signal after DCT transformation had better sparsity, and the signal reconstructed by OMP algorithm had higher reconstruction accuracy. The introduction of compressed sensing technology not only reduced the data transmission capacity of wireless nodes, reduced the power consumption of data transmission, and also extended the life of nodes, which proved the feasibility of compressed sensing technology in the field of mechanical vibration monitoring.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC54830.2022.9929731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In view of the characteristics of energy consumption in wireless sensor network nodes in the process of mechanical vibration detection, compression sensing technology (CS) was introduced. The system completed the sparse representation of the signal and the design of the orthogonal measurement matrix in the DSP of the terminal nodes. After wireless transmission of the measurement data to the coordinator node, with the help of CCSLink platform, it realized the reconstruction of the signal in the MATLAB environment. It was found that the sparse signal after DCT transformation had better sparsity, and the signal reconstructed by OMP algorithm had higher reconstruction accuracy. The introduction of compressed sensing technology not only reduced the data transmission capacity of wireless nodes, reduced the power consumption of data transmission, and also extended the life of nodes, which proved the feasibility of compressed sensing technology in the field of mechanical vibration monitoring.