In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a fle...In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a flexible structure and seldom assume the structural bias of input data,so it is difficult for transformers to learn positional encoding of the medical images when using fewer images for training.To solve these problems,a dual branch structure is proposed.In one branch,Mix-Feed-Forward Network(Mix-FFN)and axial attention are adopted to capture long-range dependencies and keep the translation invariance of the model.Mix-FFN whose depth-wise convolutions can provide position information is better than ordinary positional encoding.In the other branch,traditional convolutional neural networks(CNNs)are used to extract different features of fewer medical images.In addition,the attention fusion module BiFusion is used to effectively integrate the information from the CNN branch and Transformer branch,and the fused features can effectively capture the global and local context of the current spatial resolution.On the public standard datasets Gland Segmentation(GlaS),Colorectal adenocarcinoma gland(CRAG)and COVID-19 CT Images Segmentation,the F1-score,Intersection over Union(IoU)and parameters of the proposed TC-Fuse are superior to those by Axial Attention U-Net,U-Net,Medical Transformer and other methods.And F1-score increased respectively by 2.99%,3.42%and 3.95%compared with Medical Transformer.展开更多
Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally intelligentmachines.Graph-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC tasks.However,their...Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally intelligentmachines.Graph-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC tasks.However,their limited ability to collect and acquire contextual information hinders their effectiveness.We propose a Text Augmentation-based computational model for recognizing emotions using transformers(TA-MERT)to address this.The proposed model uses the Multimodal Emotion Lines Dataset(MELD),which ensures a balanced representation for recognizing human emotions.Themodel used text augmentation techniques to producemore training data,improving the proposed model’s accuracy.Transformer encoders train the deep neural network(DNN)model,especially Bidirectional Encoder(BE)representations that capture both forward and backward contextual information.This integration improves the accuracy and robustness of the proposed model.Furthermore,we present a method for balancing the training dataset by creating enhanced samples from the original dataset.By balancing the dataset across all emotion categories,we can lessen the adverse effects of data imbalance on the accuracy of the proposed model.Experimental results on the MELD dataset show that TA-MERT outperforms earlier methods,achieving a weighted F1 score of 62.60%and an accuracy of 64.36%.Overall,the proposed TA-MERT model solves the GBN models’weaknesses in obtaining contextual data for ERC.TA-MERT model recognizes human emotions more accurately by employing text augmentation and transformer-based encoding.The balanced dataset and the additional training samples also enhance its resilience.These findings highlight the significance of transformer-based approaches for special emotion recognition in conversations.展开更多
The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode n...The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode noise of the converter.Traditionally,the measurement method is used for transformer modeling,and a single lumped device is used to establish the transformer model,which cannot be predicted in the transformer design stage.Based on the transformer common-mode noise transmission mechanism,this paper derives the transformer common-mode equivalent capacitance under ideal conditions.According to the principle of experimental measurement of the network analyzer,the electromagnetic field finite element simulation software three-dimensional(3D)modeling and simulation method is used to obtain the two-port parameters of the transformer,extract the high-frequency parameters of the transformer,and establish its electromagnetic compatibility equivalent circuit model.Finally,an experimental prototype is used to verify the correctness of the model by comparing the experimental measurement results with the simulation prediction results.展开更多
Dry-Type Cast Resin Distribution Transformers(CRT)is the secondgeneration of air-cooled distribution transformers where oil is replaced by resin for electrical insulation.CRT transformers may installed indoor adjacent...Dry-Type Cast Resin Distribution Transformers(CRT)is the secondgeneration of air-cooled distribution transformers where oil is replaced by resin for electrical insulation.CRT transformers may installed indoor adjacent to or near residential areas since they are clean and safe comparing to the conventional transformers.But,as it is obvious,noise discrepancy is intrinsically accompanied with all types of transformers and is inevitable for CRT transformers too.Minimization of noise level caused by such these transformers has biological and ergonomic importance.As it is known the core of transformers is the main source of the noise generation.In this paper,experimental and numerical investigation is implemented for a large number of fabricated CRT transformers in IT Co(Iran Transfo Company)to evaluate the effective geometrical parameters of the core on the overall sound level of transformers.Noise Level of each sample is measured according to criteria of IEC60651 and is reported in units of Decibel(dB).Numerical simulation is done using noncommercial version of ANSYS Workbench software to extract first six natural frequencies and mode shapes of CRT cores which is reported in units of Hz.Three novel non-dimensional variables for geometry of the transformer core are introduced.Both experimental and numerical results show approximately similar response to these variables.Correlation between natural frequencies and noise level is evaluated statistically.Pearson factor shows that there is a robust conjunction between first two natural frequencies and noise level of CRTs.Results show that noise level decreases as the two first natural frequencies increases and vice versa,noise level increases as the two natural frequencies of the core decreases.Finally the noise level decomposed to two parts.展开更多
