Showing 4 results for Frequency Response
Moniri, Farshad,
Volume 2, Issue 1 (1-2006)
Abstract
Power transformers are key components in electrical power supplies and their failure could cause severe consequences on continuity of service and also generates substantial costs. Identifying problems at an early stage, before catastrophic failure occurs, is a great benefit for reliable operation of power transformers. Frequency Response Analysis (FRA) is a new, well-known and powerful diagnostic test technique for transformers which could find mechanical as well as electrical faults such as detection and positioning of winding short circuit, winding movement, loss of clamping pressure, aging of insulation, etc. Yet there are several practical limitations to affect the accuracy and ease using this test as a regular condition monitoring technique in the field that many of them originated from noise and measuring errors. This paper purposes a transformer automated self diagnosis system can be installed on every power supply as a part of SCADA to extract FRA graphs from transformers and offers high repeatability which is a great benefit for FRA test. This is the first time that KALMAN Filter will be use in order to eliminate narrow-band and wide-band noises from FRA graphs that ends up not only smoothed measurement but also rate of changes that is so valuable in decision making and scheduling for transformers maintenance. So we will have an intelligent system which is able to predict the future of transformer using experience of not only own self but also all the transformers in an integrated network.
H. Heydari, M. Rezaee,
Volume 6, Issue 4 (12-2010)
Abstract
The principle object of this paper is to offer a modified design of Rogowski coil based on its frequency response. The improvement of the integrator circuit for nullifying the phase difference between the waveforms of the measured-current and the corresponding terminal voltage is a further object of this investigation.
This paper addresses an accurate, yet more efficient measuring and protecting device for low frequency applications. This requires verification for the simulations by physical descriptions and experimental results. These validate the superior performance of Rogowski coils over conventional current transformers.
Keywords: current transformer, frequency response, integrator circuit, mutual inductance, Rogowski coil, terminal resistor
A. Bijari, S. H. Keshmiri , W. Wanburee,
Volume 8, Issue 1 (3-2012)
Abstract
This paper presents a nonlinear analytical model for micromechanical silicon ring resonators with bulk-mode vibrations. A distributed element model has been developed to describe the dynamic behavior of the micromechanical ring resonator. This model shows the nonlinear effects in a silicon ring resonator focusing on the effect of large amplitudes around the resonance frequency, material and electrical nonlinearities. Through the combination of geometrical and material nonlinearities, closed-form expressions for third-order nonlinearity in mechanical stiffness of bulk-mode ring resonators are obtained. Using the perturbation method and the method of harmonic balance, the expressions for describing the effect of nonlinearities on the resonance frequency and stability are derived. The results, which show the effect of varying the AC drive voltage, initial gap, DC applied voltage and the quality factor on the frequency response and resonant frequencies, are discussed in detail. The nonlinear model introduces an appropriate method in the field of bulk-mode ring resonator design for achieving sufficient power handling and low motional resistance.
M. Bigdeli,
Volume 18, Issue 1 (3-2022)
Abstract
Moisture in the transformer insulation can shorten its life. There are many methods for detecting humidity in transformer paper insulation. One of the methods used in the factory to evaluate the drying process of transformer insulation and determine its humidity is the frequency response analysis method. In this paper, the desired experiments are performed on different transformers, and after obtaining the results of frequency response measurements, the required features are extracted from them. Then, using the k-means method, these features are placed in three clusters (dry, wet, and excessively wet). The cost function of the k-means method is optimized using the particle swarm optimization (PSO) algorithm to get a better result. By applying new data from different transformers, the capability of the proposed method in determining the moisture content of the transformer is evaluated. The results obtained from the evaluation of the insulation condition of another group of transformers indicate the high accuracy of the proposed method.