第18卷第10期 2010年10月
文章编号
1004-924X(2010)102280-08
光学精密工程
Optics and Precision Engineering
Vol.18No,10
Oct.2010
面向IP模式测控系统的PLSR-SBR双层压缩
洪晓斌，刘桂雄
（华南理工大学机械与汽车工程学院，广东广州510640）
摘要：针对以太网测控网络存在数据冲突导致系统实时性、可靠性降低间题，提出了基于偏最小二乘回归(PLSR)SBR的双层压缩方法。第一层建立主参量与所有辅助参量的确定模型，利用压缩有效性指标确定主成分，完成主参量的信息压端。第二层基于改进的SBR，通过选取辅助参量中的基础序列，建立基础信号；在满足拟合误差条件下，逐步将每一个输辅助参量序列映射到基础信号上，完成对辅助参量的数据压缩。该方法重点解决辅助参量和主参量中的解释潜变量和反映潜变量相关程度最大、基础信号由最少基础序列组成、辅助参量实现最小变长分解个数及基础信号独立更新原则等关键间题。最后将该方法应用于IP模式乙醇浓度测控系统。实验结果表明，在IP模式测控系统同时具有主参量和辅助参量，且不同参量间存在相关性时，该方法可在允许拟合相对误差为5%的情况下，使压缩率达到68%以上，从面有效地降低以太网测控网络数据冲突程度。
关键词：IP模式测控系统；数据压编；偏最小二乘国归；改进的SBR
中图分类号：TN911.7：TP273
文献标识码：A
doi;10.3788/OPE,20101810.2280
Double-layercompressionmethodbasedonPLSR-SBR
forIPmodemeasurementandcontrolsystem
HONG Xiao-bin, LIU Gui-xiong
(School of Mechanical and Automotive Engineering,
SouthChina University ofTechnology，Guangzhou51064l，China)
Abstract: To address the existing problems in Ethernet measurement and control networks, such as real-time and reliability caused by the collision of measurement and control data, a double-layer compression method based on Partial Least Square Regression-self Based Regression(PLSR-SBR) was induced to the IP Mode Measurement and Control System(IMMCS). In the first layer, the model of main parameters and all auxiliary parameters was built up based on PLSR. The principal score of main parameter was determined by the efficient compression index to finish the information compression of main parameter. In the second layer, the auxiliary parameters were cornpressed based on a modified SBR to set up a basic signal., To ensure the fitting error to be smaller than the setting value, every auxiliary parameter sequence in the auxiliary parameters or the de composed sequences were mapped in turn to a definitive basic signal to complete the data compression of tho auxiliary parameters. Innovative technologies for some key problems were addressed in the method, including the confirmation of maximum correlation degree of interpreting latent variables and reflecting latent variables,
收稿日期：2009-12-10；修订日期：2010-03-10
基金项目：教育部新世纪优秀人才支持计划资助项目（No.NCET-08-0211)；广东省自然科学基金资助项目（No.
000601006000（100000010200 金资助项目（No.2009ZM0042）