基于小波包分解的阈值消噪在 车载CAN总线上的应用

高印寒; 马喜来; 何丽桥; 杨开宇; 周晓华

doi:null

您当前的位置：

首页 >

文章列表页 >

基于小波包分解的阈值消噪在车载CAN总线上的应用

更新时间：2020-08-12

- 基于小波包分解的阈值消噪在车载CAN总线上的应用
- Application of threshold denoising based on wavelet packet decomposition to vehicular CAN-bus
- 光学精密工程 2007年15卷第3期页码：434-439
- 作者机构：
  
  1. 吉林大学测试科学实验中心,吉林长春,130025
  2. 吉林大学仪器科学与电气工程学院,吉林长春,130026
  3. 吉林大学物理学院,吉林长春,130025
- 作者简介：
- 基金信息：
- DOI：
  中图分类号： TP274
- 收稿日期：2006-10-19，
  
  修回日期：2007-01-18，
  
  网络出版日期：2007-06-30，
  
  纸质出版日期：2007-06-30
- 稿件说明：
移动端阅览
高印寒, 马喜来, 何丽桥, 等. 基于小波包分解的阈值消噪在车载CAN总线上的应用[J]. 光学精密工程, 2007,15(3):434-439.

GAO Yin-han, MA Xi-lai, HE Li-qiao, et al. Application of threshold denoising based on wavelet packet decomposition to vehicular CAN-bus[J]. Optics and precision engineering, 2007, 15(3): 434-439.
高印寒, 马喜来, 何丽桥, 等. 基于小波包分解的阈值消噪在车载CAN总线上的应用[J]. 光学精密工程, 2007,15(3):434-439. DOI：

GAO Yin-han, MA Xi-lai, HE Li-qiao, et al. Application of threshold denoising based on wavelet packet decomposition to vehicular CAN-bus[J]. Optics and precision engineering, 2007, 15(3): 434-439. DOI：

摘要

为了实现在车载CAN总线控制器故障产生不可预知干扰信号的情况下正确读出CAN总线上的故障码

提出了一种基于小波包分解的阈值消噪方法。将信号进行基于最小Shannon熵原理的最佳树小波包分解后

针对CAN总线传输信号特点

对高频和低频系数采取不同阈值处理的混合阈值消噪处理。对于高频系数

采用基于Stein无偏似然估计原理的自适应阈值;在干扰信号的统计特性未知的情况下

对低频系数阈值的选取采取保持频率单一和能量损耗小的双重标准。最后

由阈值处理后的系数重构信号

得到正确的传输码。实验结果表明

该混合阈值消噪处理方法对消除这种由CAN总线上的控制器故障引起的干扰

较传统的消噪技术提高1/3以上的信噪比

增加了后期读取CAN总线故障码的准确率。

Abstract

In order to identify the correct failure code in a vehicular CAN-bus disturbed by the unforeseen damage of the controllers

application of threshol denosing based on wavelet packet decomposition was proposed here. The disturbed signal was decomposed into the multiscale wavelet domain by minimal Shannon entropy criteria. Then

the threshold based on Stein's unbiased risk estimation was used to eliminate the noise in the high frequency coefficients and the double criteria

and holding frequency singleness and little energy losses were used to set the threshold of the low frequency coefficients. Finally

the denoised signal was achieved by the invert WPD. Experimental results show that the S/N radio of the denoising technique in proposed method has been increased 1/3 over that of tranditional method

which can effectively get the correct facult-code while the some controller is damaged in CAN bus.

关键词

Keywords

references

. 张禾,梅树才. 基于CAN总线的电动汽车实验平台 . 汽车电子,2005,(5):76-78. ZHANG H,MEI SH C.The CAN bus based platform for electric vehicle experiments . Auto. Electron., 2005,(5):76-78. (in Chinese)

. COPPOLA L,BUSO S. Application of Fourier and wavelet transforms to the identification of EMI noise sources in SMPSs[J]. IEEE Trans. Electromagn. Comp., 2003,47(7):160-168.

