利用平稳小波变换处理FBG传感信号
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摘要
FBG传感系统中,噪声的存在严重影响了解调系统中心波长检测的精确度。小波变换具有强大的时频分析能力,利用平稳小波变换对FBG反射谱信号进行了去噪处理,并与普通离散小波变换的去噪效果进行了对比。结果表明:对于实际FBG反射谱,该方法信噪比要比普通离散小波变换高出3 dB,而均方差仅为普通离散小波变换的1/4。而且该方法保证了消噪后FBG反射谱信号峰值即对应中心波长,克服了普通离散小波变换因下采样操作而造成的非线性相位和非平移不变的缺点。
Signals in fiber Bragg grating(FBG) sensing demodulation system always have noises,which deteriorate the detection accurate of demodulation result.Wavelet transform was chosen to process the FBG reflection spectrum signals because of its powerful ability in time-frequency analysis.Stationary wavelet transform was applied to de-noising FBG reflection spectrum signals,and compared with the denoising effect by using ordinary discrete wavelet transform.The result shows that the actual FBG reflection spectrum′s signal-to-noise ratios(SNR) by using this method is 3 dB higher than the SNR using ordinary discrete wavelet transform.Simultaneously,its mean squared error(MSE) is only a quarter of the MSE using ordinary discrete wavelet transform.And this method can effectively ensure the Bragg wavelength of de-noising FBG reflection spectrum at the spectrum peak,and overcome the shortcoming of non-linear phase and non-shift-invariant which is caused by sub-sample process in ordinary discrete wavelet transform.
Signals in fiber Bragg grating(FBG) sensing demodulation system always have noises,which deteriorate the detection accurate of demodulation result.Wavelet transform was chosen to process the FBG reflection spectrum signals because of its powerful ability in time-frequency analysis.Stationary wavelet transform was applied to de-noising FBG reflection spectrum signals,and compared with the denoising effect by using ordinary discrete wavelet transform.The result shows that the actual FBG reflection spectrum′s signal-to-noise ratios(SNR) by using this method is 3 dB higher than the SNR using ordinary discrete wavelet transform.Simultaneously,its mean squared error(MSE) is only a quarter of the MSE using ordinary discrete wavelet transform.And this method can effectively ensure the Bragg wavelength of de-noising FBG reflection spectrum at the spectrum peak,and overcome the shortcoming of non-linear phase and non-shift-invariant which is caused by sub-sample process in ordinary discrete wavelet transform.
引文
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[15]Yu Kaiping,Zou Jingxiang,Yang Bingyuan.Study onperformance and application of the wavelet function[J].Journal of Harbin Institute of Technology,2000,32(2):36-39.(in Chinese)于开平,邹经湘,杨炳渊.小波函数的性质及其应用研究[J].哈尔滨工业大学学报,2000,32(2):36-39.
[16]Mortazavi S H,Shahrtash S M.Comparing denoisingperformance of DWT,WPT,SWT and DT-CWT for partialdischarge signals[C]//Proceedings of 43rd InternationalConference on UPEC,2008:1-6.
[2]Liang Youcheng,Jiang Shaoji,Yu Zhiqiang,et a1.FiberBragg grating sensor demodulation technique based onasymmetric F-P filter[J].Infrared and Laser Engineering,2007,36(6):909-909.(in Chinese)梁有程,江绍基,余志强,等.基于非对称F-P滤波器的光纤光栅解调技术[J].红外与激光工程,2007,36(6):909-909.
[3]Bai Quan,Zhu Fusheng,Bian Jingmei.Simulation ofearthquake ground motion based on discrete stationarywavelet transform[J].World Earthquake Engineering,2009,25(3):124-129.(in Chinese)白泉,朱浮生,边晶梅.基于平稳离散小波变换的地震动时程模拟[J].世界地震工程,2009,25(3):124-129.
[4]Zhou Wei.MATLAB Advanced Technology of WaveletAnalysis[M].Xi′an:Xidian University Press,2006.(in Chinese)周伟.MATLAB小波分析高级技术[M].西安:西安电子科技大学出版社,2006.
