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The main insulation structure of the valve‐side winding of converter transformer bears the effect of AC and DC superimposed voltage during operation. The electric field intensity in the pressboard is much higher than that in the pressboard in the AC transformer. This condition increases the probability of failure of insulation structure. Therefore, the design and optimization of the main insulation structure of the valve‐side winding are keys to ensure the stable operation of converter transformer. This study establishes a model of the main insulation structure of the valve‐side winding of the ±1100 kV converter transformer. The influence of the insulating oil–paper configuration on the electric field distribution of the main insulation structure of the valve‐side winding is analysed, and then, an optimization idea is proposed. The oil–paper configuration includes two aspects: oil–paper insulation structural design and combination selection, that is, the influence of typical oil–paper structural design parameters and the aging state of different oil–paper combinations on the electric field distribution. Finally, the optimization idea of the oil–paper configuration for valve‐side winding of converter transformer is obtained, and the established model is optimized. [ABSTRACT FROM AUTHOR]

The stable operation of transformers is an important guarantee of power system security. The temperature distribution of main insulation is different in long‐term operation. The temperature difference between the local hottest spot temperature and the average oil temperature in the transformer exceeds 30 K. Therefore, the oil‐paper insulation inside the transformer will exhibit non‐uniform ageing after long‐term operation. At present, frequency domain dielectric response (FDS) technology is widely used in transformer ageing assessment. However, the existing assessment methods are only used for overall insulation ageing assessment. The average moisture content and polymerization degree of the overall insulation between each phase winding are obtained. But it still cannot be used to assess the non‐uniform ageing of the transformer's main insulation. The radial, axial, and two directions non‐uniform ageing models have been made in the laboratory in this study. The FDS and physicochemical properties of non‐uniform ageing models were tested. The variation law of FDS for non‐uniform ageing models was analysed. Meanwhile, the dielectric relaxation model of non‐uniform ageing for main insulation was established. The method of frequency division iterative calculation was proposed. Combined with the Fessler moisture balance formula of ageing oil‐paper insulation, the quantitative assessment method for ageing parameters of the non‐uniform ageing model can be realized. Compared the calculated results with the chemical analysis results, the relative error of the polymerization degree calculation is less than 4%, and the error of the moisture content calculation is less than 0.3%. The calculation results can meet the needs of the engineering apply. Therefore, this method can realize the quantitative assessment of transformer main insulation ageing, which is of great significance to assess the transformer insulation state. [ABSTRACT FROM AUTHOR]

Oil‐paper composite is the main insulation system in oil‐filled transformers. In recent years, the use of nanotechnology to improve the electrical and thermal properties of transformer oil has become a field of research interest. In this paper, the electrical properties such as breakdown strength, volume resistivity, and dielectric response of nano‐filled oil‐paper insulation are evaluated. The evaluation is carried out on a double‐layer of oil‐paper composites insulation. The double‐layer samples are prepared considering different nano‐filler types. The studied nano‐filler types are Pb3O4, Al2O3, and SiO2 with average particle size 25 nm of each. For each nano‐filler type, oil‐paper samples with different concentrations (0.04, 0.06, 0.1, 0.2, and 0.4 g/L) are prepared. The effect of nano‐filler types on the breakdown strength, volume resistivity, and dielectric response of oil‐paper composites are highly evaluated. The results show that the filler types as well as filler permittivity affects the breakdown strength, volume resistivity, and dielectric response of oil‐paper composites insulation. Also, the results show that nano‐filler with high permittivity gives higher improvement in breakdown strength of Oil‐paper composite compared nano‐filler with low permittivity. Finally, the interpretation of all obtained results considering breakdown strength, volume resistivity, and dielectric response is highly reported. [ABSTRACT FROM AUTHOR]

This study is for the case where the available data of power transformer oil–paper insulation is limited to a small amount furfural data, to solve the problems in oil–paper insulation degradation modelling, such as few samples available, unknown function form of the degradation process, differences of individual transformers among degradation processes, and commonality of degradation trends. A power transformer oil–paper insulation degradation modelling and prediction method based on functional principal component analysis (FPCA) is proposed. First, discrete furfural data of oil–paper insulation degradation are converted into continuous functional data, and the common degradation information of transformers is extracted based on functional time warping technology. Second, the principal components of insulation degradation are extracted based on FPCA method, and the difference of degradation information of individual transformers is obtained by analysing the differential of principal component scores. Subsequently, power transformer oil–paper insulation degradation model is constructed, and finally, the degradation model is updated based on Bayesian theory and the oil–paper insulation degradation is predicted. The example results show that compared with traditional transformer oil–paper insulation degradation modelling method, the proposed method has obvious superiority in model accuracy. [ABSTRACT FROM AUTHOR]

To explore the aging assessment method of the oil–paper insulation in power transformers, the polarization and depolarization current (PDC) characteristics of oil–paper composite insulation samples are investigated under high applied voltage. Based on the asymmetry of polarization absorption current and depolarization current and the polarity effect of insulation pressboard, the repeated polarization current test method is proposed. A novel aging characteristic parameter, which is the ratio of the normalized charge for the first polarization and the normalized charge for the second polarization, is extracted. The difference between the decay rates of the first polarization current and the second polarization current increases at first and then decreases with the polarization time, and decreases with increasing aging degree of the pressboard. The more serious the insulation aging is, the smaller the variation range of aging characteristic parameter with polarization time is, and the closer the value is to 1. With decrease in the DP, the maximum of aging characteristic parameter changes in a decreasing trend. The aging condition of the oil–paper composite insulation can be assessed by the repeated polarization current method and the relationship between the aging characteristic parameter and the polarization time. [ABSTRACT FROM AUTHOR]