Structured microgrids(SμGs)and Flexible electronic large power transformers(FeLPTs)are emerging as two essential technologies for renewable energy integration,flexible power transmission,and active control.SμGs prov...Structured microgrids(SμGs)and Flexible electronic large power transformers(FeLPTs)are emerging as two essential technologies for renewable energy integration,flexible power transmission,and active control.SμGs provide the integration of renewable energy and storage to balance the energy demand and supply as needed for a given system design.FeLPT’s flexibility for processing,control,and re-configurability offers the capability for flexible transmission for effective flow control and enable SμGs connectivity while still keeping multiscale system level control.Early adaptors for combined heat and power have demonstrated significant economic benefits while reducing environmental foot prints.They bring tremendous benefits to utility companies also.With storage and active control capabilities,a 300-percent increase in bulk transmission and distribution lines are possible without having to increase capacity.SμGs and FeLPTs will also enable the utility industry to be better prepared for the emerging large increase in base load demand from electric transportation and data centers.This is a win-win-win situation for the consumer,the utilities(grid operators),and the environment.SμGs and FeLPTs provide value in power substation,energy surety,reliability,resiliency,and security.It is also shown that the initial cost associated with SμG and FeLPTs deployment can be easily offset with reduced operating cost,which in turn reduces the total life-cycle cost by 33%to 67%.展开更多
High frequency transformer is used in many applications among the Switch Mode Power Supply (SMPS), high voltage pulse power and etc can be mentioned. Regarding that the core of these transformers is often the ferrite ...High frequency transformer is used in many applications among the Switch Mode Power Supply (SMPS), high voltage pulse power and etc can be mentioned. Regarding that the core of these transformers is often the ferrite core;their functions partly depend on this core characteristic. One of the characteristics of the ferrite core is thermal behavior that should be paid attention to because it affects the transformer function and causes heat generation. In this paper, a typical high frequency transformer with ferrite core is designed and simulated in ANSYS software. Temperature rise due to winding current (Joule-heat) is considered as heat generation source for thermal behavior analysis of the transformer. In this simulation, the temperature rise and heat distribution are studied and the effects of parameters such as flux density, winding loss value, using a fan to cool the winding and core and thermal conductivity are investigated.展开更多
This paper proposed a method of optimal economic life interval evaluation of transformer, thus providing scientific support for power system planning and reconstruction. First, obtaining the transformer failure rate b...This paper proposed a method of optimal economic life interval evaluation of transformer, thus providing scientific support for power system planning and reconstruction. First, obtaining the transformer failure rate by using Levenberg-Marquardt based least squares algorithm on the consumption that transformer failure mode meets three-parameters Weibull distribution. Second, calculating operation cost and failure cost of transformer during its life cycle on the basis of transformer failure rate. Then, acquiring the optimal economic life interval of transformer through life cycle minimal average annual cost based on the theory of interval analysis. Finally, the proposed method is proved to be effective by applying to some real transformers.展开更多
This paper presents equipment for early detection of failures in the insulation of power transformers, checking existing partial discharges inside. The equipment involves hardware, control and signal acquisition softw...This paper presents equipment for early detection of failures in the insulation of power transformers, checking existing partial discharges inside. The equipment involves hardware, control and signal acquisition software, and signal analysis software. This equipment has a set of algorithms that were made with intelligent extraction techniques and interpretation of data. The degradation diagnosis of the equipment insulation is based on digital signal processing algorithms for extraction of features and also in artificial intelligence algorithms that allies a mining involving all the data linked to the equipment throughout its operating life can make an assessment of the operating conditions of the equipment and suggest interventions and provide an estimated time so that they have to be made.展开更多
This paper deals with experimental investigations of the electrical and physical properties of oil impregnated insulation paper for power transformers at different temperatures. The ac breakdown voltage, tensile stren...This paper deals with experimental investigations of the electrical and physical properties of oil impregnated insulation paper for power transformers at different temperatures. The ac breakdown voltage, tensile strength and water content of insulation papers impregnated in mineral oil for different time periods were investigated. The effect of insulation paper thickness on the electrical and mechanical properties has also been studied. The results showed that the breakdown voltage and the tensile strength decreased with increasing the time of immersion of insulation paper in oil at room temperature, at 5℃ and at -12℃. Also, the thermal aging effect on the characteristic of insulation paper has been studied. It was found that high temperatures affect the breakdown voltage and the tensile strength to a great extent.展开更多
