Vibration source recognition for pumping station plant house based on IESMD-PSE-EEI

JIANG Qi1, WANG Jiankang2, ZHANG Jianwei1, LIU Xizhu3, ZHAO Yu1, 2

Journal of Vibration and Shock ›› 2025, Vol. 44 ›› Issue (9) : 45-56.

PDF(4985 KB)
PDF(4985 KB)
Journal of Vibration and Shock ›› 2025, Vol. 44 ›› Issue (9) : 45-56.
VIBRATION THEORY AND INTERDISCIPLINARY RESEARCH

Vibration source recognition for pumping station plant house based on IESMD-PSE-EEI

  • JIANG Qi1, WANG Jiankang2, ZHANG Jianwei*1, LIU Xizhu3, ZHAO Yu1,2
Author information +
History +

Abstract

To address the challenge of accurately identifying vibration sources in pumping station buildings with multiple excitation sources and strong background noise interference, an improved Extreme-point Symmetric Mode Decomposition (IESMD)-power spectral entropy-energy entropy increment joint vibration source identification method was proposed. First, IESMD adaptive separation is carried out on the wavelet threshold noise reduction preprocessed signal, noise spectrum theory is introduced to determine the power spectrum entropy and energy entropy increment thresholds, and the Intrinsic Mode Function (IMF) is quantitatively screened to achieve accurate identification of vibration sources. The vibration source was identified based on the measured vibration data of five typical parts of the Dayuzhang Pumping Station powerhouse, and the vibration energy was introduced to calculate the energy proportion of each frequency division. The results showed that: This method can decompose multi-source signals into multiple effective frequency-modulated and amplitude-modulated components. The hydraulic excitation caused by Rotor-stator interaction (RSI) during operation is the dominant vibration source of the plant vibration. Its main frequency of vibration is 33.32Hz. The energy proportion at the pump seat, outlet bend and motor positions is as high as 84.54%, 98.53% and 97.15%, which is the main reason for the vibration of the pumping station plant.

Key words

vibration source identification / IESMD / PSE / energy entropy increment / contribution rate

Cite this article

Download Citations
JIANG Qi1, WANG Jiankang2, ZHANG Jianwei1, LIU Xizhu3, ZHAO Yu1, 2. Vibration source recognition for pumping station plant house based on IESMD-PSE-EEI[J]. Journal of Vibration and Shock, 2025, 44(9): 45-56