Considering that the working temperature is much higher in high‐voltage direct‐current (HVDC) convert transformers than in conventional AC transformers, the combination of thermally upgraded paper and natural ester might be a better choice to withstand high temperature in long‐term operation. This study compares the chemical structure, DC breakdown voltage, space charge and trap distribution of thermally upgraded paper aged in natural esters and mineral oil. The relationship between DC breakdown and accumulated charges was analyzed. Results show that the thermally upgraded paper aged in natural ester (NEI‐TUP) has a higher volume resistivity and DC breakdown voltage than that aged in mineral oil (MOI‐TUP). The NEI‐TUP group has a larger deep trap density than the MOI‐TUP group due to the chemical structure of natural ester. The larger deep trap density could contribute to the lower charge accumulation quantity and higher DC breakdown voltage. The thermally upgraded paper immersed in natural ester presents better insulation capability under thermal and DC electrical stress than that immersed in conventional mineral oil. This research indicated that the combination of thermally upgraded paper and natural ester might be a potential alternative for the mineral oil immersed paper in the future. [ABSTRACT FROM AUTHOR]

This paper utilizes a hybrid Debye model to accurately simulate the relaxation response process of the oil‐paper insulation of a transformer to explore the application of frequency domain dielectric spectroscopy (FDS) in nondestructive diagnosis of the aging condition of oil‐paper insulation. Via FDS test data, the model parameters can be identified, and the influence laws of FDS can be obtained through the variation of model parameters. To explore the effects of insulating paper moisture content, insulating paper layers, and test temperature on FDS characteristics, an FDS experimental platform is established. The results show that the hybrid Debye model can effectively reflect the relaxation response process of oil‐paper insulation under different conditions, as well as that a physical relationship between the model parameters and oil‐paper dielectric polarization exists. In addition, the parameters of the hybrid Debye model can be used as the characteristic quantities for the non‐destructive evaluation of the oil‐paper insulation state, providing new ideas for the non‐destructive evaluation of the oil‐paper insulation state. [ABSTRACT FROM AUTHOR]

In recent years, frequency domain spectroscopy (FDS) is often used to evaluate oil paper insulation state in power transformer bushing. But it is still very difficult to evaluate the moisture content accurately and quickly. In order to solve this problem, this paper proposes an intelligent algorithm based on random forest regression (RFR) to construct an efficient evaluation method through segmented FDS curves. Furthermore, the characteristics of FDS curves were studied and the intelligent method was compared with support vector regression (SVR) and deep neural networks (DNN). The results show that the dielectric loss, the real part and imaginary part of complex capacitance all move upward with the moisture increasing, so they can be used as the input feature of the evaluation model; The moisture content evaluation accuracy of the RFR model in the whole frequency band is higher than that of SVR and DNN models; With the increase of lower cut off frequency (FDS test stop frequency), the FDS test time is greatly shortened, and the accuracy of the RFR model can still meet the evaluation requirements. Therefore, the data in a compromise frequency band can be used to evaluate the moisture content of oil paper insulation accurately and quickly. [ABSTRACT FROM AUTHOR]

The condition assessment of oil–paper insulation is a vital issue in transformer management. To investigate the effect of moisture content on the accuracy of the prediction model, accelerated ageing experiments were performed with different initial moisture content (IMC) in laboratory condition. Two types of multi-parameter lifetime prediction models, e.g. with and without consideration of IMC, were presented for comparison purpose. The authors found that a better accuracy for its prediction results could be achieved by establishing the prediction models with the consideration of IMC. Besides, models considering IMC have better economic feasibility than that without considering IMC(non-IMC) as its total cost is cheaper according to life cycle cost (LCC) calculations. In addition, failure probability based on the proposed prediction models was also calculated as a direct indicator for evaluating the oil–paper insulation status. [ABSTRACT FROM AUTHOR]

Nomex insulation paper has been widely used in mining dry type transformer insulation because of its excellent performance. However, the injection of space charge can affect the electrical properties of the Nomex paper and accelerate the ageing process of the insulation system, which causes the insulation system failure or even breakdown. Therefore, it is of great practical value to study the space charge characteristics of Nomex insulation paper in different hygrothermal ageing conditions. The accelerated hygrothermal ageing tests of Nomex insulation specimens with different initial moisture contents were conducted. The space charge distribution of specimens impregnated by varnish were measured by the pulsed electro‐acoustic method at different ageing stages. Simultaneously, the space charge characteristics during polarising and depolarising phases were deeply analysed. Experimental results show that negative charges accumulate between the varnish‐paper interface in specimens near the anode. The number of negative charges gradually decreases with the increase of ageing degree. Under the influence of humidity, Nomex paper can be hydrolysed, which increases the trap density and trap level. Finally, a large amount of positive and negative charges in aged specimens would result in the distortion of the local electric field, which could decrease the breakdown strength of Nomex insulation specimens and be a threat to transformer insulation. [ABSTRACT FROM AUTHOR]

