کنفرانس مهندسی برق ایران

صفحه اصلی / سی امین کنفرانس بین المللی مهندسی برق

Design an Intelligent Fault Detection System for Spring-Drive Operating Mechanism of SF6 High Voltage Circuit Breaker Using ADAMS

نویسندگان :

Milad Tahvilzadeh¹ Mehdi Aliyari Shooredeli² Ali asghar Razi Kazemi³

1- دانشگاه خواجه نصیر‌الدین طوسی 2- دانشگاه خواجه نصیر‌الدین طوسی 3- دانشگاه خواجه نصیر‌الدین طوسی

کلمات کلیدی :

High voltage circuit breaker (HVCB), Fault detection, Machine Learning, Travel curve (TC)

چکیده :

High-voltage circuit breakers (HVCBs) are one of the main components of a power system that have a protective function. That is why monitoring and faults diagnosing HVCBs are essential to prevent damage to other parts of system. This paper presents a design of an intelligent fault detection system, using machine learning algorithms for a typical EDF, 72.5 kV, SF6 HVCB with a spring drive mechanism. The faults of the drive mechanism appear in the travel curve of the contacts, which is used in the design of the fault detection model. As collecting experimental data is costly, ADAMS software has been employed to provide various scenarios. Subsequently, the database required to train the fault detection model is generated based on the extracting the appropriate feature from the curves. Afterwards, it is possible to compare the performance of machine learning models and provide a suitable model for fault detection. Finally, using the optimum model enables us to detect the state of the HVCBs. In the case of faulty state, the origin of the abnormality can be determined according to the faults considered in the database.

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