针对叶尖定时信号因严重的非均匀采样和欠采样导致的谱分析难题,提出了基于扩展离散傅里叶变换(EDFT)的分析方法。不同于传统的傅里叶变换,EDFT是以傅里叶积分变换为目标,在扩展的频率范围内通过构造和优化变换基函数替代传统FFT变换中的指数基来实现非均匀和欠采样信号的谱分析,在分析中利用原始数据迭代和近似拟合保证了分析精度。该方法突破了奈奎斯特采样定理的限制,扩大了分析频率范围,分析谱线数也不再受限于采样点数,提高了频率分辨率。为了验证所提方法的可行性和可靠性,采用所构建的叶尖定时系统采样数学模型生成数据和试验台测试数据分别进行了方法应用分析,结果显示无论是仿真数据或试验数据,当传感器数量大于等于3时,基于所提方法能够准确分析得到叶片振动的谱信号,表明所提方法可以有效地解决非均匀欠采样叶尖定时信号的谱分析的难题,且具有良好的抗干扰性。
Abstract
In order to solve the problem that it is difficult to analyze the blade vibration frequency caused by the serious nonuniform sampling and under-sampling of the tip timing signal, an analysis method of the tip timing signal based on the extended discrete Fourier transform (EDFT) is proposed. Different from the traditional Fourier transform, the EDFT takes the Fourier integral transform as the goal and uses the optimized transform basis function to replace the traditional DFT transform in the extended frequency range. The method is not restricted by Nyquist sampling theorem, which expands the frequency range and improves the frequency resolution. In order to verify the feasibility and reliability of the proposed method, the data generated by the mathematical model of sampling process and the test data are analyzed respectively. The results show that when the number of sensors is more than or equal to 3, the accurate blade vibration spectrum signal can be obtained based on the simulation data or test data, which shows that the proposed method can effectively solve the problem of spectrum analysis of nonuniform under-sampling tip timing signal, and has good anti-interference performance.
关键词
扩展傅里叶变换 /
非均匀采样 /
欠采样 /
叶尖定时
{{custom_keyword}} /
Key words
Extended DFT /
nonuniform sampling /
under-sampling /
blade tip-timing
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 张俊红,杨硕,刘海,等. 裂纹参数对航空发动机叶片频率转向特性影响研究[J]. 振动与冲击,2014, 33(20): 7-11.
ZHANG Jun-hong,YANG Shuo,LIU Hai,et al. Influence of crack parameters on frequency veering characteristic of aeroengine blade[J]. Journal of Vibration and Shock, 2014, 33(20): 7-11.
[2] 张继旺,张来斌,段礼祥,等. 基于EEMD的含噪叶尖定时脉冲信号提取方法[J]. 油气储运,2019, 38(06): 685-691.
ZHANG Jiwang,ZHANG Laibin,Duan Lixiang,et al. An EEMD based noised blade tip-timing pulse signal extracting method[J]. Oil & Gas Storage and Transportation, 2019, 38(06): 685-691.
[3] 郭旭民,孙祺,马辉,等. 旋转叶片-柔性机匣碰摩振动响应分析[J]. 振动与冲击,2019, 38(05): 162-168.
GUO Xumin,SUN Qi,MA Hui,et al. Rub vibration responses of rotating blade and flexible casing[J]. Journal of Vibration and Shock, 2019, 38(05): 162-168.
[4] 樊俊铃. 基于权函数法的应力强度因子计算和断裂评估[J]. 航空动力学报,2018, 33(08): 1886-1895.
Fan Junling. Stress intensity factor calculation and fracture evaluation based on weight function method[J]. Journal of Aerospace Power,2018, 33(08): 1886-1895.
[5] Romuald Rzadkowski,Leszek Kubitz,Michał Maziarz,et al. Tip-Timing Measurements and Numerical Analysis of Last-Stage Steam Turbine Mistuned Bladed Disc During Run-Down[J]. Journal of Vibration Engineering & Technologies, 2020, 8(3): 409-415.
[6] Chengwei Fan,Yadong Wu,Pete Russhard,et al. An Improved Blade Tip-timing Method for Vibration Measurement of Rotating Blades During Transient Operating Conditions[J]. Journal of Vibration Engineering & Technologies, 2020(prepublish): 1-10.
[7] 王维民,张旭龙,陈康,等. 大型轴流压气机叶片无键相振动监测与故障预警方法[J]. 振动与冲击, 2019, 38(23): 54-61+118.
WANG Weimin,ZHANG Xulong,CHEN Kang,et al. Vibration monitoring and fault pre-warning method for large axial compressor blades without OPR sensor[J]. Journal of Vibration Engineering & Technologies, 2019, 38(23): 54-61+118.
