张梦,潘鑫,高金吉,卢加乔,马威龙
ZHANG Meng,PAN Xin,GAO Jinji,LU Jiaqiao,MA Weilong

• 1:北京化工大学发动机健康监控及网络化教育部重点实验室
• 2:北京化工大学化工安全教育部工程中心

摘要(Abstract)：

针对提取频率相近信号特征的经典算法Zoom-FFT(ZFFT)在分离差频1 Hz以内的微速差信号时，需要足够的数据长度才能达到良好的信号分离效果的问题，为了在不增加数据长度的基础上提高信号频率分辨率，在ZFFT算法的基础上产生了ZFFT+FT算法。通过LabVIEW软件仿真试验研究了该算法对频率差1 Hz和0.5 Hz的微速差信号提取精度，并与chirp Z transform(CZT)算法、ZFFT算法以及FFT算法的提取精度作了对比，通过提取结果的相对误差及方差来衡量提取精度。在同轴微速差双转子试验台进行现场试验，利用FFT对微速差信号28 s数据集的提取结果与CZT，ZFFT及ZFFT+FT算法对4 s数据集的提取结果作对比，ZFFT+FT与FFT算法的提取结果最大相差0.56 μm，验证了ZFFT+FT的实时性和精确性。结果表明，ZFFT+FT算法能够实时精准提取频率差1 Hz以内的微速差信号。研究结果可为旋转机械微速差信号的提取提供参考。
The separation of micro-speed difference signals within differential frequency 1 Hz is a challenge in the field of dual-rotor vibration feature extraction.Zoom-FFT(ZFFT) is a classical algorithm for extracting the features of signals with similar frequencies.However，it needs sufficient data length to achieve a good signal separation effect.In order to improve the signal frequency resolution without increasing the data length，the ZFFT+FT algorithm is generated on the basis of ZFFT algorithm.The extraction accuracy of the algorithm for micro-speed difference signals with frequency difference of 1 Hz and 0.5 Hz was studied through LabVIEW software simulation experiments，and compared with that of chirp Z transform(CZT)，ZFFT and FFT algorithms.The extraction accuracy was measured by the relative error and variance of the extraction results.Field experiments were carried out in the coaxial micro-speed difference dual-rotor test stand，and the extraction results of 28s dataset of micro-speed difference signal by FFT were compared with those of 4s dataset extracted by CZT，ZFFT and ZFFT+FT algorithms.The maximum error between ZFFT+FT algorithm and FFT algorithm is 0.56 μm，which verifies the real-time performance and accuracy of ZFFT+FT.The results indicate that the ZFFT+FT algorithm can accurately extract the micro-speed difference signals within frequency difference of 1 Hz in real time.The research results can provide reference for the extraction of micro-speed difference signals in rotating machinery.

关键词(KeyWords)： 微速差;双转子;Zoom-FFT;ZFFT+FT
micro-speed difference;dual-rotor;Zoom-FFT;ZFFT+FT

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金面上项目(51875031);; 北京市自然科学基金面上项目(3212010)