In distribution systems,voltage levels of the various buses should be maintained within the permissible limits for satisfactory operation of all electrical installations and equipment.The task of voltage control is cl...In distribution systems,voltage levels of the various buses should be maintained within the permissible limits for satisfactory operation of all electrical installations and equipment.The task of voltage control is closely associated with fluctuating load conditions and corresponding requirements of reactive power compensation.The problem of load bus voltage optimization in distribution systems that have distributed generation(DG)has recently become an issue.In Oman,the distribution code limits the load bus voltage variations within±6%of the nominal value.Several voltage control methods are employed in active distribution systems with a high share of photovoltaic systems(PV)to keep the voltage levels within the desirable limits.In addition to the constraint of targeting the best voltage profile,another constraint has to be achieved which is the minimum loss in the distribution network.An optimised solution for voltage of load busses with on-load tap-changing(OLTC)tarnsformers and PV sources is presented in this paper.This study addresses the problem of optimizing the injected power from PV systems associated with the facilities of tap-changing transformers,as it is an important means of controlling voltage throughout the system.To avoid violating tap-changing constraints,a method is depicted for determining the minimal changes in transformer taps to control voltage levels with distributed PV sources.The taps of a range+5 to-15%,can be achieved by tap-changing transformers.The OLTC operation was designed to keep the secondary bus within the voltage standard for MV networks.展开更多
It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and ac...It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and accurate manner.To this end,a transformer fault diagnosis method based on infrared image processing and semi-supervised learning is proposed herein.First,we perform feature extraction on the collected infrared-image data to extract temperature,texture,and shape features as the model reference vectors.Then,a generative adversarial network(GAN)is constructed to generate synthetic samples for the minority subset of labelled samples.The proposed method can learn information from unlabeled sample data,unlike conventional supervised learning methods.Subsequently,a semi-supervised graph model is trained on the entire dataset,i.e.,both labeled and unlabeled data.Finally,we test the proposed model on an actual dataset collected from a Chinese electricity provider.The experimental results show that the use of feature extraction,sample generation,and semi-supervised learning model can improve the accuracy of transformer fault classification.This verifies the effectiveness of the proposed method.展开更多
For actively modulated In-line Sagnac interferential all optic fiber current transformers (AOFCTs), the accuracies are directly affected by the amplitude of the modulation signal. In order to deeply undertand the func...For actively modulated In-line Sagnac interferential all optic fiber current transformers (AOFCTs), the accuracies are directly affected by the amplitude of the modulation signal. In order to deeply undertand the function of the modulator, a theoretical model of modulation effect to AOFCTs is built up in this paper. The effect of the amplitude of the modulation signal to the output intensity of AOFCTs is theoretically formulated and numerical calculated. The results show that the modulation voltage variation could affect the output accuracies significantly. This might be some references on the investigation for practical applications of AOFCTs.展开更多
Outdoor power transformers are one of the most pervasive noise sources in power transmission and distribution systems.Accurate prediction of outdoor noise propagation plays a dominant role for the evaluation and contr...Outdoor power transformers are one of the most pervasive noise sources in power transmission and distribution systems.Accurate prediction of outdoor noise propagation plays a dominant role for the evaluation and control of noise relevant to the transformer stations.In this paper surface vibration tests are carried out on a scale model of a single-phase transformer tank wall at different excitation frequencies.The phase and amplitude of test data are found to be randomly distributed when the excitation frequency exceeds the seventh mode frequency,which allows the single-phase power transformer to be simplified as incoherent point sources.An outdoor-coherent model is subsequently developed and incorporated with the image source method to investigate noise propagation from single-phase power transformers,due to the occurrence of multiple reflections and diffractions in the propagation path of each point source.The proposed model is used to calculate the sound field of the power transformer group by exploiting the additional phase information.In comparison with the ISO9613 model and the boundary element method,it is found that the proposed coherent image source method leads to more accurate prediction results,and hence better performance for the prediction of the outdoor noise induced by single-phase power transformers.展开更多
Partial discharge test on a transformer is carried out according to the items in IEC 60. During the test, unproved measuring system is calibrated by proved system at a voltage no less than 50% the rated testing voltag...Partial discharge test on a transformer is carried out according to the items in IEC 60. During the test, unproved measuring system is calibrated by proved system at a voltage no less than 50% the rated testing voltage. The result is then extrapolated linearly, leading to an error related to the distribution of stray capacitance, which varies with the testing frequency, especially to large transformers. In this paper a factor, named the capacitive rise fact, is introduced to assess the rise. The factor can be adjusted to some extent by changing the reactance that is connected to the LV side of the testing circuit to lower the capacity of the power source. However, the factor changes when the voltage divider on the high voltage side is removed after the voltage ratio has been calculated, and a great error is resulted under unfavorable conditios.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 61972267the National Natural Science Foundation of Hebei Province under Grant F2018210148+1 种基金the University Science Research Project of Hebei Province under Grant ZD2021334the Science and Technology Project of Hebei Education Department(ZD2022098).
