When discharge faults occur in dry air switchgear,the air decomposes to produce diverse gases,with NO_(2) reaching the highest levels.Detecting the NO_(2) level can reflect the operation status of the equipment.This p...When discharge faults occur in dry air switchgear,the air decomposes to produce diverse gases,with NO_(2) reaching the highest levels.Detecting the NO_(2) level can reflect the operation status of the equipment.This paper proposes to combine ZnO cluster with MoS_(2) to improve the gassensitive properties of the monolayer.Based on the Density Functional Theory(DFT),the effect of(ZnO)n size on the behavior of MoS_(2 )is considered.Key parameters such as adsorption energy and band gap of(ZnO)n-MoS_(2)/NO_(2) system were calculated.The ZnO-MoS_(2) heterojunction was successfully synthesized by a hydrothermal method.The gas sensor exhibits a remarkable response and a fast response-recovery time to 100 ppm NO_(2).In addition,it demonstrates excellent selectivity,long-term stability and a low detection limit.This work confirms the potential of the ZnO-MoS_(2) composite structure as a highly effective gas sensor for NO_(2) detection,which provides valuable theoretical and experimental insights for fault detection in dry air switchgear.展开更多
Founded in 1919, Shanghai Hua Tong Switchgear Works ("HTSW" in short for below) is one of large enterprises on state level. With high and new technology, it is designed as an export base for mechanical and e...Founded in 1919, Shanghai Hua Tong Switchgear Works ("HTSW" in short for below) is one of large enterprises on state level. With high and new technology, it is designed as an export base for mechanical and electrical product of the Ministry of Machinery Industry as well. It has been awarded the honor of first grade factory in the competition for key and major project construction in Shanghai year by year,展开更多
Transient enclosure voltage（TEV）,which is a phenomenon induced by the inner dielectric breakdown of SF_6 during disconnector operations in a gas-insulated switchgear（GIS）,may cause issues relating to shock hazard ...Transient enclosure voltage（TEV）,which is a phenomenon induced by the inner dielectric breakdown of SF_6 during disconnector operations in a gas-insulated switchgear（GIS）,may cause issues relating to shock hazard and electromagnetic interference to secondary equipment.This is a critical factor regarding the electromagnetic compatibility of ultra-high-voltage（UHV）substations.In this paper,the statistical characteristics of TEV at UHV level are collected from field experiments,and are analyzed and compared to those from a repeated strike process.The TEV waveforms during disconnector operations are recorded by a self-developed measurement system first.Then,statistical characteristics,such as the pulse number,duration of pulses,frequency components,magnitude and single pulse duration,are extracted.The transmission line theory is introduced to analyze the TEV and is validated by the experimental results.Finally,the relationship between the TEV and the repeated strike process is analyzed.This proves that the pulse voltage of the TEV is proportional to the corresponding breakdown voltage.The results contribute to the definition of the standard testing waveform of the TEV,and can aid the protection of electronic devices in substations by minimizing the threat of this phenomenon.展开更多
Due to imperfect manufacturing technology, design defects and environmental impact, the failure rate of 10 kV switchgear is very high. For this reason, based on taken present situation of traditional switchgear and th...Due to imperfect manufacturing technology, design defects and environmental impact, the failure rate of 10 kV switchgear is very high. For this reason, based on taken present situation of traditional switchgear and the current technical requirements for switchgear into account, a new reliable and safe modular high voltage switchgear design method is presented in this paper, which can reduce the failure rate of switchgear and improve the reliability of power supply. The electric field and temperature rise simulation model are established to check the reasonability and validity. By using the finite element software, the simulation results show that the design in this paper has a maximum temperature rise of 55 K for the main cabinet and a maximum temperature rise of 45 K for the deputy cabinet, which is far below the international standard of 70 K. The areas where the partial discharge is likely to occur within the switchgear are places such as the connection between bus-bar and cabinet, bus-bar joint and bus-bar corner. In order to avoid potential dangers, the discharge point must be located in time to prevent insulation fault of electrical equipment of the high voltage switchgear. The simulation results demonstrate that the design method in this paper greatly improve the reliability of switchgear and meets the demands of power system.展开更多
Objective In order to find early latent faults and prevent catastrophic failures, diagnosis of insulation condition by measuring technique of partial discharge(PD) in gas insulated switchgear (GIS) is applied in this ...Objective In order to find early latent faults and prevent catastrophic failures, diagnosis of insulation condition by measuring technique of partial discharge(PD) in gas insulated switchgear (GIS) is applied in this paper, which is one of the most basic ways for diagnosis of insulation condition. Methods Ultra high frequency(UHF) PD detection method by using internal sensors has been proved efficient, because it may avoid the disturbance of corona, but the sensor installation of this method will be limited by the structure and operation condition of GIS. There are some of electromagnetic (E-M) waves leak from the place of insulation spacer, therefore, the external sensors UHF measuring PD technique is applied, which isn't limited by the operation condition