Studying and application of improved signal blind source separation based on WOA-VMD

WANG Haijun1,2, HAO Zhihao1,2, LIU Tong3, HU Hang3, LIANG Chao1,2

Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (9) : 222-229.

PDF(1271 KB)
PDF(1271 KB)
Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (9) : 222-229.

Studying and application of improved signal blind source separation based on WOA-VMD

  • WANG Haijun1,2, HAO Zhihao1,2, LIU Tong3, HU Hang3, LIANG Chao1,2
Author information +
History +

Abstract

It is of great guiding significance to identify the vibration sources of the hydropower station accurately and effectively for the long-term safe and stable operation of the hydropower station. Blind source separation (BSS) is an effective method for signal decomposition and vibration source identification. In order to realize blind source separation of vibration signals under complex environment of hydropower station, an improved blind source separation model based on WOA-VMD was described. Firstly, WOA-VMD and correlation method was used to de-noise the observed signals to ensure the accuracy of blind source separation results. Then, the covariance matrix of de-noised signals was solved and the number of sources was estimated with the dominant eigenvalue method.  Finally, the signals were preprocessed by centralization and whitening, and then JADE method was used to solve the separation matrix to achieve blind source separation of vibration signals. The simulation results show that compared with the traditional BSS model, the correlation coefficient between the separation signal and the source signal is improved by 9.1%, 7.1% and 8.3% respectively, and the main frequency error of the separation signal is also reduced. The method was applied to the vibration engineering of hydropower station and better separation effect was achieved.

Key words

hydropower plant / blind source separation (BSS) / whale optimization algorithm (WOA) / source number estimation / joint approximate diagonalization of eigen-matrix (JADE)

Cite this article

Download Citations
WANG Haijun1,2, HAO Zhihao1,2, LIU Tong3, HU Hang3, LIANG Chao1,2. Studying and application of improved signal blind source separation based on WOA-VMD[J]. Journal of Vibration and Shock, 2023, 42(9): 222-229