文摘In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a flexible structure and seldom assume the structural bias of input data,so it is difficult for transformers to learn positional encoding of the medical images when using fewer images for training.To solve these problems,a dual branch structure is proposed.In one branch,Mix-Feed-Forward Network(Mix-FFN)and axial attention are adopted to capture long-range dependencies and keep the translation invariance of the model.Mix-FFN whose depth-wise convolutions can provide position information is better than ordinary positional encoding.In the other branch,traditional convolutional neural networks(CNNs)are used to extract different features of fewer medical images.In addition,the attention fusion module BiFusion is used to effectively integrate the information from the CNN branch and Transformer branch,and the fused features can effectively capture the global and local context of the current spatial resolution.On the public standard datasets Gland Segmentation(GlaS),Colorectal adenocarcinoma gland(CRAG)and COVID-19 CT Images Segmentation,the F1-score,Intersection over Union(IoU)and parameters of the proposed TC-Fuse are superior to those by Axial Attention U-Net,U-Net,Medical Transformer and other methods.And F1-score increased respectively by 2.99%,3.42%and 3.95%compared with Medical Transformer.
文摘Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally intelligentmachines.Graph-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC tasks.However,their limited ability to collect and acquire contextual information hinders their effectiveness.We propose a Text Augmentation-based computational model for recognizing emotions using transformers(TA-MERT)to address this.The proposed model uses the Multimodal Emotion Lines Dataset(MELD),which ensures a balanced representation for recognizing human emotions.Themodel used text augmentation techniques to producemore training data,improving the proposed model’s accuracy.Transformer encoders train the deep neural network(DNN)model,especially Bidirectional Encoder(BE)representations that capture both forward and backward contextual information.This integration improves the accuracy and robustness of the proposed model.Furthermore,we present a method for balancing the training dataset by creating enhanced samples from the original dataset.By balancing the dataset across all emotion categories,we can lessen the adverse effects of data imbalance on the accuracy of the proposed model.Experimental results on the MELD dataset show that TA-MERT outperforms earlier methods,achieving a weighted F1 score of 62.60%and an accuracy of 64.36%.Overall,the proposed TA-MERT model solves the GBN models’weaknesses in obtaining contextual data for ERC.TA-MERT model recognizes human emotions more accurately by employing text augmentation and transformer-based encoding.The balanced dataset and the additional training samples also enhance its resilience.These findings highlight the significance of transformer-based approaches for special emotion recognition in conversations.
文摘The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode noise of the converter.Traditionally,the measurement method is used for transformer modeling,and a single lumped device is used to establish the transformer model,which cannot be predicted in the transformer design stage.Based on the transformer common-mode noise transmission mechanism,this paper derives the transformer common-mode equivalent capacitance under ideal conditions.According to the principle of experimental measurement of the network analyzer,the electromagnetic field finite element simulation software three-dimensional(3D)modeling and simulation method is used to obtain the two-port parameters of the transformer,extract the high-frequency parameters of the transformer,and establish its electromagnetic compatibility equivalent circuit model.Finally,an experimental prototype is used to verify the correctness of the model by comparing the experimental measurement results with the simulation prediction results.
