TY - JOUR
T1 - Improving Hilbert–Huang transform for energy-correlation fluctuation in hydraulic engineering
AU - Lu, Shibao
AU - Zhang, Xiaoling
AU - Shang, Yizi
AU - Li, Wei
AU - Skitmore, Martin
AU - Jiang, Shuli
AU - Xue, Yangang
N1 - Funding Information:
This research was funded by the National Natural Science Foundation of China (Grant Nos 51579248 , 51379219 and 51769012 ), Zhejiang Province Funds for Distinguished Young Scientists (Grant No. LR15E090002 ), and Gansu Province Natural Science Foundation of China (Grant No. 1506RJZA059 ). The work described in this paper was also substantially supported by the grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 11271716 and CityU 21209715 ) This paper has also been partially supported by CityU New research initiatives/Infrastructure support from Central (APRC) (Project No: 9610386 ), CityU strategic research grant (Project No: 7004950 and 7005142 ).
Publisher Copyright:
© 2018 Elsevier Ltd
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Intense vibrations in hydraulic turbine generator unit draft tubes lead to a run-out of the unit shafting and threaten its safe and stable operation. Correct maintenance is therefore important for the safe operation of such units. This study involves assessing the condition of the turbine generator unit by extracting the feature information of its vibration signals. Based on previous research, we present an enhanced Hilbert–Huang transform (HHT) method with an energy-correlation fluctuation criterion to extract feature information and effectively verify the method with simulated signals. An inspection application based on the signal from a vortex strip in the draft tube of a prototype turbine under suboptimal operating conditions indicates that this method is more effective than the traditional one, with a better component identification capability and better suited to the analysis of the complex and dynamic feature information of hydro turbines.
AB - Intense vibrations in hydraulic turbine generator unit draft tubes lead to a run-out of the unit shafting and threaten its safe and stable operation. Correct maintenance is therefore important for the safe operation of such units. This study involves assessing the condition of the turbine generator unit by extracting the feature information of its vibration signals. Based on previous research, we present an enhanced Hilbert–Huang transform (HHT) method with an energy-correlation fluctuation criterion to extract feature information and effectively verify the method with simulated signals. An inspection application based on the signal from a vortex strip in the draft tube of a prototype turbine under suboptimal operating conditions indicates that this method is more effective than the traditional one, with a better component identification capability and better suited to the analysis of the complex and dynamic feature information of hydro turbines.
UR - http://www.scopus.com/inward/record.url?scp=85054657550&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2018.08.088
DO - 10.1016/j.energy.2018.08.088
M3 - Article
AN - SCOPUS:85054657550
SN - 0360-5442
VL - 164
SP - 1341
EP - 1350
JO - Energy
JF - Energy
ER -