scholarly journals A Modified Aging Kinetics Model for Aging Condition Prediction of Transformer Polymer Insulation by Employing the Frequency Domain Spectroscopy

Polymers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2082 ◽  
Author(s):  
Jiefeng Liu ◽  
Xianhao Fan ◽  
Yiyi Zhang ◽  
Hanbo Zheng ◽  
Zixiao Wang ◽  
...  
Keyword(s):  
Moisture Content ◽  
Frequency Domain ◽  
Degree Of Polymerization ◽  
Kinetics Model ◽  
Model Parameters ◽  
Aging Condition ◽  
Feature Parameter ◽  
Aging Kinetics ◽  
Cellulose Insulation ◽  
Potential Tool

The aging kinetics model is of great interest to scholars since it is capable of describing the variation law between the degree of polymerization (DP) and the aging duration of transformer polymer (cellulose) insulation. However, it is difficult to determine the moisture content inside the transformer polymer insulation without destroying it, so that the model parameters cannot be confirmed. Such limitation greatly restricts its application. It is interesting to note that as long as the moisture content of the transformer polymer insulation could be characterized (replaced) by a certain feature parameter, the above issue will be solved naturally. The existing researches indicate that the Frequency Domain Spectroscopy (FDS) is sensitive to moisture. Consequently, the feature parameter that could characterize the moisture inside transformer polymer insulation (extracted from the FDS curve) can be used to report a modified aging kinetics model, which could perform the aging condition prediction of transformer polymer insulation under various test conditions, including aging duration, aging temperature, and initial moisture. In that respect, the average relative error of prediction results of prepared samples is equal to 7.41%, which reveals that the reported model might be serviced as a potential tool for the aging condition prediction of transformer polymer insulation.

New Method for Assessment Ageing Condition of Oil Impregnated Insulation Pressboard Based on Frequency Domain Spectroscopy

2014 ◽  
Vol 513-517 ◽  
pp. 323-327 ◽  
Author(s):  
Jian Hao ◽  
Jin Fu ◽  
Pei Guo ◽  
Gao Lin Wu ◽  
Qian Wang ◽  
...  
Keyword(s):  
Dielectric Loss ◽  
Moisture Content ◽  
Frequency Domain ◽  
Condition Assessment ◽  
New Method ◽  
Time Saving ◽  
Interpolation Curve ◽  
Ageing Condition ◽  
Cellulose Insulation

It is important to assess the condition of the cellulose insulation in transformer. However, taking paper samples from a transformer is both impractical and destructive. In this paper, a new method for assessment ageing condition of oil impregnated insulation pressboard based on frequency domain spectroscopy (FDS) was proposed. The FDS measurements were taken on oil impregnated insulation pressboards with five ageing levels at moisture content of 1.22%, 2.06%, 3.02% and 3.87%. The dielectric loss of all the samples were calculated bytanδ (f)interpolationandthe ageing condition assessment database which contains data of five ageing levels and 1%-4% moisture content was built. It is found that thetanδ (f)interpolation is more sencentive to ageing and moisture. It could realize the ageing condition assessment by comparing thetanδ (f)interpolation curve with the curves in the database.The assessing result of the middle-low main insulation life of a 220kV transformer valided that it is effective and time saving to use the new method for ageing condition assessment.

scholarly journals Prediction of Moisture and Aging Conditions of Oil-Immersed Cellulose Insulation Based on Fingerprints Database of Dielectric Modulus

Polymers ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1722
Author(s):  
Yiyi Zhang ◽  
Sheng Li ◽  
Xianhao Fan ◽  
Jiefeng Liu ◽  
Jiaxi Li
Keyword(s):  
Low Frequency ◽  
Degree Of Polymerization ◽  
Transformer Oil ◽  
Electrode Polarization ◽  
Insulation System ◽  
Dielectric Modulus ◽  
Aging Conditions ◽  
Fingerprint Database ◽  
Cellulose Insulation ◽  
Potential Tool