The AC breakdown properties of Kraft paper, pressboard and the enamel insulation layer in riceoil, peanut oil and corn oil were investigated under both new and agedconditions. The ageing of paper insulators and the enamel insulation layer inoils with the open cup method was carried out at 130 oC for 500 h in an aircirculation oven. The puncture breakdown strength was determined by varying thenumber of layers and thickness of Kraft paper, while various electrode gapdistances were used to measure the surface breakdown strength. Experimentalresults show that the breakdown strength and the tensile strength of paperinsulators impregnated with these vegetable oils are comparable to that inmineral oil, and the surface breakdown strength of paper insulators is slightlyaffected by types of impregnating oils. The ageing significantly reduces boththe breakdown strength and the tensile strength of paper insulators ininvestigated oils. In addition, it was also found that the enamel layer invegetable oils withstood higher puncture breakdown strength than in mineral oil,and the ageing process significantly reduced the puncture breakdown strength ofthe enamel layer. This enamel layer was observed to markedly enhance the surfacebreakdown strength of pressboard. [ABSTRACT FROM AUTHOR]

The value of paper conductivity provides quantitative evaluation of transformer insulation health. However, proper identification of paper conductivity requires complete profile of polarisation–depolarisation current (PDC). PDC measurement being a time‐consuming offline process generally takes several hours to complete. Furthermore, magnitude of PDC becomes very low at larger value of time, which makes it sensitive to changes in environmental conditions and field noise. Hence, accuracy of paper conductivity identification can be ensured by conducting multiple measurements. This in‐turn prolongs shutdown time of equipment and become less advantageous to utilities. Here, a method is proposed which is capable of estimating paper conductivity using PDC data recorded for only 800 s. The proposed technique is tested on data collected from several real‐life in‐service transformers. In order to illustrate the accuracy of the proposed technique, paper conductivities (calculated from short duration PDC) were compared with those computed using PDC measured for 10,000 s. [ABSTRACT FROM AUTHOR]

The service life of a transformer depends on the ageing degree of the internal oil–paper insulation. In order to reliably predict the remaining service life of oil–paper insulation for a single transformer, this study proposes a method based on monitoring the performance degradation data of oil–paper insulation. In this study, the remaining life prediction model of oil–paper insulation is established according to the Wiener stochastic process. The parameters of the model are iteratively updated by using the Bayesian rule and maximum expectation algorithm. The objective of remaining service life prediction of transformer oil–paper insulation is achieved. In the laboratory, multiple groups of oil–paper insulation samples undergo an ageing test at 130°C. Certain amount of performance degradation data is obtained by continuously monitoring the oil–paper insulation. Along with the prediction method of remaining life, the accuracy of the remaining life prediction of transformer oil–impregnated paper is verified when the model parameters are updated. This is a significant guiding factor for predicting the remaining life through the performance degradation data of the continuously operating transformer. [ABSTRACT FROM AUTHOR]

The oil‐impregnated transformer is an important part of the power system. The ageing degree of the internal oil‐paper insulation determines the service life of the transformer. The low frequency of the frequency domain dielectric spectroscopy can effectively characterise the ageing degree of transformer oil‐paper insulation. For accurately and quantitatively evaluate the aging state of oil‐paper insulation of transformer, the physical process of low‐frequency electrode polarisation is theoretically analysed in this work. Considering the polarisation of the low‐frequency electrode, the theoretical expression of the dielectric response of the equivalent XY model of the transformer is obtained. Meanwhile, to verify the rationality of the theoretical expression, the accelerated thermal ageing test of the oil‐paper insulation samples were carried out under laboratory conditions. The DC conductivity, ion mobility and FDS tests of oil‐paper insulation samples were tested on ageing 5, 10 and 15 days, respectively. The test results were combined with the theoretical expression of the low‐frequency dielectric response. It is found that the difference between the calculated result and the measured result is small. Therefore, the theoretical expression of the transformer equivalent XY model can be applied to calculate the dielectric parameters of the oil‐paper insulation at low‐frequency. [ABSTRACT FROM AUTHOR]

Induction period evaluated from time domain dielectric response of oil‐paper insulation (OPI) contains information related to heat dissipating property of oil. In the present paper, effect of aging sensitive oil properties on the value of induction period is investigated. Three types of dielectric liquids (pure mineral oil, synthetic ester, mixture of synthetic ester, and mineral oil) are considered for the present work. A neural network (NN) is used for modelling the non‐linear relationship between induction period and various oil properties. The trained network is subsequently used to study the influence of various oil properties on induction period. [ABSTRACT FROM AUTHOR]

Ambient temperature has significant influence on properties of oil–paper insulation, which makes surface discharge process complex. This paper aims at revealing the influence mechanism of ambient temperature on surface charge and discharge behaviours under DC voltage. The oil–paper with thickness of 0.08 mm was used and the ambient temperature varies from 20 to 80°C in this paper. The results of surface potential decay (SPD) experiments show that the initial surface potential declines and the process of SPD is accelerated with increasing temperature because of higher carrier mobility. Additionally, both shallow and deep trap energy level become deeper, the shallow trap density is enlarged while the deep trap density is shrunken at higher temperature. The surface discharge tests were performed and Weibull results indicate that it is prone to occurring surface discharge at higher ambient temperature. The possibility of surface discharge under negative voltage is larger than that under positive voltage because of polarity effect. It is concluded that more carriers escape from deep traps to participate in the procedure of surface discharge at higher temperature, which declines the surface discharge voltage. [ABSTRACT FROM AUTHOR]

