A novel wind turbine condition monitoring method based on cloud computing. (May 2019)

• Record Type: Journal Article
• Authors: Qian, Peng; Zhang, Dahai; Tian, Xiange; Si, Yulin; Li, Liangbi
• Is Part Of: Renewable energy. Volume 135(2019)
• Page Start: 390
• Page End: 398
• Publication Date: 2019-05
• Subjects: Cloud computing -- Wind turbine -- Data security -- SCADA data -- Hierarchical extreme learning machine -- Compressed sensing; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2018.12.045
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: With the development of condition monitoring technology, the data collected by sensors are voluminous and much faster than before. The cloud computing technology is a good solution for big data processing, it is therefore very suitable to be applied in the condition monitoring of the wind turbine, especially for data-driven model-based condition monitoring methods. In order to solve this problem, a novel wind turbine condition monitoring method based on cloud computing is proposed in this paper. A data-driven model-based condition monitoring (CM) method by using hierarchical extreme learning machine (H-ELM) algorithm is adopted to achieve fault detection of the gearbox in the wind turbine, which has better performance than traditional ELM method. Then, compressed sensing (CS) method is applied to compress the first hidden layer output that will be uploaded to the cloud for further calculation. The proposed method is not only able to detect the faults effectively, but also considering data upload quantity reduction and data security. The case study validates the effectiveness of the proposed method. Consequently, it is effective and can also enhance economic benefit and operating efficiency of the wind farm. Highlights: A novel data-driven model-based wind turbine condition monitoring method based on cloud computing system is proposed. H-ELM method is applied in the condition monitoring of the wind turbine. The proposed method is not only able to reduce data upload quantity to the cloud, but also ensure data security that is beneficial to enhance the data security ability of condition monitoring system based on cloud computing.