References

[1] Kumar K, Saini R P. A review on operation and maintenance of hydropower plants[J]. Sustainable Energy Technologies and Assessments, 2022, 49: 101704.
[2]罗毅,武博翔.基于深度学习LSTM-DBN的水轮机振动故障预测方法[J].振动.测试与诊断,2022,42(06):1233-1238+1251.
LUO Yi,WU Boxiang. Vibration fault prediction method of hydraulic turbine system based on deep learning LSTM-DBN[J].Vibration. Test and Diagnosis,2022,42(06):1233-1238+1251. 
[3] Mohanta R K, Chelliah T R, Allamsetty S, et al. Sources of vibration and their treatment in hydropower stations-A review[J]. Engineering science and Technology, an international journal, 2017, 20(2): 637-648.
[4]吴嵌嵌,张雷克,马震岳,等.水电站机组-厂房结构突增负荷过渡过程振动特性研究[J].振动与冲击,2019,38(18):53-61.
Wu C, Zhang L, Ma Zhenyue, et al. Vibration characteristics of the unit-plant structure of hydropower station under transition load-up process [J].Journal of Vibration and Shock,2019,38(18):53-61.
[5] Heckbert P. Fourier transforms and the fast Fourier transform(FFT) algorithm[J]. Computer Graphics, 1995, 2(1995): 15-463. 
[6]Jwo D J, Wu I H, Chang Y. Windowing design and performance assessment for mitigation of spectrum leakage[C].E3S Web of Conferences. EDP Sciences, 2019, 94: 03001.
[7]Panalaran S, Sulisetyono A. Pre-processing data and window function testing on wave spectrum analysis[C].IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2024, 1298(1): 012037.
[8]Sun B, Wu X, Chen X, et al. Parameter Estimation of Sub-/Super-Synchronous Oscillation Based on Interpolated All-Phase Fast Fourier Transform with Optimized Window Function[J]. Journal of Modern Power Systems and Clean Energy, 2023.
[9]陈鹏,赵少美,陈钦,等.频谱泄漏校正的多频实信号频率估计算法[J].振动与冲击,2021,40(15):107-113.
Chen Peng, Zhao Shaomei, Chen Qin, et al. Frequency estimation algorithm for multi-frequency real signals based on spectrum leakage correction[J].Journal of Vibration and Shock,2021,40(15):107-113. 
[10]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 Siqi, Tan Zhiyin, Yang Siguo, et al. An improved Fourier decomposition method and its application in fault diagnosis of rolling bearings[J].Vibration and Shock,2023,42(12):178-186.
[11] Huang N E, Shen Z, Long S R, et al. The empirical mode
decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London. Series A: mathematical, physical and engineering sciences, 1998, 454(1971): 903-995. 
[12]董霄峰,练继建,王海军.运行状态下海上风机结构振源特性研究[J].振动与冲击,2017,36(17):21-28.
Dong Xiaofeng, Lian Jijian, Wang Haijun. Vibration source feature of offshore wind turbine power structures under operational conditions[J].Vibration and Shock,2017,36(17):21-28. 
[13]Fu, Qiang, et al. Fault feature selection and diagnosis of rolling bearings based on EEMD and optimized Elman_AdaBoost algorithm[J]. IEEE Sensors Journal, 2018, 18(12): 5024-5034.
[14]李国英,王诗彬,陈雪峰.基于自适应EEMD的风电机组联轴器松动故障诊断[J].振动.测试与诊断,2022,42(02):292-298+407-408.
Li Guoying, Wang Shibin, Chen Xuefeng. Looseness fault iagnosis on coupling of wind turbines based adaptive EEMD[J].Vibration. Test and Diagnosis,2022,42(02):292-298+407-408. 
[15] Liu F, Gao J, Liu H. The feature extraction and diagnosis of rolling bearing based on CEEMD and LDWPSO-PNN[J]. Ieee Access, 2020, 8: 19810-19819. 
[16] 宿文才,张树团,刘涛,等.混合插值的ESMD在电机轴承故障特征提取的应用[J].振动与冲击,2020,39(04):266-272.
Su Wencai, Zhang Shutuan, Liu Tao, et al. Application of  hybrid interpolated ESMD in motor bearing fault feature extraction[J].Vibration and Shock,2020,39(04):266-272.
[17]李双江,辛景舟,蒋黎明,等.基于TVFEMD-IMF能量熵增量的桥梁监测数据降噪方法[J].振动.测试与诊断,2024,44(01):178-185+206.
Li Shuangjiang, Xin Jingzhou, Jiang Liming, et al. Bridge monitoring data de-noise method based on TVFEMD-IMF energy entropy increment[J].Vibration. Testing and Diagnosis,2024,44(01):178-185+206.
[18]吴嵌嵌,张雷克,马震岳.水电站水机电-结构系统动力耦联模型研究及数值模拟[J].振动与冲击,2017,36(16):1-10.
WU Qianqian,ZHANG Leike,MA Zhenyue. Model analysis and numerical simulation of a dynamic coupling hydraulic-mechanical-electric-structural system for a hydropower station[J].Vibration and Shock,2017,36(16):1-10.
[19]刘聪.某可逆式机组厂房振动问题的原因分析及处理方案[J].水电能源科学,2020,38(11):156-159.
Liu Cong. Analysis and solution of vibration problem for a reversible unit powerhouse[J].Hydropower Energy Science,2020,38(11):156-159.
[20]张建伟,侯鸽,暴振磊,等.基于CEEMDAN与SVD的泄流结构振动信号降噪方法[J].振动与冲击,2017,36(22):138-143.
 
Zhang Jianwei, Hou Ge, Feng Zhenlei, et al. A signal de-noising method for vibration signals from flood discharge structures based on CEEMDAN and SVD[J]. Vibration and Shock,2017,36(22):138-143. 
[21]Mei L, Li S, Zhang C, et al. Adaptive signal enhancement based on improved VMD-SVD for leak location in water-supply pipeline[J]. IEEE Sensors Journal, 2021, 21(21): 24601-24612.
[22]Wang S, Zhang L, Yin G. Vibration prediction and evaluation system of the pumping station based on ARIMA–ANFIS–WOA hybrid model and DS evidence theory[J]. Water, 2023, 15(14): 2656.
[23]张建伟,江琦,王涛.基于原型观测的梯级泵站管道振源特性分析[J].农业工程学报,2017,33(01):77-83.
Zhang Jianwei, Jiang Qi, Wang Tao. Analysis of Vibration 
Characteristics of pipeline of trapezoid pumping station based on prototype observation[J]. Transactions  of the  Chinese  Society   of Agricultural Engineering (Transactions of the CSAE),2017,33(01):77-83.
[24]朱国俊,李康,冯建军,等.空化对轴流式水轮机尾水管压力脉动和转轮振动的影响[J].农业工程学报,2021,37(11):40-49.
Zhu Guojun, Li Kang, Feng Jianjun, et al. Effect of cavitation on pressure fluctuation of draft turbe and runner vibration in a Kaplan turbine[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2021,37(11):40-49.
PDF(4985 KB)

127

Accesses

0

Citation

Detail

Sections
Recommended

/