Frequency-domain spectroscopy (FDS) is demonstrated to be affected by electrode polarization and conductance behavior in the low-frequency ranges, which causes the unreliable prediction results of transformer cellulose insulation. In order to solve this issue, a fingerprint database based on the dielectric modulus is reported to predict the degree of polymerization (DP) and moisture content of cellulose insulation. In the current work, the relevant fingerprints that characterize the insulation conditions are obtained by studying the dielectric modulus curves of cellulose insulation with various insulation conditions, as well as the DC conductivity of transformer oil. Then, the dielectric modulus fingerprint database is established in the lab, and the accuracy of the reported fingerprint database is later verified. As a potential tool, the dielectric modulus fingerprint database is tested by several samples, and the results demonstrate that the accuracy of this method is more than 80%. In that respect, an interesting discovery of this paper is that the dielectric modulus fingerprint database may be a helpful tool for conditions prediction of the transformer cellulose insulation system.

Developing a Linearization Method to Determine Optimum Blending for Surimi with Varied Moisture Contents Using Linear Programming

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Hyeon W. Park ◽  
Jae W. Park ◽  
Won B. Yoon
Keyword(s):  
Linear Programming ◽  
Moisture Content ◽  
Standard Procedure ◽  
Unit Cost ◽  
Linearization Method ◽  
Model Parameters ◽  
Additional Information ◽  
Moisture Contents ◽  
Design Variables ◽  
Critical Moisture

AbstractNovel algorithm to determine the least cost formulation of a surimi blend was developed using linear programming (LP). Texture properties and the unit cost of surimi blend at the target moisture content were used as constraint functions and the objective function, respectively. The mathematical models to describe the moisture content dependence of the ring tensile properties were developed using critical moisture content, and the model parameters were used for the least cost LP (LCLP) model. The LCLP model successfully predicted the quality of surimi blend. Sensitivity analysis was used to obtain an additional information when the perturbations of design variables are provided. A standard procedure to determine the least cost formulation for blending surimi with varied moisture contents was systematically developed.

scholarly journals Effect of Radial Moisture Distribution on Frequency Domain Dielectric Response of Oil-Polymer Insulation Bushing

Polymers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1219 ◽  
Author(s):  
Daning Zhang ◽  
Guanwei Long ◽  
Yang Li ◽  
Haibao Mu ◽  
Guanjun Zhang
Keyword(s):  
Moisture Content ◽  
Space Charge ◽  
Frequency Domain ◽  
Water Distribution ◽  
Space Charge Polarization ◽  
Moisture Distribution ◽  
Mechanism Analysis ◽  
Loss Peak ◽  
Charge Polarization ◽  
Peak Value

In order to realize the diagnosis of water distribution, this paper analyzes the interface polarization and macroscopic space charge polarization mechanism when the water distribution is non-uniform. The experimental results of this paper and bushing show that when the moisture distribution is non-uniform, there is a significant loss peak in the tanδ-f curve. The loss peak shifts to higher frequencies as the non-uniformity coefficient increases. There are common intersection points between multiple tanδ-f curves. Further, this paper realizes the diagnosis of the location of moisture distribution through Frequency Domain Spectroscopy (FDS) testing of different voltages and different wiring methods based on the macroscopic space charge polarization. In the single-cycle FDS test, when the positive electrode is first added to the area with higher moisture content, the amplitude of the tanδ-f curve is smaller. The tanδ-f curves under different wiring methods constitute a “ring-shaped” loss peak. As the voltage increases, the peak value of the loss peak shifts to the lower frequency band. As the temperature increases, the peak value of the loss peak shifts to higher frequencies. Based on the above rules and mechanism analysis, this research provides a new solution for the evaluation of moisture content of oil-immersed polymers equipment.

