Research on Fault Diagnosis of Wind Power Generator Blade Based on SC-SMOTE and kNN
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초록
Because SCADA monitoring data of wind turbines are large and fast changing, the unbalanced proportion of data in various working conditions makes it difficult to process fault feature data. The existing methods mainly introduce new and nonrepeating instances by interpolating adjacent minority samples. In order to overcomethe shortcomings of these methods which does not consider boundary conditions in balancing data, an improved oversampling balancing algorithm SCSMOTE (safe circle synthetic minority oversampling technology) is proposed to optimize data sets. Then, for the balanced data sets, a fault diagnosis method based on improvedknearest neighbors (kNN) classification for wind turbine blade icing is adopted. Compared with the SMOTE algorithm, the experimental results show that the method is effective in the diagnosis of fan blade icing fault and improves the accuracy of diagnosis.
Abstract
Because SCADA monitoring data of wind turbines are large and fast changing, the unbalanced proportion of data in various working conditions makes it difficult to process fault feature data. The existing methods mainly introduce new and nonrepeating instances by interpolating adjacent minority samples. In order to overcomethe shortcomings of these methods which does not consider boundary conditions in balancing data, an improved oversampling balancing algorithm SCSMOTE (safe circle synthetic minority oversampling technology) is proposed to optimize data sets. Then, for the balanced data sets, a fault diagnosis method based on improvedknearest neighbors (kNN) classification for wind turbine blade icing is adopted. Compared with the SMOTE algorithm, the experimental results show that the method is effective in the diagnosis of fan blade icing fault and improves the accuracy of diagnosis.
참고문헌 (17)
- J. Butler-Adam, "The fourth industrial revolution and education", South African Journal of Science, 114(5-6) (2018)
- L. Alhmoud, "Reliability improvement for a high-power IGBT in wind energy applications", IEEE Transactions on Industrial Electronics, 65(9), pp.7129~7137 (2018)
- Z. Bo, "Acoustic emission detection of fatigue cracks in wind turbine blades based on blind deconvolution separation", Fatigue & Fracture of Engineering Materials & Structures, 40(6), pp.959~970 (2017)
- 정영식, "Advanced Big Data Analysis, Artificial Intelligence & Communication Systems", JIPS(Journal of Information Processing Systems), 15(1), pp.1~6 (2019), 한국정보처리학회[DOI]
- 정영식, "Artificial Intelligence for the Fourth Industrial Revolution", JIPS(Journal of Information Processing Systems), 14(6), pp.1301~1306 (2018), 한국정보처리학회[DOI]
- S. Zhang, "Learning k for KNN classification", ACM Transactions on Intelligent Systems and Technology, 8(3) (2017)
- Yanling Wang, "Short-Term Wind Speed Forecast Based on Least Squares Support Vector Machine", JIPS(Journal of Information Processing Systems), 14(6), pp.1385~1397 (2018), 한국정보처리학회[DOI]
- S. Sun, "Impact of blade icing on wind turbines", Wind Energy, 2014(9), pp.100~103 (2014)
- Q. Dong, "A review of icing effect on horizontal axis wind turbine", Machinery Design and Manufacture, 2014(10), pp.269~272 (2014)
- C. Puyals, "Research on the causes of performance degradation of wind farm and fault warning of wind turbine components by SCADA data analysis", Wind Energy Industry, 2018(8), pp.65~68 (2018)
- N. Li, "Ice detection method by using SCADA data on wind turbine blades", Refrigeration Air Conditioning & Electric Power Machinery, 2018(1), pp.58~62 (2018)
- S. Wang, "A wind tunnel experimental study on icing distribution of rotating blade", Journal of Engineering Thermophysics, 38(6), pp.1229~1236 (2017)
- B. Yang, "Sparse time-frequency representation for incipient fault diagnosis of wind turbine drive train", IEEE Transactions on Instrumentation and Measurement, 67(11), pp.2616~2627 (2018)
- Y. Guo, "Wind turbine diagnosis under variable speed conditions using a single sensor based on the synchrosqueezing transform method", Sensors, 17 (2017)
- G. Douzas, "Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE", Information Sciences, 465, pp.1~20 (2018)
- 박종혁, "Advances in Multimedia Computing and Security and the Introduction of New Senior Editors", JIPS(Journal of Information Processing Systems), 12(4), pp.549~554 (2016), 한국정보처리학회
- 강승식, "Word Similarity Calculation by Using the Edit Distance Metrics with Consonant Normalization", JIPS(Journal of Information Processing Systems), 11(4), pp.573~582 (2015), 한국정보처리학회[DOI]