Wind turbine accidents: a data mining study

Asian, Sobhan and Ertek, Gürdal and Haksöz, Çağrı and Pakter, Sena and Ulun, Soner (2017) Wind turbine accidents: a data mining study. IEEE Systems Journal, 11 (3). pp. 1567-1578. ISSN 1932-8184 (Print) 1937-9234 (Online)

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Official URL: http://dx.doi.org/10.1109/JSYST.2016.2565818


While the global production of wind energy is increasing, there exists a significant gap in the academic and practice literature regarding the analysis of wind turbine accidents. This paper presents the results obtained from the analysis of 240 wind turbine accidents from around the world. The main focus of this paper is revealing the associations between several factors and deaths and injuries in wind turbine accidents. Specifically, the associations of death and injuries with the stage of the wind turbine's life cycle (transportation, construction, operation, and maintenance) and the main cause factor categories (human, system/equipment, and nature) were studied. To this end, we conducted a detailed investigation that integrates exploratory and statistical data analysis and data mining methods. This paper presents a multitude of insights regarding the accidents and discusses implications for wind turbine manufacturers, engineering and insurance companies, and government organizations.

Item Type:Article
Uncontrolled Keywords:Accidents; data analysis; data mining; wind energy; wind power generation
Subjects:Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
H Social Sciences > HD Industries. Land use. Labor > HD0061 Risk Management
H Social Sciences > HA Statistics
T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering > T57.6-57.97 Operations research. Systems analysis
T Technology > TS Manufactures > TS0155-194 Production management. Operations management
ID Code:36683
Deposited By:Çağrı Haksöz
Deposited On:27 Nov 2018 10:52
Last Modified:27 Nov 2018 10:52

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