A signal processing method based on empirical mode decomposition (EMD) is proposed,aiming at the serious interference problems that exist in the vibration displacement tests for the vehicle weapon.A new judgement criterion of determining the trend is presented for extracting the trend effectively.According to the symmetrical characteristics of the vibration signal relative to the time axis,the method determines whether the IMF component belongs to the trends by comparing the mean value between each order IMF component and the original signal.Effectiveness of the method is verified by the simulation vibration signal.The measured signals are processed by EMD,and the vibration displacement signal eventually is reconstructed.By comparing with wavelet transform method and a qualitative EMD trend determinant method,the results show that the trend extraction method based on EMD is effective and helpful to evaluate the performance of the weapon objectively.
[1] 陈隽,徐幼麟.经验模分解在信号趋势项提取中的应用[J].振动、测试与诊断,2005,25(2):101-104. Chen Jun,Xu Youlin.Application of EMD to signal trend extraction[J].Journal of Vibration,Measurement & Diagnosis,2005,25(2):101-104.(in Chinese)
[2] 龙源,谢全民,钟明寿,等.爆破震动测试信号预处理分析中趋势项去除方法研究[J].工程力学,2012,29(10):63-68. Long Yuan,Xie Quan-min,Zhong Ming-shou,et al.Research on trend removing methods in preprocessing analysis of blasting vibration monitoring signals[J].Engineering Mechanics,2012,29(10):63-68.(in Chinese)
[3] 侯青剑,王宏力.一种基于EMD的模拟电路故障特征提取方法[J].系统工程与电子技术,2009,31(6):1525-1528. HOU Qing-jian,WANG Hong-li.Method of fault feature extraction for analog circuits based on EMD[J].Journal of Systems Engineering and Electronics,2009,31(6):1525-1528.(in Chinese)
[4] 王静,李天云,王永宏.应用经验模态分解法的tan δ在线监测数据趋势提取[J].高电压技术,2009,35(12):3007-3010. Wang Jing,Li Tian-yun,Wang Yong-hong.Trend extracting of tan δ on-line monitoring using EMD[J].High Voltage Engineering,2009,35(12):3007-3010.(in Chinese)
[5] 曲从善,许化龙,谭营,等.基于新型经验模分解的激光陀螺漂移趋势项提取[J].宇航学报,2009,30(2):597-603. Qu Cong-shan,Xu Hua-long,Tan Ying,et al.Trend extraction from laser gyro drift data based on modified empirical mode decomposition[J].Journal of Astronautics,2009,30(2):597-603.(in Chinese)
[6] 王燕,薛云朝,马铁华.基于EMD和最小二乘法的零漂处理方法研究[J].北京理工大学学报,2015,35(2):118-122. Wang Yan,Xue Yun-zhao,Ma Tie-hua.Research on zero drift processing method using EMD and least-square[J].Transactions of Beijing Institute of Technology,2015,35(2):118-122.(in Chinese)
[7] 雷达,钟诗胜.基于奇异值分解和经验模态分解的航空发动机健康信号降噪[J].吉林大学学报(工学版),2013,43(3):764-770. Lei Da,Zhong Shi-sheng.Aircraft engine health signal denoising based on singular value decomposition and empirical mode decomposition methods[J].Journal of Jilin University(Engineering and Technology Edition),2013,43(3):764-770.(in Chinese)
[8] Jingliang Sun,Huanye Sheng.A hybrid detrending method for fractional Gaussian noise[J].Physica A,2011,390(17):2995-3001.
[9] Y H Dong,J X Zhang.Trend extraction in vibration signal based on EMD[J].Advanced Materials Research,2012,459:377-380.
[10] Jacek Dybala,Radoslaw Zimroz.Rolling bearing diagnosing method based on empirical mode decomposition of machine vibration signal[J].Applied Acoustics,2014,77:195-203.
[11] Zhijing Yang,Bingo Wing-Kuen Ling,Chris Bingham.Trend extraction based on separations of consecutive empirical mode decomposition components in Hilbert marginal spectrum[J].Measurement,2013,46(8):2481-2491.
[12] C Li,M Liang.Extraction of oil debris signature using integral enhanced empirical mode decomposition and correlated reconstruction[J].Meas Sci Technol,2011,22(8):085701.
[13] Azadeh Moghtaderi,Pierre Borgnat,Patrick Flandrin.Trend filtering:Empirical mode decompositions versus and hodrick-prescott[J].Advances in Adaptive Data Analysis,2011,3(1&2):41-61.
[14] Azadeh Moghtaderi,Patrick Flandrin,Pierre Borgnat.Trend filtering via empirical mode decompositions[J].Computational Statistics & Data Analysis,2013,58:114-126.
[15] 李秀坤,李婷婷,马涛.微弱信号强干扰分离方法研究[J].振动与冲击,2011,30(3):225-227. Li Xiu-kun,Li Ting-ting,Ma Tao.The research on strong interference separation of week signal[J].Journal of Vibration and Shock,2011,30(3):225-227.(in Chinese)
[16] Huang N E,Zheng S,Steven R,et al The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]Proc of the Royal Society of London,1998,A(454):903-995.
[17] 王安麟,石世宁,李晓田.挖掘机动态性能试验及其数据的小波处理方法[J].同济大学学报:自然科学版,2014,42(1):115-123. WANG Anlin,SHI Shining,LI Xiaotian.Dynamic performance test and wavelet processing method for non-stationary random data of hydraulic excavator[J].Journal of Tongji University(Natural Science),2014,42(1):115-123.(in Chinese)
[18] 吴志成,王重阳,任爱君.消除信号趋势项时小波基优选方法研究[J].北京理工大学学报,2013,33(8):811-814. WU Zhi-cheng,WANG Chong-yang,REN Ai-jun.Optimal selection of wavelet base functions for eliminating signal trend based on wavelet analysis[J].Transactions of Beijing Institute of Technology,2013,33(8):811-814.(in Chinese)