of GIS. Results This paper analyzes propagated electromagnetic (E-M) waves of partial discharge pulse excited by using the finite-difference time-domain (FDTD) method. The signal collected at the outer point is more complex than that of the inner point, and the signals' amplitude of outer is about half of the inner, because it propagates through spacer and insulation slot. Set up UHF PD measuring system. The typical PD in 252kV GIS bus bar was measured using PD detection UHF technique with external sensors. Finally, compare the results of UHF measuring technique using external sensors with the results of FDTD method simulation and the traditional IEC60270 method detection. Conclusion The results of experiment shows that the UHF technique can realize the diagnosis of insulation condition, the results of FDTD method simulation and the result UHF method detection can demonstrate each other, which gives references to further researches and application for UHF PD measuring technique.展开更多
Partial discharge(PD)is an important reason for the insulation failure of the switchgear.In the process of PD detection,PD signal is often annihilated in strong noise.In order to improve the accuracy of PD detection i...Partial discharge(PD)is an important reason for the insulation failure of the switchgear.In the process of PD detection,PD signal is often annihilated in strong noise.In order to improve the accuracy of PD detection in power plant switchgear,a method based on continuous adaptive wavelet threshold switchgear PD signals denoising is proposed in this paper.By constructing a continuous adaptive threshold function and introducing adjustment parameters,the problems of over⁃processing of traditional hard threshold functions and incomplete denoising of soft threshold functions can be improved.The analysis results of simulated signals and measured signals show that the continuous adaptive wavelet threshold denoising method is significantly better than the traditional denoising method for the PD signal.The proposed method in this paper retains the characteristics of the original signal.Compared with the traditional denoising methods,after denoising the simulated signals,the signal⁃to⁃noise ratio(SNR)is increased by more than 30%,and the root⁃mean⁃square error(RMSE)is reduced by more than 30%.After denoising the real signal,the noise suppression ratio(NRR)is increased by more than 40%.The recognition accuracy rate of PD signal has also been improved to a certain extent,which proves that the method has a certain practicability.展开更多
An automatic 3D wiring method for switchgear design is proposed in this paper. First, wiring constraints are created, and a corresponding evaluation model is proposed. Then, based on the structure of the cabinet, we p...An automatic 3D wiring method for switchgear design is proposed in this paper. First, wiring constraints are created, and a corresponding evaluation model is proposed. Then, based on the structure of the cabinet, we propose a contour expansion scheme to construct rough paths. Different wiring features of the switchgear are used to connect rough local paths. All the paths are represented in a uniform data structure and forma path network. Finally, an improved A* algorithm is used to search the wiring path between the components in the routing network; the evaluation model is considered as heuristic rules for path searching. The result can satisfy the practical requirements of switchgear design. Experimental results are also provided.展开更多
A new approach is developed to inspect the internal pressure within the vacuum switchgear by no means of magnet-exciting coil, micro-discharge threshold voltage Ud and field emission threshold voltage Ud all of which ...A new approach is developed to inspect the internal pressure within the vacuum switchgear by no means of magnet-exciting coil, micro-discharge threshold voltage Ud and field emission threshold voltage Ud all of which are available in laboratory. Experimental results show that internal pressure is a function of the ratio of the micro-discharge threshold voltage to the field emission threshold voltage i.e., Ud/Ue. By this method, the internal pressure in the range of 10^0-10^-4 Pa within vacuum chambers can be inspected without magnet-exciting coil which is required in conventional magnetron discharge method.展开更多
This paper develops a novel distributed temperature measurement system based on DSP and DS18B20 digital thermometer. The real-time temperature of each node in the switchgear is obtained by several DS18B20s which are c...This paper develops a novel distributed temperature measurement system based on DSP and DS18B20 digital thermometer. The real-time temperature of each node in the switchgear is obtained by several DS18B20s which are connected on the 1-wire bus together. RS-485 master-slave communication protocol is used to centralize monitoring temperatures of several switchgear cabinets. The system also has the function of temperature alarm. The operation of simulation experiment has showed that the system is able to complete monitoring real-time temperatures in high voltage switchgear.展开更多
We present a temperature monitoring and warning system, which is based on wireless communi- cation technology and applied in train switchgear in this paper. The system is consists of three parts, including wireless te...We present a temperature monitoring and warning system, which is based on wireless communi- cation technology and applied in train switchgear in this paper. The system is consists of three parts, including wireless temperature detection module, inter-vehicle transmission networks module and?remote monitoring server. The switchgear contact temperature data are collected via the wireless temperature detection module and exchanged in inter-vehicle wireless networking by Zigbee modules. Then the temperature of train switchgear cabinets can be monitored remotely through the GPRS wireless communication.展开更多