Capacitive high‐voltage bushing is one of the typical oil‐immersed paper insulation equipment, which is an indispensable external connection component for power transformers. In order to evaluate the effectiveness of frequency domain spectroscopy (FDS) for diagnosing moisture content of oil‐immersed paper insulation bushing, this article studied the frequency‐domain dielectric characteristics of oil‐immersed paper insulation samples and field bushing. At the same time, the basic principle of interfacial polarisation is used to analyse the samples and field bushing with non‐uniform moisture content. The results show that the moisture content affects the whole frequency band of the FDS curve. When the distribution of moisture content is non‐uniform, the paper with high moisture content has a great influence on the whole FDS curve of oil‐immersed paper insulation. In addition, the FDS curves will show a significant loss peak. The frequency of the peak point gradually moves towards the high frequency as the non‐uniformity of the moisture content distribution increases. The experimental results show that the variation law of oil‐immersed paper insulation can be used to quantitatively evaluate the moisture content and moisture type of oil–paper insulation power equipment. [ABSTRACT FROM AUTHOR]

Study of alternate fluids for transformer and their combination with traditional ones is an interesting area of research. The intent of this work is to investigate the thermal ageing performance of ester oils (synthetic and natural), and mixed oil vis‐à‐vis mineral oil. All the samples were thermally stressed at 110, 140, 160, and 185°C for 2 weeks each. Dissolved decay contents in oil and linear thermal expansion coefficients of solid insulation have been studied using ultraviolet visible infrared spectroscopy and dilatometry analysis, respectively, as per ASTM standards. Change in functional groups of the insulation oils with ageing have been understood by Fourier transform infrared spectroscopy analysis. Additionally, diffusion of oil–moisture mixture into paper with ageing and the corresponding effect on dielectric strength of paper has been also examined using ASTM standards. It is observed that the use of synthetic ester (SE) and addition of SE to mineral insulating oil lead to improved performance of oil–paper insulation system with retarding the rate of degradation of the insulation system. [ABSTRACT FROM AUTHOR]

Accurate estimation of paper‐moisture in transformer insulation is necessary for ensuring their satisfactory operation. Paper‐moisture in transformer insulation can be estimated from their corresponding transfer function zero obtained from insulation model that is parameterised using polarisation depolarisation current data. However, paper‐moisture estimated using transfer function zero is less reliable for a new unit. Considering the fact, a method is proposed in this work that can estimate the paper‐moisture with greater accuracy. Instead of using only transfer function zero, tanδ has also been employed for estimating the paper‐moisture. In order to investigate the effectiveness, the proposed technique has first been applied on several test samples in the laboratory. The proposed technique is then applied on few power transformers to estimate their paper‐moisture. Results obtained from the experiment show that this technique can estimate the paper‐moisture content within test samples and power transformer insulation with better accuracy. [ABSTRACT FROM AUTHOR]

In conventional frequency domain spectroscopy (FDS) measurement, sinusoidal excitation is applied to a composite oil‐paper insulation under test, for a minimum of two cycles over a wide range of frequencies typically starting from 1 kHz to 1 mHz or even upto 0.1 mHz. The frequency sweep down to 1 mHz, is inevitably time consuming especially in lower frequency ranges. Considering the aforesaid fact, the main aim of the present study is to reduce overall FDS measurement time. The insulation under test is subjected to some fraction of one full cycle of excitation, and the corresponding dielectric response current is measured for each fraction. Using least square curve‐fitting technique, response current over two cycles is predicted from which dielectric dissipation factor (tanδ) is calculated. For this contribution, sinusoidal and non‐sinusoidal excitations in form of triangular waveform with five different initial slopes are used as excitation voltage. The technique is experimentally validated on three samples with different preset moisture contents prepared in the laboratory. The dielectric dissipation factor obtained by using the proposed technique is compared with the conventional method using two cycles, which show negligible differences. Most important of all is the overall test time, which can be brought down significantly when compared with conventional FDS measurement. [ABSTRACT FROM AUTHOR]

Polarisation and depolarisation current (PDC) measurement and analysis is one of the popular tools for effective diagnosis of power transformer insulation. Normally, it is assumed that polarisation current is the combination of the current due to dipole movement and conduction current. Similarly, the depolarisation current is only due to the relaxation of dipoles. However, it is found that after eliminating the effect of dc conduction from polarisation current the resulting current is not similar to that of measured depolarisation current. This shows some non‐linearity is present in the system. This non‐linearity occurs due to movement of trapped charge that resides in the interfacial region of oil–paper insulation. This study shows the effect of de‐trapping charge on various performance parameters that are used for insulation diagnosis like paper moisture and dielectric dissipation factor (tanδ). [ABSTRACT FROM AUTHOR]

Polarisation current profile varies non‐linearly with a magnitude of charging voltage. This implies performance parameters obtained from polarisation–depolarisation current and those measured using specialised equipment cannot always be compared. Results reported in this study suggested that the non‐linearity in insulation response can be explained in terms of the interaction between space charge and insulation conductivity. The influence of using different charging voltages and its effect on performance parameter calculation is investigated in this study with the help of laboratory samples. It is shown in this study that with the help of a trained artificial neural network, it is possible to identify the charging voltage at which insulation response exhibits minimum non‐linearity. To test the accuracy of the proposed method performance parameters measured using commercial equipment are compared with those calculated from the polarisation current profile. [ABSTRACT FROM AUTHOR]