文摘Dry-Type Cast Resin Distribution Transformers(CRT)is the secondgeneration of air-cooled distribution transformers where oil is replaced by resin for electrical insulation.CRT transformers may installed indoor adjacent to or near residential areas since they are clean and safe comparing to the conventional transformers.But,as it is obvious,noise discrepancy is intrinsically accompanied with all types of transformers and is inevitable for CRT transformers too.Minimization of noise level caused by such these transformers has biological and ergonomic importance.As it is known the core of transformers is the main source of the noise generation.In this paper,experimental and numerical investigation is implemented for a large number of fabricated CRT transformers in IT Co(Iran Transfo Company)to evaluate the effective geometrical parameters of the core on the overall sound level of transformers.Noise Level of each sample is measured according to criteria of IEC60651 and is reported in units of Decibel(dB).Numerical simulation is done using noncommercial version of ANSYS Workbench software to extract first six natural frequencies and mode shapes of CRT cores which is reported in units of Hz.Three novel non-dimensional variables for geometry of the transformer core are introduced.Both experimental and numerical results show approximately similar response to these variables.Correlation between natural frequencies and noise level is evaluated statistically.Pearson factor shows that there is a robust conjunction between first two natural frequencies and noise level of CRTs.Results show that noise level decreases as the two first natural frequencies increases and vice versa,noise level increases as the two natural frequencies of the core decreases.Finally the noise level decomposed to two parts.
文摘Structured microgrids(SμGs)and Flexible electronic large power transformers(FeLPTs)are emerging as two essential technologies for renewable energy integration,flexible power transmission,and active control.SμGs provide the integration of renewable energy and storage to balance the energy demand and supply as needed for a given system design.FeLPT’s flexibility for processing,control,and re-configurability offers the capability for flexible transmission for effective flow control and enable SμGs connectivity while still keeping multiscale system level control.Early adaptors for combined heat and power have demonstrated significant economic benefits while reducing environmental foot prints.They bring tremendous benefits to utility companies also.With storage and active control capabilities,a 300-percent increase in bulk transmission and distribution lines are possible without having to increase capacity.SμGs and FeLPTs will also enable the utility industry to be better prepared for the emerging large increase in base load demand from electric transportation and data centers.This is a win-win-win situation for the consumer,the utilities(grid operators),and the environment.SμGs and FeLPTs provide value in power substation,energy surety,reliability,resiliency,and security.It is also shown that the initial cost associated with SμG and FeLPTs deployment can be easily offset with reduced operating cost,which in turn reduces the total life-cycle cost by 33%to 67%.
文摘High frequency transformer is used in many applications among the Switch Mode Power Supply (SMPS), high voltage pulse power and etc can be mentioned. Regarding that the core of these transformers is often the ferrite core;their functions partly depend on this core characteristic. One of the characteristics of the ferrite core is thermal behavior that should be paid attention to because it affects the transformer function and causes heat generation. In this paper, a typical high frequency transformer with ferrite core is designed and simulated in ANSYS software. Temperature rise due to winding current (Joule-heat) is considered as heat generation source for thermal behavior analysis of the transformer. In this simulation, the temperature rise and heat distribution are studied and the effects of parameters such as flux density, winding loss value, using a fan to cool the winding and core and thermal conductivity are investigated.
文摘This paper proposed a method of optimal economic life interval evaluation of transformer, thus providing scientific support for power system planning and reconstruction. First, obtaining the transformer failure rate by using Levenberg-Marquardt based least squares algorithm on the consumption that transformer failure mode meets three-parameters Weibull distribution. Second, calculating operation cost and failure cost of transformer during its life cycle on the basis of transformer failure rate. Then, acquiring the optimal economic life interval of transformer through life cycle minimal average annual cost based on the theory of interval analysis. Finally, the proposed method is proved to be effective by applying to some real transformers.
文摘This paper presents equipment for early detection of failures in the insulation of power transformers, checking existing partial discharges inside. The equipment involves hardware, control and signal acquisition software, and signal analysis software. This equipment has a set of algorithms that were made with intelligent extraction techniques and interpretation of data. The degradation diagnosis of the equipment insulation is based on digital signal processing algorithms for extraction of features and also in artificial intelligence algorithms that allies a mining involving all the data linked to the equipment throughout its operating life can make an assessment of the operating conditions of the equipment and suggest interventions and provide an estimated time so that they have to be made.
文摘This paper deals with experimental investigations of the electrical and physical properties of oil impregnated insulation paper for power transformers at different temperatures. The ac breakdown voltage, tensile strength and water content of insulation papers impregnated in mineral oil for different time periods were investigated. The effect of insulation paper thickness on the electrical and mechanical properties has also been studied. The results showed that the breakdown voltage and the tensile strength decreased with increasing the time of immersion of insulation paper in oil at room temperature, at 5℃ and at -12℃. Also, the thermal aging effect on the characteristic of insulation paper has been studied. It was found that high temperatures affect the breakdown voltage and the tensile strength to a great extent.