In view of the switch partial discharge detection work, ultra-high frequency is undoubtedly the best detection method among many detection methods. The detection method has the characteristics of high sensitivity and ...In view of the switch partial discharge detection work, ultra-high frequency is undoubtedly the best detection method among many detection methods. The detection method has the characteristics of high sensitivity and strong anti-interference. Aiming at several kinds of problems that often occur in switch cabinets, after scientific design, four partial discharge models including sharp point, sharp plate, air gap and edge surface are made, and an ultra-high frequency partial discharge detection platform is built here. Aiming at the work of parameter extraction, it is usually carried out by using the traditional statistical method, and then the fault problems are analyzed through the PSO-SVM algorithm. At the same time, it is also necessary to concatenate the statistical and video domain feature vectors, and then carry out the data extraction work. Finally, it is carrying out the comparison work with the BP neural network fault diagnosis algorithm. According to the results after comparison, PSO-SVM algorithm has better recognition rate, which can reach 98.5% at most. It provides a good reference value for future work.展开更多
This paper discusses a preferable solution to mitigate the CT （current transformer） saturation problem, and at same time, reduce the accuracy errors when considering the selection of CTs for installation on the medi...This paper discusses a preferable solution to mitigate the CT （current transformer） saturation problem, and at same time, reduce the accuracy errors when considering the selection of CTs for installation on the medium voltage switchgear of a nuclear power plant. This consideration is important for both measurement and protection functions of the digital protective relays. This is a study to ascertain the best options for a suitable solution to prevent CT saturation in relations to its protective capabilities during short circuit fault without compromising the CT accuracy class during normal operation of the system, while ensuring its conformity to the design requirement is within limit. The advantages of current transformers have proven not only to be reliable and safe, but also are of easy handling, reduction of the cost and components on the MV （medium voltage） switchgear. The purpose of this research is to identify best approach to resolve the existing problems in the current protection system. With the view of LPCT （low power current transformer） which has been newly constructed by few manufacturers to provide good protection and a wide range of measuring function without errors, some other solutions will be considered in this research.展开更多
Medium voltage switchgear is widely used in distribution network. It plays the role of power distribution, measurement, control and protection circuit in residents, factories and public service facilities. However, du...Medium voltage switchgear is widely used in distribution network. It plays the role of power distribution, measurement, control and protection circuit in residents, factories and public service facilities. However, due to the high standard and complexity of the structural design of the medium voltage switchgear, some product defects will lead to a certain short circuit fault of the medium voltage switchgear. This paper analyzes the short-circuit fault of medium voltage switchgear, introduces the research on arc extinguishing technology of medium voltage switchgear, and puts forward corresponding preventive countermeasures, which is helpful to reduce the short-circuit fault of medium voltage switchgear in power grid.展开更多
Within 30 min after live operation of gas-insulated switchgear(GIS),more than 60%of discharge failures are caused by metallic particles.To address this issue,this study explored the vibration propagation mechanisms in...Within 30 min after live operation of gas-insulated switchgear(GIS),more than 60%of discharge failures are caused by metallic particles.To address this issue,this study explored the vibration propagation mechanisms in GIS cavities and established an equivalent vibration transmission model.A kinetic energy transfer conservation model between the cavity and particles was constructed,systematically analyzing the critical factors affecting the particle starting field strength and explicitly formulating the criterion for vibration-induced particle activation.The electric field distortion caused by particle rotation was investigated,and a collision dynamics model characterizing rotational mo-tion was developed.By analyzing the critical conditions for stable and rotational motion,the corresponding criterion was derived.The results showed that the electric field distortion caused by flaky particles increases with the rotation angle.Vibration effectively activates particles and enhances their mobility.The discharge risk is positively correlated with vibration intensity and particle thickness,but negatively correlated with particle size.This paper clarifies the motion mechanism of flaky metal particles in GIS under shock vibration,providing support for solving the problem of frequent faults after GIS live operation.展开更多