To investigate the effect of aging on surface discharge of the pressboard on the shielding electrode at the end of bushing, a thermal aging preparation methods of different aging degrees of pressboard samples, surface defect model, and the associated hemisphere are designed and the step‐up method is used for subsequent experimental work. Finally, the partial discharges (PDs) under different degrees of aging are compared and combined with Fourier Transform Infrared spectra and electric field simulation. Results show that the pre‐discharge occurs mainly in the oil gap between the hemispherical electrode edge and the pressboard. The aging of the pressboard exerts no obvious effect on the discharge characteristics in the initial stage of PD; with the development of the discharge, the development of aging of pressboard leads to a higher electric field intensity acting over a greater area, the more intense the discharge, the faster the relative discharge increases and the larger its amplitude. This discharge will cause decomposition of the oil in the pores of the aging pressboard thus generating gas bubbles which will move as discharge develops. When the bubbles reach the surface of the pressboard, the local electric field intensity will increase and the discharge will become more intense. [ABSTRACT FROM AUTHOR]

The oil‐paper compound insulation plays a vital role in the insulation structure of power transformer. To obtain the characteristics of the transformer's insulation system, it is of great importance to study the dielectric response of oil‐paper compound insulation. In this study, fractional calculus is applied to model the oil‐paper compound insulation. Both low‐frequency and broadband high‐frequency models are proposed and then they are verified by fitting the measured data of different insulation papers. Finally they are applied to two different cases: (i) the low‐frequency model for fitting polarity reversal property; (ii) the broadband high‐frequency model for studying the influence of the parameters variations on the frequency domain spectroscopy (FDS). The results demonstrate the advantages of the proposed models when compared with traditional ones. [ABSTRACT FROM AUTHOR]

The converter transformer is an essential part of the DC transmission system. Compared with the traditional oil‐impregnated AC transformer, the main insulation of the converter transformer bears more complex electric field aging stress during long‐term operation. The influence of the proportion of AC components in the AC/DC composite electric field on insulation aging is still unclear. Therefore, a combined aging test platform of composite electric field and thermal was built in the laboratory, and accelerated aging tests of oil‐paper insulation under different AC/DC ratios were carried out. Through the time‐frequency domain dielectric response characteristics of oil‐paper insulation, the quantitative relationship between the time‐frequency domain dielectric response characteristic parameters and AC proportional coefficient in different aging stages was obtained. The results show that the influence of the AC component on the aging of the oil‐impregnated pressboard is more prominent. The maximum relaxation polarization time and the maximum exponential coefficient of polarization–depolarization current (PDC) can effectively characterize the aging of oil‐paper insulation. Meanwhile, to accurately assess the insulation state of the converter transformer, this paper established the equivalent dielectric relaxation model for the main insulation structure. A quantitative assessment method for moisture content and aging of oil‐paper insulation based on time‐frequency domain dielectric response was proposed. The influence of transformer oil conductivity, test temperature, and main insulation structure was eliminated. The effectiveness of this method was verified by comparative tests, the maximum error for DP is 20, and the maximum error for moisture content is 0.15%. The research results of this paper can provide theoretical support for on‐site assessment of converter transformer insulation status. [ABSTRACT FROM AUTHOR]

Analytical solution for transient, diffusing fields inside a ring conductor with rectangular cross‐section is discussed. Some details from the paper by V. Thiagarajan with additional clarifications are presented. The comment paper on the Thiagarajan analysis by Gratkowski and Ziolkowski criticises the boundary condition used at the outer radius of the ring conductor and changes it by setting the vector potential to zero at the outer radius of the ring. It is shown that: (i) the boundary condition used by Thiagarajan is an exact analytical result from classical physics, arising from interface field continuity criterion, (ii) setting the vector potential to zero at the outer radius of the ring is not a physically valid boundary condition, and (iii) it changes the boundary value problem entirely with no comparison to the analysis commented upon (which is valid mathematically and physically). [ABSTRACT FROM AUTHOR]

Frequency domain spectroscopy (FDS) is being used to assess the insulation condition of oil–paper power transformers. However, it has to date only been implemented on de‐energised transformers, which requires the transformers to be shut down for an extended period and may cause significant costs. To solve this issue, a newly improved monitoring method based on the FDS principle is proposed to implement the dielectric measurement on energised transformers. Moreover, a chirp waveform excitation and its novel processing method are introduced. Compared with the conventional FDS results, dielectric results from the energised insulation system have higher tanδ values because of the increased losses. To further understand the insulation ageing process, the effects of the geometric capacitance are removed from the measured imaginary admittance of the insulation system to enhance the ageing signature. The resulting imaginary admittance is then shown to correlate well with the central time constant in return voltage measurements results. The proposed methods address the issues on techniques used on energised transformers and provide a clue for on‐line FDS diagnostic application. [ABSTRACT FROM AUTHOR]

This study reports experimental study of cellulose performance in mixture of mineral and synthetic ester (SE) oils. Solid insulation impregnated with mineral oil (MO) and mixture oil has been subjected to accelerated thermal stresses to understand the deterioration rate of cellulose. Diffusion of oil–moisture mixture into paper and corresponding variation in dielectric strength of paper has been examined. Compatibility of solid insulation with MO and mixture oil is analysed by thermal expansion coefficients, X‐ray diffraction analysis and dissolved decay products. Furthermore, chemical functional groups present in aged oils are identified by Fourier transform infrared spectroscopy analysis. It is observed that the performance of cellulose insulation is improved with addition of SE to MO. This is achieved by higher water solubility of esters, which enables higher moisture consumption during hydrolysis and keeps cellulose dry. [ABSTRACT FROM AUTHOR]