文摘In distribution systems,voltage levels of the various buses should be maintained within the permissible limits for satisfactory operation of all electrical installations and equipment.The task of voltage control is closely associated with fluctuating load conditions and corresponding requirements of reactive power compensation.The problem of load bus voltage optimization in distribution systems that have distributed generation(DG)has recently become an issue.In Oman,the distribution code limits the load bus voltage variations within±6%of the nominal value.Several voltage control methods are employed in active distribution systems with a high share of photovoltaic systems(PV)to keep the voltage levels within the desirable limits.In addition to the constraint of targeting the best voltage profile,another constraint has to be achieved which is the minimum loss in the distribution network.An optimised solution for voltage of load busses with on-load tap-changing(OLTC)tarnsformers and PV sources is presented in this paper.This study addresses the problem of optimizing the injected power from PV systems associated with the facilities of tap-changing transformers,as it is an important means of controlling voltage throughout the system.To avoid violating tap-changing constraints,a method is depicted for determining the minimal changes in transformer taps to control voltage levels with distributed PV sources.The taps of a range+5 to-15%,can be achieved by tap-changing transformers.The OLTC operation was designed to keep the secondary bus within the voltage standard for MV networks.
基金supported by China Southern Power Grid Co.Ltd.science and technology project(Research on the theory,technology and application of stereoscopic disaster defense for power distribution network in large city,GZHKJXM20180060)National Natural Science Foundation of China(No.51477100).
文摘It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and accurate manner.To this end,a transformer fault diagnosis method based on infrared image processing and semi-supervised learning is proposed herein.First,we perform feature extraction on the collected infrared-image data to extract temperature,texture,and shape features as the model reference vectors.Then,a generative adversarial network(GAN)is constructed to generate synthetic samples for the minority subset of labelled samples.The proposed method can learn information from unlabeled sample data,unlike conventional supervised learning methods.Subsequently,a semi-supervised graph model is trained on the entire dataset,i.e.,both labeled and unlabeled data.Finally,we test the proposed model on an actual dataset collected from a Chinese electricity provider.The experimental results show that the use of feature extraction,sample generation,and semi-supervised learning model can improve the accuracy of transformer fault classification.This verifies the effectiveness of the proposed method.
文摘For actively modulated In-line Sagnac interferential all optic fiber current transformers (AOFCTs), the accuracies are directly affected by the amplitude of the modulation signal. In order to deeply undertand the function of the modulator, a theoretical model of modulation effect to AOFCTs is built up in this paper. The effect of the amplitude of the modulation signal to the output intensity of AOFCTs is theoretically formulated and numerical calculated. The results show that the modulation voltage variation could affect the output accuracies significantly. This might be some references on the investigation for practical applications of AOFCTs.
基金This work is funded by the Anhui Natural Science Foundation Project of China(under Grant KJ2016A201)the National Natural Science Foundation of China(under Grant 11774378).
文摘Outdoor power transformers are one of the most pervasive noise sources in power transmission and distribution systems.Accurate prediction of outdoor noise propagation plays a dominant role for the evaluation and control of noise relevant to the transformer stations.In this paper surface vibration tests are carried out on a scale model of a single-phase transformer tank wall at different excitation frequencies.The phase and amplitude of test data are found to be randomly distributed when the excitation frequency exceeds the seventh mode frequency,which allows the single-phase power transformer to be simplified as incoherent point sources.An outdoor-coherent model is subsequently developed and incorporated with the image source method to investigate noise propagation from single-phase power transformers,due to the occurrence of multiple reflections and diffractions in the propagation path of each point source.The proposed model is used to calculate the sound field of the power transformer group by exploiting the additional phase information.In comparison with the ISO9613 model and the boundary element method,it is found that the proposed coherent image source method leads to more accurate prediction results,and hence better performance for the prediction of the outdoor noise induced by single-phase power transformers.
文摘Partial discharge test on a transformer is carried out according to the items in IEC 60. During the test, unproved measuring system is calibrated by proved system at a voltage no less than 50% the rated testing voltage. The result is then extrapolated linearly, leading to an error related to the distribution of stray capacitance, which varies with the testing frequency, especially to large transformers. In this paper a factor, named the capacitive rise fact, is introduced to assess the rise. The factor can be adjusted to some extent by changing the reactance that is connected to the LV side of the testing circuit to lower the capacity of the power source. However, the factor changes when the voltage divider on the high voltage side is removed after the voltage ratio has been calculated, and a great error is resulted under unfavorable conditios.