Application of S transform for detection of external interferences in online transformer impulse frequency response analysis
- Authors: Mohseni, Bahar , Hashemnia, Naser , Islam, Syed
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017; Milan, Italy; 6th-9th June 2017 p. 1-4
- Full Text: false
- Reviewed:
- Description: Online impulse frequency response analysis is a recently-developed diagnostic method for in service transformer with a promising outlook. This paper aims to detect the impact of external interferences including pulse shaped interferences from switching operations and other phenomena in the power system on the frequency response of the transformer. For modeling the transformer for online IFRA, a simulation approach based on finite element analysis (FEA) and circuit analysis is used. In this approach, instead of using a linear model with static parameters, 3D finite element model of the transformer is calculated in Maxwell Software and then exported into an external Maxwell Spice circuit which allows for study the terminal behaviors of the transformer. A modified S transform is then applied to the recorded input and output signals in healthy and faulty conditions to construct the electrical impedance as well as the time-frequency contours of the transient responses.
Online detection of partial discharge inside power transformer winding through IFRA
- Authors: Mohseni, Bahar , Hashemnia, Naser , Islam, Syed
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE Power and Energy Society General Meeting, PESGM 2017; Chicago, United States; 16th-20th July 2017 Vol. 2018, p. 1-5
- Full Text: false
- Reviewed:
- Description: Predictive maintenance offers substantial benefits for detecting the early signs of power transformer faults before they burgeon into catastrophic failures. Online impulse frequency response analysis is a recently-developed diagnostic method for in service transformer with a promising outlook. This paper aims to propose an online partial discharge detection method the online IFRA test. To emulate the dynamic performance characteristics of in service transformer, 3D finite element model of the transformer is calculated in Maxwell Software. In post processing, the FEM sub-circuit model is exported into an external Maxwell Spice circuit to study the terminal behaviors of the transformer. A pulse signal simulating PD is injected between sections of the LV winding. The S transform is then applied to the recorded input and output signals in healthy and faulty conditions to construct the electrical impedance as well as the time-frequency contours of the transient responses. Also, a mechanical deformation is imposed on the transformer to compare its impact on online IFRA to the impact of internal partial discharge.
Understanding online frequency response signatures for transformer winding deformation: Axial displacement simulation
- Authors: Zhao, Zhongyong , Islam, Syed , Hashemnia, Naser , Hu, Di , Yao, Chenguo
- Date: 2016
- Type: Text , Conference proceedings , Conference paper
- Relation: 2016 International Conference on Condition Monitoring and Diagnosis, CMD 2016; Xi'an, China; 25th-28th September 2016 p. 404-407
- Full Text: false
- Reviewed:
- Description: The power transformer is considered as the most critical and expensive device in substation, however, the irreversible transformer winding mechanical deformation can eventually develop into catastrophic failure if no further steps are taken in a proper way, which would cause the outage of transformer and the significant economic losses. Online frequency response analysis (FRA) has been proven to be a promising tool for condition monitoring and diagnosing of winding deformation. Online FRA relies on graphic comparison of signatures, but up to now, there is no standard and practical interpretation code for signatures classification and quantification. This paper particularly studies the characteristic of online FRA signatures under the winding axial displacement mode, in which the 3D finite element electromagnetic analysis and online transformer equivalent high frequency electrical model are established as auxiliary tools to precisely emulate winding axial displacement. Results of this simulation will provide guidance on understanding online frequency response signatures.