作者(Author): 张梦,潘鑫,高金吉,卢加乔,马威龙
ZHANG Meng,PAN Xin,GAO Jinji,LU Jiaqiao,MA Weilong

参考文献(References)：

• [1]ZHANG W X，LIU X J，CHEN X W，et al.A NSZT method for frequency estimation and anti-noise performance analysis[J].Chinese Journal of Electronics，2018，27(3)：648-657.
• [2]SUN Y X，LIU C，SUN L J，et al.Chatter detection with beat effect based on beat frequency estimation[J].IEEE Transactions on Automation Science and Engineering，2020，18(4)：2166-2174.
• [3]梅海青，冯毅.基于振动信号频谱分析的回转机械故障诊断方法[J].流体机械，2003，31(1)：29-31.MEI H Q，FENG Y.Mechanical failure diagnosing method basing on vibration signal[J].Fluid Machinery，2003，31(1)：29-31.
• [4]贾朱植，杨理践，祝洪宇，等.基于高分辨率谱估计的早期转子断条故障诊断[J].仪器仪表学报，2017，38(2)：279-287.JIA Z Z，YANG L J，ZHU H Y，et al.High-resolution spectral analysis for incipient broken rotor bar diagnosis[J].Chinese Journal of Scientific Instrument，2017，38(2)：279-287.
• [5]黄斯琪，谭志银，杨思国，等.改进的傅里叶分解方法及其在滚动轴承故障诊断中的应用[J].振动与冲击，2023，42(12)：178-186.HUANG S Q，TAN Z Y，YANG S G，et al.An improved Fourier decomposition method and its application in fault diagnosis of rolling bearings[J].Journal of Vibration and Shock，2023，42(12)：178-186.
• [6]ZHANG Y，ZHONG L，LI J，et al.Unbalanced vibration suppression of a rotor with rotating-frequency faults using signal purification[J].Mechanical Systems and Signal Processing，2023，190：110153.
• [7]颜炳良，金辉，黄冲，等.常规岛汽机旁路调节阀流激共振研究[J].流体机械，2023，51(9)：27-33.YAN B L，JIN H，HUANG C，et al.Research on flow-induced resonance of conventional island steam turbine bypass control value[J].Fluid Machinery，2023，51(9)：27-33.
• [8]齐光峰，孙东，郑炜博，等.基于频谱分析的油田注水柱塞泵故障诊断[J].流体机械，2023，51(3)：84-90.QI G F，SUN D，ZHENG W B，et al.Fault diagnosis of oil field water injection plunger pump based on spectrum analysis[J].Fluid Machinery，2023，51(3)：84-90.
• [9]施瑶，王雅静，梅宇，等.基于WPT和参数优化的VMD谐波检测方法[J].电测与仪表，2022，59(8)：166-171.SHI Y，WANG Y J，MEI Y，et al.VMD harmonic detection method based on WPT and parameter optimization[J].Electrical Measurement & Instrumentation，2022，59(8)：166-171.
• [10]CHEN D J，FAN J W，ZHANG F H.Extraction the unbalance features of spindle system using wavelet transform and power spectral density[J].Measurement，2013，46(3)：1279-1290.
• [11]赵学智，叶邦彦，陈统坚.频率添加奇异值分解算法及其在故障特征提取中的应用[J].机械工程学报，2021，57(10)：10-20.ZHAO X Z，YE B Y，CHEN T J.Frequency adding singular value decomposition algorithm and its application in fault feature extraction[J].Journal of Mechanical Engineering，2021，57(10)：10-20.
• [12]邢婷婷，关阳，刘子涵，等.基于变分模态分解和奇异值分解的频率相近信号分离方法[J].计量学报，2020，41(11)：1404-1409.XING T T，GUAN Y，LIU Z H，et al.Similar frequency signal separation based on VMD and singular value decomposition[J].Acta Metrologica Sinica，2020，41(11)：1404-1409.
• [13]李志国，林彬，高鹏涛，等.基于SVD-ITD和支持向量机的潜水磨碎泵故障诊断[J].流体机械，2021，49(10)：97-104.LI Z G，LIN B，GAO P T，et al.Fault diagnosis of submersible grinding pump based on SVD-ITD and support vector machine[J].Fluid Machinery，2021，49(10)：97-104.
• [14]ZHENG M，SHEN F.Performance comparison of dense frequency identifications for empirical mode decomposition[J].Advanced Materials Research，2011，378-379：266-269.
• [15]齐伟，赵鼎鼎，蔡萍.基于MUSIC算法的动不平衡信号提取方法研究[J].仪器仪表学报，2012，33(6)：1240-1246.QI W，ZHAO D D，CAI P.Research on extraction of unbalanced vibration signal based on MUSIC[J].Chinese Journal of Scientific Instrument，2012，33(6)：1240-1246.
• [16]肖幸鑫，宋礼威，张翊勋，等.基于CEEMD与SVM的离心泵转子不对中故障诊断方法研究[J].流体机械，2022，50(7)：85-92.XIAO X X，SONG L W，ZHANG Y X，et al.Research on fault diagnosis method of centrifugal pump rotor misalignment based on CEEMD and SVM[J].Fluid Machinery，2022，50(7)：85-92.
• [17]YU P C，WANG C，HOU L，et al.Dynamic characteristics of an aeroengine dual-rotor system with inter-shaft rub-impact[J].Mechanical Systems and Signal Processing，2022，166：108475.
• [18]刘利利，袁晨星，张楚，等.动态超压对反拱开缝型爆破片爆破性能的影响[J].压力容器，2023，40(1)：38-45.LIU L L，YUAN C X，ZHANG C，et al.Influence of dynamic overpressure on bursting performance of reverse arched slotted rupture disc[J].Pressure Vessel Technology，2023，40(1)：38-45.
• [19]李宇佳，王进君，王志强，等.基于复合信号的挖掘机工作状态智能识别方法[J].机电工程，2022，38(11)：20-29.LI Y J，WANG J J，WANG Z Q，et al.Intelligent identification method of excavator working state based on compound signal[J].Electromechanical Engineering，2022，38(11)：20-29.
• [20]TIAN J，WANG S G，ZHOU J，et al.Fault diagnosis of intershaft bearing using variational mode decomposition with TAGA optimization[J].Shock and Vibration，2021(1)：1-7.
• [21]LI J M，CHENG X，LI Q，et al.Adaptive energy-constrained variational mode decomposition based on spectrum segmentation and its application in fault detection of rolling bearing[J].Signal Processing，2021，183：108025.
• [22]MIAO Y H，ZHAO M，LIN J.Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition[J].ISA Transactions，2019，84：82-95.