Increased moisture content within an oil‐paper insulation system can significantly reduce its life expectancy, and for oil impregnated paper condenser type bushings, it is the most common cause of failure. Distinction between moisture contents using traditional power frequency tests of dissipation factor and capacitance can be difficult, particularly at ambient temperatures. Dielectric frequency response is becoming an established technique to measure the dissipation factor and capacitance of a bushing, but to date an accurate model to evaluate the condenser moisture content has not been presented using this technique. In this study, a dielectric frequency response bushing model is proposed and finite element method software is used to simulate the variation in dissipation factor and capacitance of a bushing with varying moisture content, as a function of frequency and temperature. The modelled results are compared with measurements reported in the literature and from the authors' own field measurements, where a good agreement is demonstrated. It is shown that the distinction in dissipation factor between moisture contents at frequencies <0.1 Hz is in excess of ten times greater than at 50 Hz. The proposed model can be used by practitioners to evaluate moisture content within the condenser insulation and distinguish between moisture contents ranging from 0.2 to 4.0%. [ABSTRACT FROM AUTHOR]

Ageing power systems infrastructure and concerns about climate change have increased interest in the next generation of grid infrastructure, known as the smart grid (SG). This study studies a particularly critical SG application: intelligent monitoring of power transformers for the early detection of insulation failure. Specifically, the focus is on the use of machine learning algorithms to distinguish between different types of partial discharges, which are closely correlated with insulation failure. Measurements made using acoustic emission sensors are used to train and test different classification algorithms. In an earlier study, high classification accuracies were achieved using training and test datasets collected under similar measurement conditions. However, under different conditions, classification accuracy was greatly reduced. Experiments using the latest classification techniques were performed, producing significant improvements in classification accuracy. A possible reason for these results could be a form of overfitting, and further experiments were conducted to test this hypothesis. [ABSTRACT FROM AUTHOR]

Measurement of the cervical range of motion (CROM) is significant for early diagnosis of cervical spondylosis and determination of the severity of the disease. Aiming at the problem of convenient and continuous measurement of CROM and the reduction of the impact of data fluctuations, this paper proposes a low‐cost method for testing and analyzing CROM. This paper analyzes the correspondence between smartphone orientation sensor angle and CROM, obtains smartphone orientation sensing data, and uses the extreme‐point symmetric mode decomposition method by calculating the energy of the difference value to extract the adaptive global mean curve of the CROM data, and calculates the cervical ROM. The statistical analysis of the CROM test results is carried out. Results show that the method proposed can obtain the CROM including flexion and extension, lateral flexion, and rotation in a single measurement, which has the advantages of continuous measurement and low cost. [ABSTRACT FROM AUTHOR]

The analysis of magnetic near‐field radiation emissions (MNRE) has recently raised more attention in device‐level electromagnetic compatibility testing. Pattern clustering of MNRE for integrated circuits manually is very time‐consuming because of the multi‐dimensional characteristics of MNRE, such as frequency, spatial position, emission intensity, etc. This paper proposes a novel pattern clustering method of MNRE, including strong emission frequency extraction, feature extraction, and density‐based clustering. Ring oscillator and five working states are designed on a Field Programmable Gate Array with 256 Ball Grid Array package, which are used to create a complex multi‐source emission case for verifying the effectiveness of the clustering method. The verification results show that the proposed method can correctly cluster the multi‐source emission patterns. Further, the method is also applied to a Microcontroller Unit with unknown operating states; the results show that the proposed method also can effectively distinguish the unknown emission patterns and locate the unknown interference source. The accuracy of the interference source location is proven by 3D X‐ray microscope inspection. [ABSTRACT FROM AUTHOR]

The problem of crystal ice formation inside aircraft turbine engines is well‐documented, and poses a significant risk to safety. The problem is not only one of power loss in flight, but the very real possibility that a flame‐out event could occur due to ice accretion on compressor stators, with potentially catastrophic outcomes. Although many instrumentation systems have been developed for wing ice detection, incipient formation of crystal ice is somewhat more difficult to detect. This is compounded by the need for a noncontact sensor which is robust to in‐flight conditions. This paper proposes an approach to the detection of ice formation based on microwave transmission characteristics across the first and possibly the second stage of the compressor stator. It is shown that noncontact detection is feasible under realistic conditions. The contribution of this paper is twofold. First, the microwave transmission approach is motivated using wind tunnel measurements, and appropriate frequency bands are determined. Next, a signal processing approach involving higher‐order analysis of time‐frequency distribution characteristics is then put forward. Experimental results are presented to support the hypothesis that multiband detection offers a workable approach to the incipient crystal‐ice detection problem. [ABSTRACT FROM AUTHOR]

This paper presents a novel bolt looseness detection method for power transmission towers based on vibration signal analysis. The proposed method utilizes pulse excitation to extract the vibration signal of the tower, which is then adaptively decomposed using the Variational Mode Decomposition of Spider Wasp optimizer (SWVMD). This overcomes limitations of traditional Variational Mode Decomposition methods by leveraging bio‐inspired optimization to improve signal decomposition. Simulated signals processed with different optimization methods verify the superiority of the SWO approach. Field tests on a 110‐kV transmission tower further demonstrate the effectiveness of the proposed SWVMD technique for analyzing on‐site vibration data. A new improved intrinsic multiscale sample entropy feature is also introduced for bolt state characterization. A Spider Wasp Support Vector Machine classifier is developed to realize accurate bolt loosening monitoring using the extracted features. Dynamic response tests under varying bolt conditions show that the method can identify early loosening and reduce tower damage risks compared to conventional techniques. This novel vibration‐based detection framework presents an innovative application of nature‐inspired computing for power infrastructure health monitoring. [ABSTRACT FROM AUTHOR]

