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## Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization

#### Yunus Eroğlu [1] , Serap Ulusam Seçkiner [2]

The technological developments in wind energy field have reduced the investment and the operation costs. For this reason, wind farms have become more popular around the world. Increasing the share of wind energy in the market has led to the need for secure, inexpensive, and effective monitoring and control approaches. In the present work, various monitoring and control tools, which are cheap and easy to implement in wind farms using existing system data are proposed. The primary purpose of this study is to offer a new methodology, i.e. an artificial neural network (ANN) design with a novel training algorithm called Antrain ANN, in order to explore the early fault detection in a wind turbine. Our case problem is the fault detection for a wind turbine. For this issue, we used real data consisting of 873 samples with 12 inputs and one output. The models used in the work try to forecast fault occurrence before 10 minutes it happens.  The proposed Antrain ANN algorithm is compared with Quick Propagation, Conjugate Gradient Descent, Quasi-Newton, Limited Memory Quasi-Newton, Online Backpropagation, and Batch Back Propagation algorithms, respectively. The results have shown that the proposed novel approach has better results in the correct classification rates than other algorithms except the Quasi-Newton and Limited Memory Quasi-Newton ones.
Ant colony algorithm, Artificial neural networks, Fault detection, Wind energy, Wind turbine
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Birincil Dil en Mühendislik, Ortak Disiplinler Araştırma Makaleleri Orcid: 0000-0002-8354-6783Yazar: Yunus Eroğlu (Sorumlu Yazar)Kurum: İskenderun Technical UniversityÜlke: Turkey Orcid: 0000-0002-1612-6033Yazar: Serap Ulusam Seçkiner Kurum: Gaziantep UniversityÜlke: Turkey Yayımlanma Tarihi : 31 Aralık 2019
 Bibtex @araştırma makalesi { jes613315, journal = {Journal of Energy Systems}, issn = {}, eissn = {2602-2052}, address = {}, publisher = {Erol KURT}, year = {2019}, volume = {3}, pages = {139 - 147}, doi = {10.30521/jes.613315}, title = {Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization}, key = {cite}, author = {Eroğlu, Yunus and Ulusam Seçkiner, Serap} } APA Eroğlu, Y , Ulusam Seçkiner, S . (2019). Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization. Journal of Energy Systems , 3 (4) , 139-147 . DOI: 10.30521/jes.613315 MLA Eroğlu, Y , Ulusam Seçkiner, S . "Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization". Journal of Energy Systems 3 (2019 ): 139-147 Chicago Eroğlu, Y , Ulusam Seçkiner, S . "Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization". Journal of Energy Systems 3 (2019 ): 139-147 RIS TY - JOUR T1 - Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization AU - Yunus Eroğlu , Serap Ulusam Seçkiner Y1 - 2019 PY - 2019 N1 - doi: 10.30521/jes.613315 DO - 10.30521/jes.613315 T2 - Journal of Energy Systems JF - Journal JO - JOR SP - 139 EP - 147 VL - 3 IS - 4 SN - -2602-2052 M3 - doi: 10.30521/jes.613315 UR - https://doi.org/10.30521/jes.613315 Y2 - 2019 ER - EndNote %0 Journal of Energy Systems Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization %A Yunus Eroğlu , Serap Ulusam Seçkiner %T Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization %D 2019 %J Journal of Energy Systems %P -2602-2052 %V 3 %N 4 %R doi: 10.30521/jes.613315 %U 10.30521/jes.613315 ISNAD Eroğlu, Yunus , Ulusam Seçkiner, Serap . "Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization". Journal of Energy Systems 3 / 4 (Aralık 2020): 139-147 . https://doi.org/10.30521/jes.613315 AMA Eroğlu Y , Ulusam Seçkiner S . Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization. JES. 2019; 3(4): 139-147. Vancouver Eroğlu Y , Ulusam Seçkiner S . Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization. Journal of Energy Systems. 2019; 3(4): 147-139.