Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026Scopus SJRQ2/r/munzur/1051
  A Unified and Interpretable Benchmark of Classification Models for DGA-Based Power Transformer Fault Diagnosis

  Doğan, Kıvanç; Ertarğın, Merve; Çalışkan, Abuzer; Bakay, Ayşenur

  Power transformers are among the most critical components of electric power transmission and distribution systems, and unexpected failures can lead to substantial economic losses and prolonged power outages. Dissolved Gas Analysis (DGA) is the most widely used diagnostic technique for transformer fault diagnosis and involves interpreting gases dissolved in insulating oil. However, conventional interpretation methods, such as the Rogers ratio, the Doernenburg ratio, the IEC 60599 ratio method, and the Duval Triangle, rely heavily on expert knowledge, may produce inconsistent diagnoses for the same oil sample, and may fail to provide a diagnosis in certain cases. In this study, 12 classification models were evaluated using the publicly available Power Transformers Fault Detection and Diagnosis (FDD) and Remaining Useful Life (RUL) dataset and a unified evaluation protocol. Model performance was assessed using Accuracy, Balanced Accuracy, and Macro-F1 score, while model interpretability was investigated through Shapley Additive Explanations (SHAP) analysis. The results showed that ensemble tree-based methods achieved the best overall performance. LightGBM and Random Forest both attained an Accuracy of 0.969 and a Macro-F1 score of 0.924, while LightGBM further achieved the highest Balanced Accuracy of 0.940. XGBoost exhibited the most stable performance under cross-validation. SHAP analysis revealed that engineered relative concentration features, particularly the CO/H2 ratio and the combined gas ratio, were among the most influential features for fault classification. These findings demonstrate that, for datasets of this scale, ensemble tree-based models combined with well-designed features provide strong and interpretable performance for imbalanced DGA-based fault diagnosis, highlighting the effectiveness of feature-based ensemble learning for small- to medium-sized datasets.

  İncele
• BildiriAçık Erişim2020/r/munzur/3797
  Speed Control of DC Motor Using Single Phase Matrix Converter

  Boydak, Merve; Orhan, Ahmet; Caliskan, Abuzer

  This paper focuses on speed control of DC motor using new driver circuit of Single-Phase Matrix Converter (SPMC). Changing of modulation index has been provided with closed loop PI control. Thus, the voltage applied to the armature has been controlled and rotating of motor at the desired speed has been enabled. Insulated Gate Bipolar Transistors (IGBTs) are used to perform SPMC topology. Sinusoidal Pulse Width Modulation (SPWM) technique is used to obtain switching signals. MATLAB / Simulink is used to implement simulation.

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  AtıfScopus3·WoS3·OpenAlex3

  İncele
• BildiriAçık Erişim2020/r/munzur/3688
  Using Buck-Boost Rectifier with Single-Phase-Matrix Converter to Reduce Switch Count Operation

  Boydak, Merve; Orhan, Ahmet; Caliskan, Abuzer

  Recently, the development of advanced power semiconductor devices has made widespread use of power switching circuits and other power electronics applications in commercial and industrial environments. This paper focuses on Single Phase Matrix Converter (SPMC) as a AC-DC boost rectifier and AC-DC buck rectifier. The SPMC was operated in the desired mode using a single driver circuit. Insulated Gate Bipolar Transistors (IGBTs) are used in the power circuit as switching devices to implement SPMC topology. Switching signals are obtained by Sinusoidal Pulse Width Modulation (SPWM) technique. The simulation is carried out using MATLAB / Simulink.

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  AtıfScopus7·WoS3·OpenAlex5

  İncele
• BildiriAçık Erişim2020/r/munzur/3401
  Speed Control of DC Motor under Load Condition Using Single Phase Matrix Converter

  Boydak, Merve; Orhan, Ahmet; Caliskan, Abuzer

  In this study, speed control of a separately excited DC motor was performed using Single Phase Matrix Converter (SPMC). The driver circuit that operates SPMC in buck-boost mode was used. The DC motor was first run without any controller and the change in speed was observed in the case of loading. Then, the motor was run by using PI controller and speed of the motor was kept constant during loading. Switches in the single-phase matrix converter are switched using Sinusoidal Pulse Width Modulation (SPWM) technique. MATLAB/Simulink was used for simulation.

  AtıfScopus1

  İncele
• BildiriYayıncıda açık erişim2020/r/munzur/3142
  Multimode Operation of Single Phase Matrix Converter with Safe Commutation Strategy

  Boydak, Merve; Orhan, Ahmet; Caliskan, Abuzer

  In this study, the multimode operation of Single-Phase Matrix Converter (SMPC) is examined. The SPMC was operated as a controlled rectifier and frequency converter using a single driver circuit. Mode selection is provided by changing the value of the constant block in the driver circuit. In the rectifier mode, the sinusoidal input voltage was rectified and transferred to the output. Output voltage at the desired frequency value was generated in the frequency changer mode. Voltage peaks in frequency converter mode were prevented with the safe commutation strategy used. Harmonics in the output voltage were examined for different modulation index values. Switches in the SPMC are switched using Sinusoidal Pulse Width Modulation (SPWM) technique. MATLAB/Simulink was used for simulation.

  AtıfOpenAlex1

  İncele