[5]Phinyomark A,Limsakul C,Phukpattaranont P.An optimalwavelet function based on wavelet denoising formultifunction myoelectric control[C]//Proceedings of 6thInternational Conference on ECTI-CON,2009:1098-1101.
[6]Zhang Feng,Liu Shangqian,Wang Dabao.A new correctionmethod of IRFPA nonuniformity based on stationary wavelettransform[J].Acta Photonica Sinica,2009,38(8):2135-2138.(in Chinese)张峰,刘上乾,汪大宝.一种新的基于平稳小波变换的红外焦平面非均匀性校正技术[J].光子学报,2009,38(8):2135-2138.
[7]Zhou Yanjiang,Pan Yishan.Method research and application ofrock-burst signal de-noising based on wavelet transformation[J].Coalmining Technology,2009,14(1):29-31.(in Chinese)周彦江,潘一山.基于小波变换的矿震信号去噪方法研究与应用[J].煤矿开采,2009,14(1):29-31.
[8]Dai Longcheng,Xuan Yimin,Yin Jian.Denoising methodsand its applications in sensing signals processing noises[J].Acta Armamentarii,2003,24(2):257-260.(in Chinese)戴龙成,宣益民,尹健.小波消噪及其在传感信号处理中的应用[J].兵工学报,2003,24(2):257-260.
[9]Wu Zhaoxia,Yan Shujuan,Li Zhiquan.Study on FBGaccelerometer based on wavelet reestablish technology[J].Chinese Journal of Sensors and Actuators,2009,22(1):67-69.(in Chinese)吴朝霞,闫淑娟,李志全.基于信号重构技术的FBG加速度测量系统研究[J].传感技术学报,2009,22(1):67-69.
[10]Shi Zhenjiang,Li Zhiquan,Zheng Hua,et al.Study on FBGdemodulation system based on real-time wavelet-denoise[J].Piezoel Ectectrics&Acoustooptics,2009,31(3):344-346.(in Chinese)史振江,李志全,郑华,等.基于实时小波消噪的光纤光栅解调系统研究[J].压电与声光,2009,31(3):344-346.
[11]Rao Yunjiang,Wu Min,Ran Zengling,et al.A fiber-opticintrusion alarm system based on quasi-distributed FBGSensors[J].Chinese Journal of Sensors and Actuators,2007,20(5):999-1002.(in Chinese)饶云江,吴敏,冉曾令,等.基于准分布式FBG传感器的光纤入侵报警系统[J].传感技术学报,2007,20(5):999-1002.
[12]Zhong Xiaojiang,Tong Weiguo,Li Baoshu.Wavelet analysisapplication in fiber grating sensing signal processing[C]//Proceedings of 2007 China Conference on Instrumentationmeasure and control technology,2007:613-617.(in Chinese)钟小江,仝卫国,李宝树.小波分析在光纤光栅传感信号处理中的应用[C]//2007中国仪器仪表与测控技术交流大会论文集,2007:613-617.
[13]Sun Yankui.Wavelet Analysis and its Application[M].Beijing:China Machine Press,2005.(in Chinese)孙彦奎.小波分析及其应用[M].北京:机械工业出版社,2005.
[14]Pan Quan,Zhang Lei,Meng Jinli,et al.Wavelet FilteringMethod and its Application[M].Beijing:Tsinghua UniversityPress,2005.(in Chinese)潘泉,张磊,孟晋丽,等.小波滤波方法及应用[M].北京:清华大学出版社,2005.
[15]Yu Kaiping,Zou Jingxiang,Yang Bingyuan.Study onperformance and application of the wavelet function[J].Journal of Harbin Institute of Technology,2000,32(2):36-39.(in Chinese)于开平,邹经湘,杨炳渊.小波函数的性质及其应用研究[J].哈尔滨工业大学学报,2000,32(2):36-39.
[16]Mortazavi S H,Shahrtash S M.Comparing denoisingperformance of DWT,WPT,SWT and DT-CWT for partialdischarge signals[C]//Proceedings of 43rd InternationalConference on UPEC,2008:1-6.
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