S. Hajiaghasi, K. Abbaszadeh, A. Salemnia,
Volume 15, Issue 1 (3-2019)
Abstract
Interturn fault detection is a challenging issue in power transformer protection. In this paper, interturn faults of distribution transformer are studied and a new online detection method based on vibration analysis is proposed. Transformer electromagnetic forces are analyzed by time stepping finite element (TSFE) modeling of interturn fault. Since the vibration associated with inter-turn faults is caused by electromagnetic forces, axial and radial electromagnetic forces for various interturn faults are studied. Transformer winding vibration under interturn faults is studied through an equivalent mathematical model combined with electromagnetic force analysis. The results show that it is feasible to predict the interturn winding faults of transformer windings with the transformer vibration analysis method. Simulation and experimentation studies are carried out on 20/0.4 kV, 50 kVA distribution transformer. The results confirm the effectiveness of the proposed method.
Shuvojit Kundu, Tuhel Ahmed, Jia Uddin,
Volume 21, Issue 1 (3-2025)
Abstract
This study aims to evaluate a cantilever beam type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. Harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress are calculated with greater precision using eigen frequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.