Various types of insulation models with time‐invariant parameters are available in the literature. Depending on the aging sensitive performance parameters to be evaluated, different models need to be employed (e.g. XY model for oil and paper‐conductivity, conventional Debye model (CDM) for paper‐moisture and tanδ). While the XY model cannot be used for estimating paper‐moisture directly, analysis based on CDM parameter becomes dependent on its branch parameters, which are non‐unique. These factors lead to either incomplete or ambiguous insulation diagnosis. These problems are resolved using the proposed new insulation model containing unique time‐varying branch parameters. Another major advantage of the proposed model is that it can be used to evaluate a host of performance parameters (like paper‐conductivity, oil and paper‐moisture, dielectric loss) thus giving a complete picture of the insulation concerned. The application of the proposed model is also tested on data collected from several real‐life power transformers. [ABSTRACT FROM AUTHOR]

Eddy‐current technique has been used in several industrial applications, such as non‐destructive testing and characterization, transmission systems, and separation processes. The main advantage of other separation techniques for eddy current separation is the absence of direct contact and do not use other liquid and water. This paper presents a novel configuration for a single‐disk vertical eddy current separator, covered by alternating permanent magnets. Unlike several other works, which employ a horizontal orientation for magnetic disks. The advantage is that it contains one driving motor, few strong permanent magnets, and a small size and simpler construction than the usual eddy‐current separators. In this work, the analysis of an eddy current separator with magnetic single disk using a numerical model based on finite element method, the obtained partial differential equation is done into the numeric solver. The experimental device was realized to separate two kinds of non‐ferrous waste: aluminium and copper. The experiment results show the effect of speed variation, metals size, and kind of metal on ejection distance. [ABSTRACT FROM AUTHOR]

Electric fences used to create protected areas (PAs) are prone to faults that affect their operation. The conventional method of measuring the voltage of the fence periodically to detect faults and walking along the fence to locate the faults is inefficient and time consuming. This paper presents a low‐cost Raspberry Pi time domain reflectometer (TDR) for fault detection and localisation in electric fences. The system is designed using cheap off‐the‐shelf components. It uses time domain reflectometry to detect hard (open and short circuit) faults in electric fences. Time domain reflectometry is a method of detecting and locating faults in electrical cables. The Raspberry Pi TDR is evaluated and it has successfully detected and located open circuit and short circuit faults in electric fences with a mean absolute error of 1.52 m. The Raspberry Pi TDR offers the potential to remotely monitor electric fences autonomously, hence improving their effectiveness. [ABSTRACT FROM AUTHOR]

In order to solve the problem of remote oil level measurement for unmanned transformers, this paper proposes an online monitoring technology for transformer oil level based on ultrasonic sensors. Subsequently, a finite element model and experimental testing platform were constructed to analyse and verify the influencing factors of the transformer oil level sensors. The results indicated that there is a lower measurement error at 140 kHz in the ultrasonic frequency range of 20–320 kHz, which can be selected as the recommended frequency. The impurities in the oil and the thickness of the tank wall have a slight impact on the accuracy of oil level measurement, and can lead to a decrease in the signal‐to‐noise ratio of the echo. Furthermore, as the speed of sound increases by about 4 m/s, for every 1°C increase in oil temperature, it is necessary to calibrate the measurement results based on the oil temperature. The test results of actual experimental transformers showed that the designed online monitoring device can achieve high‐precision monitoring of transformer oil level, with a relative error generally less than 3%. [ABSTRACT FROM AUTHOR]

Air‐insulated switchgear plays an important role in distribution network and partial discharge (PD) is one of the common faults in its operation. The method of gas component analysis, which is to detect chemical gas products, is a novel one to discover PD. In order to study the feasibility of the method, the monitoring experiment of characteristic gases, comprising carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3), of metal protrusion PD is carried out. This paper conducts the comparative experiments on three main factors affecting PD: voltage, air humidity and degree of protrusion, as well as studies how they affect the formation of characteristic gases. According to the experimental result, higher applied voltage promotes the formation of characteristic gases in the same conditions. In addition, with the increase of humidity from 40% to 75%, the generation of gases is inhibited. Furthermore, when the needle–plate distance is 30 mm, the gas concentration has almost no change within 6 h, which is different from that of 10 mm. In conclusion, the difference in gases concentration reveals the influence of three main factors on the generation of characteristic gases and provides an analytical basis for PD detection by gas composition analysis. [ABSTRACT FROM AUTHOR]

Series multi‐break mechanical switch is one of the critical components of high‐voltage hybrid DC circuit breakers. However, due to the existence of distributed capacitance, the voltage distribution between the breaks is not balanced. This paper proposed a voltage sharing configuration method of the mechanical switch of hybrid DC circuit breaker, and carried out the static DC voltage and the transient voltage distribution characteristics tests to verify its effectiveness. Considering the influence of whole structure of the circuit breaker, this paper established the electrostatic field model and circuit simulation model of a typical ±535‐kV hybrid DC circuit breaker. And it analyzed the influence of single break's opening fault, breaking open distance, and the shielding fitting on the voltage distribution characteristics of series six break mechanical switch. According to the simulation results based on the Zhangbei voltage source converter‐based high‐voltage direct current project type test parameters, the parameters design of the voltage sharing components of the mechanical switch are obtained, which can meet the voltage sharing coefficient requirement of 95%. [ABSTRACT FROM AUTHOR]