Gas-insulated switchgear(GIS)plays a critical role in ensuring the reliability of power systems,but partial discharge(PD)is a primary cause of failures within GIS equipment.Traditional PD diagnostic methods rely heavi...Gas-insulated switchgear(GIS)plays a critical role in ensuring the reliability of power systems,but partial discharge(PD)is a primary cause of failures within GIS equipment.Traditional PD diagnostic methods rely heavily on laboratory data,which differ signifi-cantly from that under the complex conditions of field data,leading to a marked drop in recognition accuracy when they are applied to field PD diagnosis.This study addresses the challenge by integrating field data into the training process,utilising a deep transfer learning approach that combines laboratory and field data to improve diagnostic accuracy for GIS PD.The research collected PD data from laboratory models representing five defect types and field data gathered from operational GIS equipment.A deep residual network(ResNet50)was pretrained using laboratory data and fine-tuned with field data through deep transfer learning to optimise the recognition of PD in field conditions.The results show that the proposed model achieves a significantly higher recognition accuracy(93.7%)for field data compared to traditional methods(60%-70%).The integration of deep transfer learning ensures that both low-dimensional general features from labora-tory data and high-dimensional specific features from field data are effectively utilised.This research significantly contributes to improving the diagnostic accuracy of PD in GIS under field conditions,providing a robust method for defect detection in operational equipment.展开更多
In the electric power equipment industry,various insulating materials and accessories are manufactured using petroleum-based epoxy resins.However,petrochemical resources are gradually becoming limited.In addition,the ...In the electric power equipment industry,various insulating materials and accessories are manufactured using petroleum-based epoxy resins.However,petrochemical resources are gradually becoming limited.In addition,the global surge in plastic usage has consistently raised concerns regarding greenhouse gas emissions,leading to worsening global warming.Therefore,to facilitate eco-friendly policies,industrialising epoxy systems applicable to high-pressure components using bio-based epoxy composites is essential.The results of the characterisation conducted in this research regarding bio-content were confirmed through thermogravimetric analysis and differential scanning calorimetry,which showed that as the bio-content increased,the thermal stability improved.Considering the operating temperature of 105℃ for the insulation spacer,structurally,no issues would be encountered if the spacer was manufactured with a bio-content of 20%(bio 20%).Subsequent tensile and flexural strength measurements revealed mechanical properties equivalent to or better than those of their petroleum-based counterparts.The impact strength tended to decrease with increasing bio-content.Analysing the dielectric properties confirmed that the epoxy composite containing 20%biomaterial is suitable for manufacturing insulation spacers.Subsequently,a series of tests conducted after spacer fabrication confirmed the absence of internal metals and bubbles with no external discolouration or cracks observed.展开更多
Accurately identifying the location and type of internal defects in gas-insulated switchgear(GIS)is a challenge.To address this challenge,this study proposes a novel method for the nondestructive detection of GIS inte...Accurately identifying the location and type of internal defects in gas-insulated switchgear(GIS)is a challenge.To address this challenge,this study proposes a novel method for the nondestructive detection of GIS internal defects.This method is based on x-ray digital radiography(X-DR)technology and an improved real-time models for object detection(RTMdet)algorithm,namely GIS-specific localised internal defect-RTMdet.Firstly,the X-DR images of GIS are preprocessed by dynamic limit adaptive histogram equalisation algorithm to improve the images contrast.Then,a convolution shuffle upsample module for upsampling is proposed,which enlarges the defect feature map by multi-convolution and pixel shuffling,reduces the information loss,and enhances the interaction between the feature information.Finally,both the multi-channel attention net and the global attention mechanism are integrated into the neck network for enhancing local feature extraction and global information association.Experiments demonstrate that the pro-posed method achieves a mean average precision@0.5:0.95 of 94.9%,showcasing excellent overall performance and generalisation ability,and is more suitable for accurate nondestructive detection of internal defects of GIS in complex scenarios.展开更多
Mechanical vibration defect is the key factor leading to sudden failure of gas-insulated switchgear(GIS)equipment.It is important to realise effective prediction of the me-chanical vibration state development trend of...Mechanical vibration defect is the key factor leading to sudden failure of gas-insulated switchgear(GIS)equipment.It is important to realise effective prediction of the me-chanical vibration state development trend of GIS equipment in order to improve its active safety protection level.This paper carried out research on the accurate prediction method and experimental validation of the mechanical vibration state and its defect severity development trend for the GIS equipment.Firstly,the deep and shallow vibration feature parameters for different mechanical defect signals were jointly extracted by time-domain features and deep belief network methods.Secondly,a new prediction model,incorporating the attention mechanism and the bidirectional gated recurrent unit(BiGRU),was constructed with the deep and shallow vibration feature parameters as inputs.Finally,the prediction trend effectiveness was verified based on the real-type GIS mechanical simulation platform and the field operation GIS equipment.Results show that the deep and shallow vibration feature extraction method proposed in this paper can characterise the mechanical defect information more comprehensively.The new prediction method of the vibration state trend based on the attention-BiGRU model shows ideal accuracy,and the predicted vibration state development trend is highly consistent with the actual,with an average absolute error of 0.063.The root mean square error(ERMSE)value of the prediction method is<5%,which reduces the relative error value at least 37% compared with the traditional prediction models.This paper provides a valuable reference for the proactive defence of GIS mechanical failure.展开更多
Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment.However,existing approaches face three significant limitations:(1)reliance on predefined ma...Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment.However,existing approaches face three significant limitations:(1)reliance on predefined mathematical models that often fail to capture equipment-specific degradation,(2)offline optimization methods that assume access to future data,and(3)the absence of component-level guidance.To address these challenges,we propose a data-driven framework for component-level decision-making.The framework leverages streaming sensor data to predict the remaining useful life(RUL)without relying on mathematical models,employs an online optimization algorithm suitable for practical settings,and,through remanufacturing simulations,provides guidance on which components should be replaced.In a case study on gas-insulated switchgear,the proposed framework achieved RUL prediction performance comparable to an oracle model in an online setting without relying on predefined mathematical models.Furthermore,by employing online optimization,it determined a remanufacturing timing close to the global optimum using only past and current data.In addition,unlike previous studies,the framework enables component-level decision-making,allowing for more detailed and actionable remanufacturing guidance in practical applications.展开更多
基金the financial support of National Natural Science Foundation of China(Nos.52207175 and 52407178)。
文摘When discharge faults occur in dry air switchgear,the air decomposes to produce diverse gases,with NO_(2) reaching the highest levels.Detecting the NO_(2) level can reflect the operation status of the equipment.This paper proposes to combine ZnO cluster with MoS_(2) to improve the gassensitive properties of the monolayer.Based on the Density Functional Theory(DFT),the effect of(ZnO)n size on the behavior of MoS_(2 )is considered.Key parameters such as adsorption energy and band gap of(ZnO)n-MoS_(2)/NO_(2) system were calculated.The ZnO-MoS_(2) heterojunction was successfully synthesized by a hydrothermal method.The gas sensor exhibits a remarkable response and a fast response-recovery time to 100 ppm NO_(2).In addition,it demonstrates excellent selectivity,long-term stability and a low detection limit.This work confirms the potential of the ZnO-MoS_(2) composite structure as a highly effective gas sensor for NO_(2) detection,which provides valuable theoretical and experimental insights for fault detection in dry air switchgear.
文摘Founded in 1919, Shanghai Hua Tong Switchgear Works ("HTSW" in short for below) is one of large enterprises on state level. With high and new technology, it is designed as an export base for mechanical and electrical product of the Ministry of Machinery Industry as well. It has been awarded the honor of first grade factory in the competition for key and major project construction in Shanghai year by year,
基金supported by the National Basic Research Program of China(973 Program) under grant 2011CB209405
文摘Transient enclosure voltage（TEV）,which is a phenomenon induced by the inner dielectric breakdown of SF_6 during disconnector operations in a gas-insulated switchgear（GIS）,may cause issues relating to shock hazard and electromagnetic interference to secondary equipment.This is a critical factor regarding the electromagnetic compatibility of ultra-high-voltage（UHV）substations.In this paper,the statistical characteristics of TEV at UHV level are collected from field experiments,and are analyzed and compared to those from a repeated strike process.The TEV waveforms during disconnector operations are recorded by a self-developed measurement system first.Then,statistical characteristics,such as the pulse number,duration of pulses,frequency components,magnitude and single pulse duration,are extracted.The transmission line theory is introduced to analyze the TEV and is validated by the experimental results.Finally,the relationship between the TEV and the repeated strike process is analyzed.This proves that the pulse voltage of the TEV is proportional to the corresponding breakdown voltage.The results contribute to the definition of the standard testing waveform of the TEV,and can aid the protection of electronic devices in substations by minimizing the threat of this phenomenon.
文摘Due to imperfect manufacturing technology, design defects and environmental impact, the failure rate of 10 kV switchgear is very high. For this reason, based on taken present situation of traditional switchgear and the current technical requirements for switchgear into account, a new reliable and safe modular high voltage switchgear design method is presented in this paper, which can reduce the failure rate of switchgear and improve the reliability of power supply. The electric field and temperature rise simulation model are established to check the reasonability and validity. By using the finite element software, the simulation results show that the design in this paper has a maximum temperature rise of 55 K for the main cabinet and a maximum temperature rise of 45 K for the deputy cabinet, which is far below the international standard of 70 K. The areas where the partial discharge is likely to occur within the switchgear are places such as the connection between bus-bar and cabinet, bus-bar joint and bus-bar corner. In order to avoid potential dangers, the discharge point must be located in time to prevent insulation fault of electrical equipment of the high voltage switchgear. The simulation results demonstrate that the design method in this paper greatly improve the reliability of switchgear and meets the demands of power system.
