Modal parameters identification of power transformer winding based on Hilbert-Huang Transform

Geng, Chao; Wang, F. H.; Jin, Z. J.

doi:10.1109/pesmg.2013.6672405

Cited by 4 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From this discussion, it may be noticed that frequencies and the damping ratio in different modes may be estimated from the measured response at an arbitrary location using Eqs. (21)- (24). However, mode shape evaluation using Eq.…”

Section: Evaluation Of Mode Shape From Limited Measurementsmentioning

confidence: 99%

“…Identify natural frequency and damping as described in Eqs. (22)- (24). Also check for frequency corresponding to excitation at source.…”

Section: Select Frequency Range Covering All Dominant Modes In the Stmentioning

confidence: 99%

“…Using these plots, modal frequency and damping ratio are identified by fitting a straight line as described in Eqs. (22)- (24). The natural frequencies identified from all four measurements are shown in Table I.…”

Section: Synthetic Measurementmentioning

confidence: 99%

“…Besides application in civil infrastructures, HHT based signal processing has gained popularity among the researchers and engineers in other fields like electrical , machine operation , oceanography and so on. Wu et al and Yan and Gao use HHT to identify the performance of a rotary machine during its operations.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Adaptive HHT (AHHT) based modal parameter estimation from limited measurements of an RC-framed building under multi-component earthquake excitations

Mahato

Teja

Chakraborty

2015

Struct. Control Health Monit.

View full text Add to dashboard Cite

SUMMARYPresent study aims to develop Hilbert-Huang transformation based signal processing scheme to identify the modal parameters of a reinforced concrete framed building subjected to multi-component earthquake excitations. An adaptive band-pass filtering strategy is developed to identify modal parameters (i.e. natural frequencies, damping and mode shapes). The proposed method is unique as it identifies the system parameters from the limited measurements due to arbitrary non-stationary excitations. The advantage of this technique is its ability to extract a complete set of modal frequencies from each measurement. The mode shapes are identified by updating the finite element model using the estimated modal parameters. In this context, the proposed method is effective as the large number of modal parameters identified from each measurement help to optimize the finite element model. The accuracy of the proposed method is demonstrated using both synthetic and actual measurements during an earthquake.

show abstract

Section: Evaluation Of Mode Shape From Limited Measurementsmentioning

confidence: 99%

“…Identify natural frequency and damping as described in Eqs. (22)- (24). Also check for frequency corresponding to excitation at source.…”

Section: Select Frequency Range Covering All Dominant Modes In the Stmentioning

confidence: 99%

Section: Synthetic Measurementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive HHT (AHHT) based modal parameter estimation from limited measurements of an RC-framed building under multi-component earthquake excitations

Mahato

Teja

Chakraborty

2015

Struct. Control Health Monit.

View full text Add to dashboard Cite

show abstract

“…The identification of the parameters of a transformer winding is an inverse problem and as such, is a difficult problem. Various methods were proposed, such as in [11] a method based on Hilbert–Huang transform to identify the transformer winding model parameters, whereas in [12] the author proposed a new parameter identification method using the least squares method. Vector fitting is a numerical method for rational approximation in the frequency domain using poles and residues [13].…”

Section: Introductionmentioning

confidence: 99%

Investigation of the transformer winding high‐frequency parameters identification using particle swarm optimisation method

Chanane

Bouchhida

Houassine

2016

IET Electric Power Applications

View full text Add to dashboard Cite

Intelligent methods are used more and more nowadays, in various fields, whose main purpose is to find better solutions to problems that are considered difficult. Identifying the parameters of transformer winding is a crucial problem. In this study, the authors shall use the 'particle swarm optimisation' (PSO) method to identify the parameters of highfrequency transformer winding, for diagnostic purposes. They validate the approach by comparing their results with the experimental ones. Two cases study of windings with air core were considered. Not only the effectiveness and accuracy of the proposed method is verified, the PSO method is compared with another methods referred to as transfer function and genetic algorithm. The results are in total agreement and show the reliability and the robustness of the PSO method. 2 Objective and principal of the study The primary goal in this study is to accurately identify the transformer winding parameters, starting from FRA measurements.

show abstract

Research on Transformer Winding State Identification Method Based on Frequency Domain Analysis and Multi-field Coupling

Jing

Wang

et al. 2021

2021 3rd International Conference on Smart Power &Amp; Internet Energy Systems (SPIES)

View full text Add to dashboard Cite

Modal parameters identification of power transformer winding based on Hilbert-Huang Transform

Cited by 4 publications

References 11 publications

Adaptive HHT (AHHT) based modal parameter estimation from limited measurements of an RC-framed building under multi-component earthquake excitations

Adaptive HHT (AHHT) based modal parameter estimation from limited measurements of an RC-framed building under multi-component earthquake excitations

Investigation of the transformer winding high‐frequency parameters identification using particle swarm optimisation method

Research on Transformer Winding State Identification Method Based on Frequency Domain Analysis and Multi-field Coupling

Contact Info

Product

Resources

About