摘要
大型发电机组远程状态监测系统中实时数据的存储与网络传输对数据压缩和重构技术提出了较高的要求。文中给出一种提升小波变换与混合熵编码技术相结合的数据压缩方法。首先利用基于提升格式的双正交滤波器组对实时数据进行小波分解,然后对小波系数进行阈值量化,最后通过混合熵编码技术对保留的系数进行编码,以进一步提高压缩效率。对实际发电机组实时数据进行了压缩试验,结果表明,有损压缩技术和无损压缩技术的结合可以获得较高的压缩比,能够较好地满足大型发电机组实时数据的存储和传输需求,是一种有效和实用的实时数据压缩方法。
For the urgent demand of real-time data compression of large turbine-generator units online monitoring and remote diagnosis, a novel real-time data compression and reconstruction method combining lifting wavelet transform and hybrid entropy coding is proposed. The signal to be compressed is firstly decomposed with biorthogonali filters based on lifting wavelet transform and the hard-threshold method is then applied to the wavelet coefficients. In order to implement higher efficient compression, a hybrid entropy coding scheme is employed to code the reserved coefficients. This method has been applied to the real-time data acquired from a large turbine-generator unit. Simulation results indicate that the proposed scheme which combines both lossy and lossless compression techniques can achieve satisfactory compression performance in applications.
出处
《电力系统自动化》
EI
CSCD
北大核心
2007年第22期65-69,共5页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(50606008)~~
关键词
发电机组监测
数据压缩
小波变换
提升格式
熵编码
turbine-generator units monitoring
data compression
wavelet transform
lifting scheme
entropy coding
