Fault source location of wind turbine based on heterogeneous nodes complex network. (August 2021)

• Record Type: Journal Article
• Authors: Zhang, Kai; Tang, Baoping; Deng, Lei; Yu, Xiaoxia; Wei, Jing
• Is Part Of: Engineering applications of artificial intelligence. Volume 103(2021)
• Publication Date: 2021-08
• Subjects: Wind turbines -- SCADA system -- Fault location -- Complex networks -- Heterogeneous networks; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2021.104300
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Previous studies regarding wind turbine health management based on wind turbine supervisory control and data acquisition (SCADA) signals focused on detecting incipient failure. In this case, most current SCADA alarm systems adopt a single or multi-signal threshold trigger alarm. When a wind turbine is operating in a large wind farm, it is catastrophic for maintenance personnel lied in the reason that the current SCADA system may trigger many alarms in the short term. Therefore, the fault source must be identified and the candidate fault sources sorted. This study aims to obtain the fault location of wind turbines based on a complex network, which does not require a large number of historical monitoring signals. A directed graph of the wind turbine and fault location theoretical framework is established; an improvement is achieved based on the heterogeneity of nodes abstracted by components of a wind turbine and variables of SCADA. The proposed fault location method based on heterogeneous nodes complex networks (HNCN) is improved based on degree-based mean-field theory and is verified by spreading simulated data and four SCADA alarm cases at a wind farm located in Liaoning, China.