[8] Saeed Bornassi,Mohammad Ghalandari,Saeed Faghfoor Maghrebi. Blade synchronous vibration measurements of a new upgraded heavy duty gas turbine MGT-70(3) by using tip-timing method[J]. Mechanics Research Communications, 2020, 104.
[9] 李孟麟,段发阶,欧阳涛,等. 基于叶尖定时的旋转机械叶片振动频率辨识ESPRIT方法[J]. 振动与冲击, 2010, 29(12): 18-22.
LI Menglin,DUAN Fajie,OUYANG Tao,et al. ESPRIT method for blade vibration frequency identification in rotating machinery based on blade tip-timing measurement[J]. Journal of Vibration and Shock, 2010, 29(12): 18-22.
[10] 贺长波,李宏坤,赵新维,等. 基于总体最小二乘准则旋转不变子空间法的叶尖定时欠采样信号分析[J]. 机械工程学报, 2019, 55(19): 103-111.
HE Changbo,LI Hongkun,ZHAO Xinwei,et al. Analysis Method for Under-sampled Blade Tip-timing Signal Based on the Rotational Invariance Technique with Total Least Squares Principle[J]. Journal of Mechanical Engineering, 2019, 55(19): 103-111.
[11] ZHENG Hu, JUN Lin, Zhong-Sheng Chen, et al. A non-uniformly under-sampled blade tip-timing signal reconstruction method for blade vibration monitoring[J]. Sensors, 2015, 15: 2419-2437.
[12] 郭浩天,段发阶,汪猛. 基于叶尖定时单参数法的叶片共振倍频数辨识[J]. 天津大学学报(自然科学与工程技术版),2016, 49(09): 951-955.
GUO Haotian, DUAN Fajie, WANG Meng. Engine Order Identification Based on Blade Tip-Timing Single Parameter Method[J]. Journal of Tianjin University(Science and Technology), 2016, 49(09): 951-955.
[13] Jun Lin, Zheng Hu, Zhong-Sheng Chen, et al. Sparse reconstruction of blade tip-timing signals for multi-mode blade vibration monitoring[J]. Mechanical Systems and Signal Processing, 2016, 81:250-258.
[14] 张效溥,田杰,孙宗翰,等. 基于任意传感器排布的叶尖定时信号压缩感知辨识方法[J]. 航空动力学报,2020,35(01):41-51.
ZHANG Xiaobo, TIAN Jie, SUN Zonghan, et al. Compressive sensing identification method of blade tip timing signals based on arbitrary sensor arrangement[J]. Journal of Aerospace Power, 2020, 35(01): 41-51.
[15] Antoine Bouchain, José Picheral, Elisabeth Lahalle, et al. Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm[J]. Mechanical Systems and Signal Processing, 2019, 130: 108-121.
[16] 范博楠,张玉波,王海斗,等. 基于叶尖定时技术的叶轮叶片动态监测研究现状[J]. 振动与冲击,2016, 35(05): 96-102.
FAN Bo-nan, ZHANG Yu-bo, WANG Hai-dou, et al. Research status for dynamic monitoring impellers' of blades based on blade tip-timing[J]. Journal of Vibration and Shock, 2016, 35(05): 96-102.
[17] V.Liepins, A spectral estimation method of nonuniformly sampled band-limited signals. Automatic Control and Computer Sciences, 1994, 28(2): 66-77.
[18] 张继旺,张来斌,段礼祥,等. 基于多键相的变转速下旋转叶片振动监测方法[J]. 油气储运,2019,38(02): 185-190+213.
ZHANG Jiwang, ZHANG Laibin, Duan Lixiang, et al. A multi-phase based vibration monitoring method for rotating blade at variable speed[J]. Oil & Gas Storage and Transportation, 2019, 38(02): 185-190+213.
[19] 王维民,任三群,陈立芳,等. 基于键相插值法的叶片振动测量研究[J]. 振动.测试与诊断,2017,37(02): 361-365+409.
WANG Weimin, REN Sanqun, CHEN Lifang, et al. The Blade Vibration Measurement Research Based on the Key Phase Interpolation Method[J]. Journal of Vibration,Measurement & Diagnosis, 2017, 37(02): 361-365+409.
[20] 时辰. 基于虚拟仪器的叶尖定时采集系统的研究[D]. 南京:南京航空航天大学, 2016.
SHI Chen. Study on Virtual Instrument for Blade Tip-timing Acquiring System[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2016.
[21] 张继旺. 基于叶尖定时的旋转叶片安全监测及智能诊断方法研究[D]. 北京: 中国石油大学(北京), 2018.
ZHANG Jiwang. Research on Non-contact Safety Monitoring and Intelligent Diagnosis of High-speed Blades Based on Blade Tip-timing Method [D]. Beijing: China University of Petroleum, Beijing, 2018.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}