. ANTONINI G. Wavelet packet-based EMI signal processing and source identification[J]. IEEE Trans. Electromagn. Comp., 2001,43(2):140-148.

. 赵未莲. 基于小波变换的阈值语音信号去噪[J]. 重庆科技学院学报,2005,(4):73-75. ZHAO W L. Speech signal denoising of threshold based on wavelet transformation . J. Chongqing Tech. Coll., 2005,(4):73-75. (in Chinese)

. 孙涛,黄天戍,李明. 小波包消噪提高小波网络故障识别性能[J]. 哈尔滨工业大学学报,2005,(4):561-564. SUN T, HUANG T SH, LI M. Fault detection and isolation capability improvement of wavelet neural network basing on wavelet packet transform denoising[J]. J. Harbin Inst. Technol.,2005,(4):561-564. (in Chinese)

. MENG J L,QUAN P,ZHANG H C.Optimal threshold determination for multiscale product in wavelet denoising . Proceeding of ISCIT,2005:570-573.

. 杨亚青, 钟丽萍. 去噪小波包能量法在水声信号识别中的应用[J]. 湛江海洋大学学报,2005,(2):69-72. YANG Y Q, ZHONG L P. Application of the denoising wavelet-packet energy method to the recognition of underwater acoustic signal[J]. J. Zhanjiang Ocean Univ., 2005,(2):69-72. (in Chinese)

. 戎历霞. 基于最优小波包基的信号去噪算法[J]. 德州学院学报,2005,(4):72-75. RONG L X. Signal denoising algorithm based on best wavelet packet groups[J].J. Dezhou Univ.,2005,(4):72-75. (in Chinese)

. ZHAO ZH D. Wavelet shrinkage denoising by generalized threshold function . 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005:5501-5506.

. HITTON M L,OGDEN R T.Data annlytic wavelet threshold selection in 2-D signal denoising[J]. IEEE Trans. Signal Process.,1997,45(2):496-500.

. 李会方,俞卞章. 基于小波的多重分形图像去噪新算法[J]. 光学精密工程,2002,12(3):305-310. LI H F, YU B Z.New wavelet-based algorithm for denoising of multifractal images[J].Opt. Precision Eng.,2002,12(3):305-310. (in Chinese)

. 孙俊喜,陈亚珠. 一种具有边缘保持特性的超声图像小波域阈值去噪新方法[J]. 光学精密工程,2002,10(5):429-433. SUN J X,CHEN Y ZH.Novel speckle reduction for medical ultrasound images based on edge preservation[J].Opt. Precision Eng.,2002,10(5):429-433. (in Chinese)

. 林晓梅,李琳娜,牛刚. 基于小波边缘检测的图像去噪方法[J]. 光学精密工程,2004,12(1):88-93. LIN X M,LI L N,NIU G. Image denoising based on wavelete detection[J]. Opt. Precision Eng.,2004,12(1): 88-93.(in Chinese)

. 王欣,于晓,隋永新,等. 基于小波的图象处理在电晕检测中的应用[J]. 光学精密工程,2006,14(4):714-719. WANG X,YU X,SUI YX,et al.. Application of multiwavelet based image processing to corona detection[J]. Opt. Precision Eng.,2006,14(4):714-719.(in Chinese)

. 刘红,翟林培,高鹰,等. 提升小波变换在图像压缩中的应用[J]. 光学精密工程,2005,13(增):201-205. LIU H,ZHAI P L,GAO Y,et al.. Lifting wavelet transform and its application in image compression[J]. Opt. Precision Eng.,2005,13(supp.):201-205.(in Chinese)

. 陈升来,黄廉卿,郭静寰. 基于整型提升小波变换的图像处理及DSP实现[J]. 光学精密工程,2006,14(13):498-502. CHEN SH L,HUANG L Q,GUO J H. Image processing based on integral lifting scheme and its implementation by DSP[J]. Opt. Precision Eng.,2006,14(3):498-502.(in Chinese)

浏览量

454

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据