Research on Fault Detection Method of Wind Turbine Generator Based on SCADA Data. Issue 3 (March 2020)

• Record Type: Journal Article
• Authors: Wang, Xin; Guo, Pengfei; Liu, Weijiang; Li, Chao
• Is Part Of: IOP conference series. Volume 782:Issue 3(2020)
• Publication Date: 2020-03
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/782/3/032112
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: In this paper, a data driven fault detection model of the generator based on improved nonlinear state estimation (INSET) method was established and the residuals of all the relevant parameters were predicted synchronously. According to the residual distribution characteristics the alarm rules were designed. In case studies, the fault was detected timely and exactly for avoiding serious accident. In addition, compared with other conventional algorithms, the results showed higher prediction accuracy and sensitivity and indicated the feasibility of the method.