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Your search keyword '"Liu, Wenyi"' showing total 122 results
Start Over Author "Liu, Wenyi" Publisher elsevier bv
122 results on '"Liu, Wenyi"'

24. A novel wind turbine health condition monitoring method based on composite variational mode entropy and weighted distribution adaptation

Author

Zhengfeng Wang, Liu Wenyi, Xin Wang, Mengchen Shan, and He Ren

Subjects
060102 archaeology, Renewable Energy, Sustainability and the Environment, Computer science, 020209 energy, Feature vector, Health condition, Mode (statistics), 06 humanities and the arts, 02 engineering and technology, Conditional probability distribution, Turbine, 0202 electrical engineering, electronic engineering, information engineering, 0601 history and archaeology, Marginal distribution, Algorithm, Weighted distribution, Classifier (UML)
Abstract

Aimed at the problem that the complicated working condition of wind turbine and the lack of sufficient target samples, which makes it difficult to conduct effective health condition monitoring (HCM), a novel method based on composite variational mode entropy (CVME) and weighted distribution adaptation (WDA) is proposed in this paper. A series of mode components are first obtained by performing variational mode decomposition (VMD) on the signals under various working conditions. The mode components are analyzed on multi-scale, and then the fuzzy entropy is extracted at different scales. The extracted CVME is input as a feature vector into WDA. The WDA method can effectively reduce the discrepancy of data distribution between the source and target domains by adjusting the weight of the marginal distribution and the conditional distribution, and solve the problem of class imbalance in domains by a weight matrix. The transferability evaluation is used to select the feature sets under auxiliary working conditions with high similarity to the target feature set as the source samples. Finally, the source and target samples are input into the classifier for training and testing. Compared with traditional fault diagnosis methods, experiment shows that the proposed method has higher accuracy in wind turbine fault diagnosis under variable working conditions.

Published
2021
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32. Metastable SrRuO3 phases with lattice-dependent magnetic anisotropy by tailoring interfacial oxygen octahedral coupling

Author

Jiang, Zhongyuan, primary, Zhang, Jian, additional, Song, Dongsheng, additional, Zhu, Mo, additional, Liu, Wenyi, additional, Wu, Qingmei, additional, Ge, Liangbing, additional, Liao, Zhaoliang, additional, Yang, Yuanjun, additional, Huang, Haoliang, additional, Wang, Jianlin, additional, Fu, Zhengping, additional, and Lu, Yalin, additional

Published
2022
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44. Thermodynamic analysis and optimization of liquefied air energy storage system

Author

He Qing, Wang Lijian, Liu Wenyi, Zhou Qian, Lu Chang, and Du Dongmei

Subjects
Exergy, Compressed air energy storage, business.industry, 020209 energy, Mechanical Engineering, Liquefaction, 02 engineering and technology, Building and Construction, Grid, Solar energy, Pollution, Industrial and Manufacturing Engineering, Energy storage, Thermodynamic model, General Energy, 020401 chemical engineering, 0202 electrical engineering, electronic engineering, information engineering, Environmental science, 0204 chemical engineering, Electrical and Electronic Engineering, Process engineering, business, Adiabatic process, Civil and Structural Engineering
Abstract

A large proportion of new energy sources, such as wind and solar energy, are unable to be directly connected to the grid owing to their instability characteristics. To solve this problem, power storage technologies, such as large-scale compressed air energy storage (CAES) technology, have become more important and are playing an increasingly important role. Liquefied air energy storage (LAES) technology is a new type of CAES technology with high power storage density, which can solve the problem of large air storage devices that other CAES systems need to configure. In this study, thermodynamic models of the main components of an LAES system are first established, and the main components of the system are analyzed and optimized. On this basis, the thermodynamic model of an LAES system is established, and the thermodynamic analysis of the system is carried out by means of exergy analysis. The analyzed results show that an LAES system configured with four-stage compression and four-stage expansion has good comprehensive thermodynamic performance. The storage pressure and release pressure of the system are determined to be 15 and 7.1 MPa, respectively, and the air temperature before the pressure-reducing valve of liquefaction is 93 K. Increasing the adiabatic efficiency of main components of the LAES system can reduce their exergy loss, thereby reducing the exergy loss of the whole system and improving its energy storage efficiency.

Published
2019
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