This research focuses on simulating a transformer
using electromagnetic field solver software: FEMM and COMSOL
Multiphysics®. These tools are used to simulate and extract
the model of a three-winding transformer. The primary objective
of the extracted model is to predict key magnetic parameters,
such as leakage and magnetizing inductances. These inductances
play a critical role in switch-mode power converter topologies,
ensuring proper operation and achieving high efficiency through
This study presents an automated approach for the generation of graphs from hand-drawn electrical circuit diagrams, aiming to streamline the digitization process and enhance the efficiency of traditional circuit design methods. Leveraging image processing, computer vision algorithms, and machine learning techniques, the system accurately identifies and extracts circuit components, capturing spatial relationships and diverse drawing styles.
The dataset is created on June 8, 2023, at 12:28 AM, consists of 760 annotated images in Pascal VOC format.
This dataset includes gathering 18-month raw PV data at time intervals of about 200 µs (5 kHz sampling). A post-processing 365-day day-by-day downsampled version, converted to 10 ms intervals (100 Hz sampling), is also included. The end results are two databases: 1. The original, raw, data, including both fast (short circuit, 200 µs) and slow (sweep, 2.5-3.9 s) information for 18 months. These show intervals of missing points, but are provided to allow potential users to reproduce any new work. 2.