References

[1] 尚银磊,李德玉,欧阳金惠.大型水电站厂房振动问题研究综述[J].中国水利水电科学研究院学报,2016,14(1):48-52+59.
SHANG Yin-lei, Li De-yu, OUYANG Jin-hui. Review on powerhouse self-oscillation character- ristics of a large-scale power station[J].Journal of China Institute of Water Resources and Hydropower Research. 2016,14(1):48-52+59.
[2] 练继建, 王海军, 秦亮. 水电站厂房结构研究[M]. 北京: 中国水利水电出版社, 2007.
[3] 杨继松. 水电站机组与厂房振源分离及识别研究[D].天津:天津大学,2018.
YANG Ji-song. Research on vibration isolation and identification of unit and powerhouse in hydropower station[D].Tianjin: Tianjin University, 2018.
[4] 张磊,李彬,杨自春,等.融合盲源分离的船舶耦合振源传递路径分析技术研究[J].振动与冲击,2020,39(17):150-156.
ZHANG Lei, LI Bin, YANG Zi-chun, et al. TPA technique for ship coupled vibration sources based on BSS[J].Journal of Vibration and Shock, 2020,39(17):150-156.
[5] 张晨阳,张亚,李世中.基于变分模态分解的侵彻过载信号盲分离[J].振动与冲击, 2022,41(5): 280-286.
ZHANG Chen-yang, ZHANG Ya, LI Shi-zhong. Blind separation of penetration overload signals based on VMD[J]. Journal of Vibration and Shock, 2022,41(5): 280-286.
[6] 刘子腾,徐永海,陶顺.基于SHIBSS方法和数据优选的系统侧谐波阻抗估算方法[J].电力自动化设备,2021,41(2):193-199.
LIU Zi-teng, XU Yong-hai, TAO Shun. Estimation method of harmonic impedance on system side based on SHIBSS method and data optimization[J]. Electric Power Automation Equipment, 2021,41(2): 193-199.
[7] Christos S, Vasiliki-Despoina K, Manousos A. K. Which BSS method separates better the EEG Signals? A comparison of five different algorithms[J]. Biomedical Signal Processing and Control,2022, 72A(10):103+292.
[8] 夏奎,李炜,邱意敏,等.基于改进型象群优化算法的BSS方法[J].电子测量与仪器学报, 2021,35(10): 153-160.
XIA Kui, Li Wei, QIU Yi-min, et al. BSS method based on improved elephant herding optimization algorithm[J]. Journal of Electronic Measurement and Instrument, 2021,35(10): 153-160.
[9] 骆伟林,金宏斌,李浩,等.基于混沌自适应烟花算法的雷达信号盲源分离[J].系统工程与电子技术,2020,42(11):2497-2505.
LUO Wei-lin, JIN Hong-bin, LI Hao, et al. Blind source separation of radar signals based on chaotic adaptive firework algorithm[J]. Journal of Systems Engineering and Electronics, 2020,42(11):2497 -2505.
[10] 毋文峰,陈小虎,苏勋家.基于经验模式分解的单通道机械信号盲分离[J].机械工程学报,2011,47(4):12-16.
WU Wen-feng, CHEN Xiao-hu, SU Xun-jia. Blind Source Separation of Single-channel Mechanical Signal Based on Empirical Mode Decomposition[J]. Journal of Mechanical Engineering,2011,47(4):
12-16.
[11] 肖瑛,马艺伟,刘学.遥测振动信号单通道盲源分离自适应滤波幅度校正方法[J].振动与冲击,2021,40(23):127-133+158.
XIAO Ying, MA Yi-wei, LIU Xue. Single channel blind source separation adaptive filtering amplitude correction method for telemetry vibration signals[J]. Journal of Vibration and Shock, 2021,40(23): 127-133+158.
[12] 余建英,何旭宏.数据统计分析与SPSS应用[M].北京:人民邮电出版社,2003.
[13] 张萍,张文海,赵新贺,等.WOA-VMD算法在轴承故障诊断中的应用[J].噪声与振动控制,2021,41(4):86-93+275.
ZHANG Ping, ZHANG Wen-hai, ZHAO Xin-he, et al. Application of WOA- VMD Algorithm in Bearing Fault Diagnosis[J]. Noise and Vibration Control, 2021,41(4): 86-93 +275.
[14] 刘立邦,杨颂,王志坚,等.基于改进WOA-LSTM的焦炭质量预测[J].化工学报,2022,73(3):1291-1299.
LIU Li-bang, YANG Song, WANG Zhi-jian, et al. Prediction of coke quality based on improved WOA-LSTM[J]. CIESC Journal, 2022,73(3): 1291-1299.
[15] 王海军,杨继松,郭飞飞.水电站厂房多源振动信号盲分离研究[J].水力发电学报,2018,37(7):113-120.
WANG Hai-jun, YANG Ji-song, GUO Fei-fei. Blind separation of multi-source vibration signals in hydropower houses[J]. Journal of Hydroelectric Engineering,2018,37(7):113-120.
[16] 秦文琪,尧辉明.基于JADE算法的钢轨接头病害故障检测研究[J].计算机测量与控制,2019,27(4):22-25.
QIN Wen-qi, YAO Hui-ming. Application of JADE algorithm in track rail joint irregularity detection[J]. Computer Measurement and Control,2019,27(4): 22-25.
[17] 席剑辉,崔健驰,蒋丽英.基于JADE-ICA的滚动轴承多故障信号盲源分离[J].振动与冲击, 2017,36(5):231-237.
XI Jian-hui, CUI Jian-chi, JIANG Li-ying. JADE- ICA-based blind source separation of multi-fault signals of rolling bearings[J]. Journal of Vibration and Shock, 2017,36(5):231-237.
[18] 王海军,许松,陆建宏,等.基于AVMD和BSA-KELM的水电站厂房结构振动预测研究[J].水资源与水工程学报,2020,31(6):168-173+179.
WANG Hai-jun1, XU Song, LU Jian-hong, et al. Structural vibration prediction of hydropower plant buildings based on AVMD and BSA-KELM[J]. Journal of Water Resources and Water Engineering, 2020,31(6):168-173+179.
PDF(1271 KB)

Accesses

Citation

Detail

Sections
Recommended

/