文摘Objective In order to find early latent faults and prevent catastrophic failures, diagnosis of insulation condition by measuring technique of partial discharge(PD) in gas insulated switchgear (GIS) is applied in this paper, which is one of the most basic ways for diagnosis of insulation condition. Methods Ultra high frequency(UHF) PD detection method by using internal sensors has been proved efficient, because it may avoid the disturbance of corona, but the sensor installation of this method will be limited by the structure and operation condition of GIS. There are some of electromagnetic (E-M) waves leak from the place of insulation spacer, therefore, the external sensors UHF measuring PD technique is applied, which isn't limited by the operation condition of GIS. Results This paper analyzes propagated electromagnetic (E-M) waves of partial discharge pulse excited by using the finite-difference time-domain (FDTD) method. The signal collected at the outer point is more complex than that of the inner point, and the signals' amplitude of outer is about half of the inner, because it propagates through spacer and insulation slot. Set up UHF PD measuring system. The typical PD in 252kV GIS bus bar was measured using PD detection UHF technique with external sensors. Finally, compare the results of UHF measuring technique using external sensors with the results of FDTD method simulation and the traditional IEC60270 method detection. Conclusion The results of experiment shows that the UHF technique can realize the diagnosis of insulation condition, the results of FDTD method simulation and the result UHF method detection can demonstrate each other, which gives references to further researches and application for UHF PD measuring technique.
基金Sponsored by the Liaoning Provincial Department of Education Scientific Research Funding Project(Youth)(Grant No.JDL2020020)the Changzhou City Applied Basic Research Program(Grant No.CJ2020007).
文摘Partial discharge(PD)is an important reason for the insulation failure of the switchgear.In the process of PD detection,PD signal is often annihilated in strong noise.In order to improve the accuracy of PD detection in power plant switchgear,a method based on continuous adaptive wavelet threshold switchgear PD signals denoising is proposed in this paper.By constructing a continuous adaptive threshold function and introducing adjustment parameters,the problems of over⁃processing of traditional hard threshold functions and incomplete denoising of soft threshold functions can be improved.The analysis results of simulated signals and measured signals show that the continuous adaptive wavelet threshold denoising method is significantly better than the traditional denoising method for the PD signal.The proposed method in this paper retains the characteristics of the original signal.Compared with the traditional denoising methods,after denoising the simulated signals,the signal⁃to⁃noise ratio(SNR)is increased by more than 30%,and the root⁃mean⁃square error(RMSE)is reduced by more than 30%.After denoising the real signal,the noise suppression ratio(NRR)is increased by more than 40%.The recognition accuracy rate of PD signal has also been improved to a certain extent,which proves that the method has a certain practicability.
基金Supported by National Key Technologies R&D Program of China(2015BAF23B03)National Nature Science Foundation of China(61672307)
文摘An automatic 3D wiring method for switchgear design is proposed in this paper. First, wiring constraints are created, and a corresponding evaluation model is proposed. Then, based on the structure of the cabinet, we propose a contour expansion scheme to construct rough paths. Different wiring features of the switchgear are used to connect rough local paths. All the paths are represented in a uniform data structure and forma path network. Finally, an improved A* algorithm is used to search the wiring path between the components in the routing network; the evaluation model is considered as heuristic rules for path searching. The result can satisfy the practical requirements of switchgear design. Experimental results are also provided.
基金the National Natural Science Foundation of China (No. 50377024)
文摘A new approach is developed to inspect the internal pressure within the vacuum switchgear by no means of magnet-exciting coil, micro-discharge threshold voltage Ud and field emission threshold voltage Ud all of which are available in laboratory. Experimental results show that internal pressure is a function of the ratio of the micro-discharge threshold voltage to the field emission threshold voltage i.e., Ud/Ue. By this method, the internal pressure in the range of 10^0-10^-4 Pa within vacuum chambers can be inspected without magnet-exciting coil which is required in conventional magnetron discharge method.
文摘This paper develops a novel distributed temperature measurement system based on DSP and DS18B20 digital thermometer. The real-time temperature of each node in the switchgear is obtained by several DS18B20s which are connected on the 1-wire bus together. RS-485 master-slave communication protocol is used to centralize monitoring temperatures of several switchgear cabinets. The system also has the function of temperature alarm. The operation of simulation experiment has showed that the system is able to complete monitoring real-time temperatures in high voltage switchgear.
文摘We present a temperature monitoring and warning system, which is based on wireless communi- cation technology and applied in train switchgear in this paper. The system is consists of three parts, including wireless temperature detection module, inter-vehicle transmission networks module and?remote monitoring server. The switchgear contact temperature data are collected via the wireless temperature detection module and exchanged in inter-vehicle wireless networking by Zigbee modules. Then the temperature of train switchgear cabinets can be monitored remotely through the GPRS wireless communication.
