摘要
无线传感器网络节点资源非常有限,若实时采集传输振动信号,由于信号变化快,数据量大,网络节点将会因为资源过早耗尽而失效,并且上位机需要很大的数据存储空间。为了解决上述问题,提出了一种针对振动信号进行压缩编码的算法,并编程将其移植到节点DSP中。首先,采用5/3提升小波对振动数据进行处理;然后,利用嵌入式零数小波对得到的小波系数进行压缩编码;最后,为了进一步提高压缩比,便于节点传输数据。对上述结果进行霍夫曼压缩编码,对数据的解码、解压缩和重构则由上位机软件完成。讨论了初始阈值和小波分解层数的选取对压缩效率的影响。实验结果表明,该算法可有效压缩振动信号(压缩比高达9.5),且在保留其频域主要特征的情况下,使传输数据量大大减少,节省了网络节点资源和上位机存储空间。
The resources of node in wireless sensor networks are limited.If the vibration signal is collected and transmitted in real-time,because the signal changes rapidly and the amount of data is large,on the one hand,the node will be invalidated because of the early exhaustion of resources,on the other hand,there is a lot of data storage space which the PC should takes.In order to solve the problem mentioned above,a compression and coding algorithm is proposed for vibration signal,it is also programmed and implanted to DSP in sensor node.The algorithm is as follows: first,the vibration data is processed by 5/3 lifting wavelet,and then the wavelet coefficients obtained are compressed and coded by embedded zerotree wavelet.In order to further improve the compression ratio,and for the sensor node which can transfer data easily,the results above are compressed and coded by huffman algorithm.The decoding,decompression and reconstruction of data are completed by software in PC.Finally,the effects of selection of initial threshold and wavelet decomposition levels to compression efficiency are discussed.The experimental results show that the vibration data can be compressed effectively(compression ratio up to 9.5),while retaining the main features of vibration signal in frequency domain,the data transmitted is greatly reduced,the resources of network node and the storage space of PC are saved.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2013年第2期236-240,338,共5页
Journal of Vibration,Measurement & Diagnosis
基金
国家自然科学基金资助项目(50875196)
国家重点基础研究发展计划("九七三"计划)资助项目(2009CB724304)
关键词
振动信号
无线传感器网络
5
3提升小波
嵌入式零数小波
霍夫曼压缩编码算法
vibration signal,wireless sensor networks,5/3 lifting wavelet,embedded zerotree wavelet,Huffman compression and coding algorithm
作者简介
王楠，男，1983年12月生，博士研究生。主要研究方向为无线传感器网络测量技术及应用、机械设备状态监测和故障诊断。曾发表《Research on linear wireless sensor networks used for online monitoring of rolling bearing in freight train》（《Journal of Physics： Conference Series 》 2011, Vol. 305,No. 1）等论文。E-mail：heroyoyu@126.com