Experimental identification of the material standard linear solid model parameters by means of dynamical measurements

2021 ◽  
pp. 107754632110371
Author(s):  
Stefano Amadori ◽  
Giuseppe Catania
Keyword(s):  
Frequency Domain ◽  
Solid Material ◽  
Model Parameters ◽  
Solid Model ◽  
Material Parameters ◽  
Experimental Identification ◽  
Standard Linear Solid Model ◽  
Standard Linear Solid ◽  
Standard Linear ◽  
Material Standard

A procedure for the experimental identification of the material standard linear solid model parameters by means of dynamic mechanical analysis test instrument measurements is presented. Since the standard linear solid material stress–strain functional D( ω) relationship in the frequency domain formally depends on the standard linear solid material parameters, a procedure able to identify these parameters from test measurement estimates is proposed in this work. Nevertheless, a critical, nonlinear and non-parametric approach is to be followed since the number of the material standard linear solid block components is generally unknown, and the material D( ω) shows a highly nonlinear dependency on the unknown standard linear solid material parameters. For these reasons, measurement and test model noise is expected to strongly influence the accuracy of the identification results. A multi-step procedure is presented, consisting first in the non-parametric identification of a frequency dependent, two degrees of freedom model instrument frame by means of a polynomial rational function, where polynomial order and parameters, such as polynomial coefficients and pole-residue couples, are optimally identified by means of an algebraic numerical technique and of an iterative stabilization procedure. Another procedure able to identify the material D( ω) polynomial rational functional relationship in the frequency domain is also proposed, taking into account the dynamic contribution of the instrument frame, of the inertial contribution of the distributed mass of the beam and of the lumped mass of the instrument force measuring system. An effective procedure, able to identify the standard linear solid material model parameters in the time domain from the identified material physical poles, is finally proposed. Some application examples, concerning the identification of the standard linear solid model of a known material and of an unknown composite material, are shown and discussed as well.

scholarly journals Methods for the Calculation of Thermoacoustic Stability Margins and Monte Carlo-Free Uncertainty Quantification

2017 ◽  
Author(s):  
Georg A. Mensah ◽  
Luca Magri ◽  
Jonas P. Moeck
Keyword(s):  
Monte Carlo ◽  
Factor Analysis ◽  
Risk Factor ◽  
Uncertainty Quantification ◽  
Frequency Domain ◽  
Gas Turbines ◽  
Network Models ◽  
System Stability ◽  
Risk Factor Analysis ◽  
Model Parameters

Thermoacoustic instabilities are a major threat for modern gas turbines. Frequency-domain based stability methods, such as network models and Helmholtz solvers, are common design tools because they are fast compared to compressible CFD computations. Frequency-domain approaches result in an eigenvalue problem, which is nonlinear with respect to the eigenvalue. Nonlinear functions of the frequency are, for example, the n–τ model, impedance boundary conditions, etc. Thus, the influence of the relevant parameters on mode stability is only given implicitly. Small changes in some model parameters, which are obtained by experiments with some uncertainty, may have a great impact on stability. The assessment of how parameter uncertainties propagate to system stability is therefore crucial for safe gas turbine operation. This question is addressed by uncertainty quantification. A common strategy for uncertainty quantification in thermoacoustics is risk factor analysis. It quantifies the uncertainty of a set of parameters in terms of the probability of a mode to become unstable. One general challenge regarding uncertainty quantification is the sheer number of uncertain parameter combinations to be quantified. For instance, uncertain parameters in an annular combustor might be the equivalence ratio, convection times, geometrical parameters, boundary impedances, flame response model parameters etc. Assessing also the influence of all possible combinations of these parameters on the risk factor is a numerically very costly task. A new and fast way to obtain algebraic parameter models in order to tackle the implicit nature of the eigenfrequency problem is using adjoint perturbation theory. Though adjoint perturbation methods were recently applied to accelerate the risk factor analysis, its potential to improve the theory has not yet been fully exploited. This paper aims to further utilize adjoint methods for the quantification of uncertainties. This analytical method avoids the usual random Monte Carlo simulations, making it particularly attractive for industrial purposes. Using network models and the open-source Helmholtz solver PyHoltz it is also discussed how to apply the method with standard modeling techniques. The theory is exemplified based on a simple ducted flame and a combustor of EM2C laboratory for which experimental validation is available.

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