文摘In view of the switch partial discharge detection work, ultra-high frequency is undoubtedly the best detection method among many detection methods. The detection method has the characteristics of high sensitivity and strong anti-interference. Aiming at several kinds of problems that often occur in switch cabinets, after scientific design, four partial discharge models including sharp point, sharp plate, air gap and edge surface are made, and an ultra-high frequency partial discharge detection platform is built here. Aiming at the work of parameter extraction, it is usually carried out by using the traditional statistical method, and then the fault problems are analyzed through the PSO-SVM algorithm. At the same time, it is also necessary to concatenate the statistical and video domain feature vectors, and then carry out the data extraction work. Finally, it is carrying out the comparison work with the BP neural network fault diagnosis algorithm. According to the results after comparison, PSO-SVM algorithm has better recognition rate, which can reach 98.5% at most. It provides a good reference value for future work.
文摘This paper discusses a preferable solution to mitigate the CT （current transformer） saturation problem, and at same time, reduce the accuracy errors when considering the selection of CTs for installation on the medium voltage switchgear of a nuclear power plant. This consideration is important for both measurement and protection functions of the digital protective relays. This is a study to ascertain the best options for a suitable solution to prevent CT saturation in relations to its protective capabilities during short circuit fault without compromising the CT accuracy class during normal operation of the system, while ensuring its conformity to the design requirement is within limit. The advantages of current transformers have proven not only to be reliable and safe, but also are of easy handling, reduction of the cost and components on the MV （medium voltage） switchgear. The purpose of this research is to identify best approach to resolve the existing problems in the current protection system. With the view of LPCT （low power current transformer） which has been newly constructed by few manufacturers to provide good protection and a wide range of measuring function without errors, some other solutions will be considered in this research.
文摘Medium voltage switchgear is widely used in distribution network. It plays the role of power distribution, measurement, control and protection circuit in residents, factories and public service facilities. However, due to the high standard and complexity of the structural design of the medium voltage switchgear, some product defects will lead to a certain short circuit fault of the medium voltage switchgear. This paper analyzes the short-circuit fault of medium voltage switchgear, introduces the research on arc extinguishing technology of medium voltage switchgear, and puts forward corresponding preventive countermeasures, which is helpful to reduce the short-circuit fault of medium voltage switchgear in power grid.
基金National Natural Science Foundation of China,Grant/Award Number:52177140Fundamental Research Funds for the Central Universities,Grant/Award Number:2023JC005The State Grid Corporation of China Limited Science and Technology Program,Grant/Award Number:5200-202355792A-3-8-KJ。
文摘Within 30 min after live operation of gas-insulated switchgear(GIS),more than 60%of discharge failures are caused by metallic particles.To address this issue,this study explored the vibration propagation mechanisms in GIS cavities and established an equivalent vibration transmission model.A kinetic energy transfer conservation model between the cavity and particles was constructed,systematically analyzing the critical factors affecting the particle starting field strength and explicitly formulating the criterion for vibration-induced particle activation.The electric field distortion caused by particle rotation was investigated,and a collision dynamics model characterizing rotational mo-tion was developed.By analyzing the critical conditions for stable and rotational motion,the corresponding criterion was derived.The results showed that the electric field distortion caused by flaky particles increases with the rotation angle.Vibration effectively activates particles and enhances their mobility.The discharge risk is positively correlated with vibration intensity and particle thickness,but negatively correlated with particle size.This paper clarifies the motion mechanism of flaky metal particles in GIS under shock vibration,providing support for solving the problem of frequent faults after GIS live operation.
基金Key Program of Joint Funds of the National Natural Science Foundation of China,Grant/Award Number:U22B20118。
文摘Gas-insulated switchgear(GIS)plays a critical role in ensuring the reliability of power systems,but partial discharge(PD)is a primary cause of failures within GIS equipment.Traditional PD diagnostic methods rely heavily on laboratory data,which differ signifi-cantly from that under the complex conditions of field data,leading to a marked drop in recognition accuracy when they are applied to field PD diagnosis.This study addresses the challenge by integrating field data into the training process,utilising a deep transfer learning approach that combines laboratory and field data to improve diagnostic accuracy for GIS PD.The research collected PD data from laboratory models representing five defect types and field data gathered from operational GIS equipment.A deep residual network(ResNet50)was pretrained using laboratory data and fine-tuned with field data through deep transfer learning to optimise the recognition of PD in field conditions.The results show that the proposed model achieves a significantly higher recognition accuracy(93.7%)for field data compared to traditional methods(60%-70%).The integration of deep transfer learning ensures that both low-dimensional general features from labora-tory data and high-dimensional specific features from field data are effectively utilised.This research significantly contributes to improving the diagnostic accuracy of PD in GIS under field conditions,providing a robust method for defect detection in operational equipment.