Frequency‐domain spectroscopy (FDS) is a widely accepted method for the estimation of moisture content in oil–paper insulation of power transformer. Researchers have shown that measurement temperature is an important factor that not only shifts the tan δ curve both horizontally and vertically with respect to frequency axis but also affects the value of paper‐moisture content of transformer insulation. This implies FDS data measured at different temperatures yields different results even if the insulation under consideration remains more or less unaffected. Availability and construction of master curve for in‐service real‐life units might not always be available. This study proposes a method that is capable of predicting the profile of tan δ curve at different measurement temperatures. Existing expressions available for predicting paper‐moisture does not consider the effect of change in measurement temperature. This study also proposes modification of existing expression to predict the moisture content of insulation paper at any measurement temperature. In addition, this study outlines a method to evaluate the value of activation energy (Ea) from the insulation response. The discussed technique is first tested successfully on data recorded from a laboratory sample. Thereafter, the method is applied on data collected from a real‐life power transformer. [ABSTRACT FROM AUTHOR]

This paper proposes a deep learning method to predict the electromagnetic emission spectrum in the electromagnetic compatibility (EMC) test of aerospace products. A threshold‐based data decomposition method is used to propose the spike signal, reconstruct the original test data, and solve the contradiction between the overfitting and prediction accuracy of the deep learning method to deal with the EMC test spectrum. Using a long short‐term memory neural network architecture for predicting electromagnetic emission spectrum, the Bayesian optimization method is used to optimize the network hyperparameter, and the acquisition function is introduced into the loss function to improve the comprehensive training optimization of deep learning network. Apply the method to three numerical examples: signal line current conduction emission, power line voltage conduction emission, and electric field radiation emission. The analysis results indicate that at a 95% confidence level, the predicted electromagnetic emission spectrum is basically consistent with the test results. The prediction results can be used as the basis for EMC evaluation of aerospace electronic equipment. [ABSTRACT FROM AUTHOR]

The leakage current characteristic monitoring of transmission line insulators is considered a worthy technique for insulator state prediction. In this paper, the harmonic analysis of leakage current signals has been performed to analyze the composite insulator condition. Experimental studies of asymmetrically aged, fully aged, and virgin insulators have been conducted. The effects of different aging types, pollution, and humidity on leakage current components, such as harmonics and the phase differences with the applied voltage, have been investigated. The analysis of the results shows that the effect of asymmetric aging on leakage current components is non‐linear, and this non‐linearity increases with the degree of pollution. Also, the type of insulator aging can be determined by the ratio of the third‐ and fifth‐order leakage current harmonics. For instance, the classification of insulators into virgin, asymmetrically aged, and fully aged can be determined by examining the corresponding value ranges of 0–0.5, 0.5–0.9, and > 0.9, respectively. Similarly, the phase difference values of < 15% and those > 15% indicate the clean and polluted operating conditions individually. [ABSTRACT FROM AUTHOR]

In the field of RFID, the reading performance of tags is an important performance indicator for measuring tag. Related studies have shown that the tags' geometrical distribution has an important influence on the tags' reading performance. In order to optimize the tags' geometrical distribution and improve the tags' reading performance, this paper proposes a tag distribution optimization method based on multi‐level wavelet‐CNN (MWCNN) and extreme learning machine (ELM). First, this paper designs a tag distribution optimization system based on stereo‐vision. Second, the stereo‐cameras are used to capture the images of the tags. Aiming at the degradation phenomenon in the acquired images, MWCNN is used to recover the degraded tag images. On the basis of the image restoration, the template matching method is used to obtain the 3D coordinates of the tags. Then, ELM is used to model and predict the nonlinear relationship between 3D coordinates of the tags and the corresponding reading distance. The results show that the average prediction relative error is 0.56% and the time cost is 2.0 s. The average prediction relative error of ELM is smaller than GA‐BP and PSO‐BP. The time cost of ELM is smaller than the wavelet neural network. [ABSTRACT FROM AUTHOR]

An adaptive Dynamic Surface Controller (DSC) is designed for a two‐axis gimbal system with actuator dynamics in the presence of parametric uncertainties in [1]. A Lyapunov stability analysis is used to guarantee the convergence of the tracking error to the origin and boundedness of all closed‐loop signals. The main objective of this corrigendum is to point out several errors that occurred throughout the paper, resulting in the inaccuracy of the used dynamic model and ineffectiveness of the proposed controller. It should be noted that taking into account the corrections stated in this corrigendum, the main result of the original paper is still valid. [ABSTRACT FROM AUTHOR]

This paper proposes a novel evaluation method to address the challenge of evaluating insulation degradation in power transformer windings based on incomplete online Internet of Things (IoT) sensing data. The method leverages the Wasserstein Slim Generative Adversarial Imputation Network with Gradient Penalty algorithm to fill the irregularly missing power transformer IoT perception data, including voltage, current, temperature, and partial discharge. Subsequently, electrical, thermal, and mechanical performance degradation damage indicators for transformer winding insulation are constructed using the filled and complete IoT perception data. By applying the tensor fusion algorithm, the characteristics of these degradation damage indicators are fused, leading to the development of a comprehensive degradation evaluation index for the winding insulation. The evaluation of the winding insulation degradation state is achieved through the minimum quantization error method. The proposed method is validated using the real‐world transformer IoT perception data, and the experimental results demonstrate its ability to accurately assess the degree of winding insulation degradation, regardless of the presence of random or continuous irregularities in IoT sensing data. [ABSTRACT FROM AUTHOR]