基金Technology Innovation Program,Grant/Award Number:20010965Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning,Grant/Award Number:RS-2023-00266248。
文摘In the electric power equipment industry,various insulating materials and accessories are manufactured using petroleum-based epoxy resins.However,petrochemical resources are gradually becoming limited.In addition,the global surge in plastic usage has consistently raised concerns regarding greenhouse gas emissions,leading to worsening global warming.Therefore,to facilitate eco-friendly policies,industrialising epoxy systems applicable to high-pressure components using bio-based epoxy composites is essential.The results of the characterisation conducted in this research regarding bio-content were confirmed through thermogravimetric analysis and differential scanning calorimetry,which showed that as the bio-content increased,the thermal stability improved.Considering the operating temperature of 105℃ for the insulation spacer,structurally,no issues would be encountered if the spacer was manufactured with a bio-content of 20%(bio 20%).Subsequent tensile and flexural strength measurements revealed mechanical properties equivalent to or better than those of their petroleum-based counterparts.The impact strength tended to decrease with increasing bio-content.Analysing the dielectric properties confirmed that the epoxy composite containing 20%biomaterial is suitable for manufacturing insulation spacers.Subsequently,a series of tests conducted after spacer fabrication confirmed the absence of internal metals and bubbles with no external discolouration or cracks observed.
基金National Engineering Research Center of UHV Technology and New Electrical Equipment Basis of China Southern Power Grid Research Institute Co.,Ltd,Grant/Award Number:NERCUTNEEB-2022-KF-08。
文摘Accurately identifying the location and type of internal defects in gas-insulated switchgear(GIS)is a challenge.To address this challenge,this study proposes a novel method for the nondestructive detection of GIS internal defects.This method is based on x-ray digital radiography(X-DR)technology and an improved real-time models for object detection(RTMdet)algorithm,namely GIS-specific localised internal defect-RTMdet.Firstly,the X-DR images of GIS are preprocessed by dynamic limit adaptive histogram equalisation algorithm to improve the images contrast.Then,a convolution shuffle upsample module for upsampling is proposed,which enlarges the defect feature map by multi-convolution and pixel shuffling,reduces the information loss,and enhances the interaction between the feature information.Finally,both the multi-channel attention net and the global attention mechanism are integrated into the neck network for enhancing local feature extraction and global information association.Experiments demonstrate that the pro-posed method achieves a mean average precision@0.5:0.95 of 94.9%,showcasing excellent overall performance and generalisation ability,and is more suitable for accurate nondestructive detection of internal defects of GIS in complex scenarios.
基金National Key R&D Program of China,Grant/Award Numbers:2022YFB2403700,2022YFB2403705Natural Science Foundation of Chongqing,Grant/Award Number:CSTB2022NSCQ-MSX1247。
文摘Mechanical vibration defect is the key factor leading to sudden failure of gas-insulated switchgear(GIS)equipment.It is important to realise effective prediction of the me-chanical vibration state development trend of GIS equipment in order to improve its active safety protection level.This paper carried out research on the accurate prediction method and experimental validation of the mechanical vibration state and its defect severity development trend for the GIS equipment.Firstly,the deep and shallow vibration feature parameters for different mechanical defect signals were jointly extracted by time-domain features and deep belief network methods.Secondly,a new prediction model,incorporating the attention mechanism and the bidirectional gated recurrent unit(BiGRU),was constructed with the deep and shallow vibration feature parameters as inputs.Finally,the prediction trend effectiveness was verified based on the real-type GIS mechanical simulation platform and the field operation GIS equipment.Results show that the deep and shallow vibration feature extraction method proposed in this paper can characterise the mechanical defect information more comprehensively.The new prediction method of the vibration state trend based on the attention-BiGRU model shows ideal accuracy,and the predicted vibration state development trend is highly consistent with the actual,with an average absolute error of 0.063.The root mean square error(ERMSE)value of the prediction method is<5%,which reduces the relative error value at least 37% compared with the traditional prediction models.This paper provides a valuable reference for the proactive defence of GIS mechanical failure.
基金supported by the Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant funded by the Korea government Ministry of Knowledge Economy(No.RS-2023-00244330)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF RS-2023-00219052RS-2024-00352587)。
文摘Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment.However,existing approaches face three significant limitations:(1)reliance on predefined mathematical models that often fail to capture equipment-specific degradation,(2)offline optimization methods that assume access to future data,and(3)the absence of component-level guidance.To address these challenges,we propose a data-driven framework for component-level decision-making.The framework leverages streaming sensor data to predict the remaining useful life(RUL)without relying on mathematical models,employs an online optimization algorithm suitable for practical settings,and,through remanufacturing simulations,provides guidance on which components should be replaced.In a case study on gas-insulated switchgear,the proposed framework achieved RUL prediction performance comparable to an oracle model in an online setting without relying on predefined mathematical models.Furthermore,by employing online optimization,it determined a remanufacturing timing close to the global optimum using only past and current data.In addition,unlike previous studies,the framework enables component-level decision-making,allowing for more detailed and actionable remanufacturing guidance in practical applications.
