The Experts below are selected from a list of 9732 Experts worldwide ranked by ideXlab platform
Masayuki Hikita - One of the best experts on this subject based on the ideXlab platform.
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consideration of generation mechanism of low frequency component of partial discharge signal detected by transient Earth Voltage
2018Co-Authors: Hiromasa Yoshizumi, Masahiro Kozako, Masayuki Hikita, Yuuki Fujii, Yusuke Nakamura, Yusuke Nakano, Hiroaki ChoAbstract:Transient Earth Voltage (TEV) detection method is drawing attention for its readiness to be installed just on the outer wall of existing equipment, and is useful for partial discharge (PD) detection. The purpose of this research is to establish reliable insulation diagnosis technique of high Voltage equipment based on partial discharge detection using TEV method. Our previous study showed that TEV sensor dominantly detects high (several 100 MHz) and low frequency (several 10 MHz) components attributed to the electromagnetic wave propagating through space and discharge current flowing through the ground line, respectively. To investigate a mechanism of generated low frequency components further, this paper deals with the effect of the length of PD measurement circuit on the low frequency component detected by TEV sensor by experiments and simulation of electromagnetic wave propagation using finite difference time domain (FDTD) method. As a result, it was found that the low frequency component includes two different kinds of dominant resonance frequencies determined by assuming the measurement circuit to act as a lumped constant electric circuit and as an antenna such as dipole antenna and loop antenna.
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classification of partial discharge sources using waveform parameters and phase resolved partial discharge pattern as input for the artificial neural network
2018Co-Authors: Taufik Rossal Sukma, Masahiro Kozako, Masayuki Hikita, Umar Khayam, Ryouya Sugawara, Hina Yoshikawa, Osamu Eda, Masanori Otsuka, Hiroshi Kaneko, Yasuharu ShiinaAbstract:Partial discharge (PD) is one of electrical phenomena which might occur in high Voltage (HV) equipment and can be used for diagnosing the condition of the equipment. Artificial neural network (ANN) is then utilized to classify PD source in HV equipment. PD measurements were conducted to generate waveform parameters in laboratory using four kinds of artificial PD sources, three kinds of noise sources by three kinds of sensors (transient Earth Voltage (TEV) sensor, surface current sensor (SCS) and high frequency current transformer (HFCT)). Nine waveform parameters from one PD event were used for training and testing the ANN (ANN_ WP). For further comparison, phase-resolved partial discharge (PRPD) pattern was also generated and used as input data for training and testing the other ANN (ANN_PR). Results reveal that ANN_ WP provides >96% of recognition rate while ANN_PR gives >90% of recognition rate. Furthermore, the ANNs are then tested using new different artificial void defect. The results show that the ANN_ WP predicted new PD data as void defect with 92 % probability while the ANN_PR prediction probability was found 96%. These results indicate that the waveform parameters can be used as an input data for ANN as well as PRPD pattern to provide sufficient accuracy for identifying the PD source. The results suggest a possibility that developed ANNs can be used as a decision-support tool in HV equipment diagnosis by comparing PD data obtained in the field.
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grounding effect on transient Earth Voltage signal induced by partial discharge in metal box model
2017Co-Authors: Hiromasa Yoshizumi, Takaaki Koga, Masahiro Kozako, Masayuki Hikita, Yuuki Fujii, Yusuke Nakamura, Hiroaki ChoAbstract:This paper deals with advancement of insulation diagnosis technology for high Voltage equipment by partial discharge (PD) detection using transient Earth Voltage (TEV) detection method. Our previous study showed that detected TEV signal contains both high-frequency and low-frequency components around 500 MHz and 30 MHz, respectively. To further investigate the principle of detecting the low frequency components, this paper presents experiment and finite difference time domain analysis of TEV signal propagation. Results revealed that the signal intensity detected by TEV sensor with grounding is about five to six times as much as that without the grounding. Furthermore, when grounded, the low frequency components tend to be strongly detected. In other words, it is suggested that PD current including the low frequency component is induced on the surface of the metal box via the ground line, and this component greatly influences the TEV detection intensity.
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partial discharge detection and induced surface current analysis using transient Earth Voltage method for high Voltage equipment
2016Co-Authors: Akihiko Itose, Masahiro Kozako, Masayuki HikitaAbstract:This study deals with advancement of insulation diagnosis technology by partial discharge (PD) detection with transient Earth Voltage (TEV) signal in high Voltage equipment such as oil-filled transformer. TEV detection method allows to detect signals by attaching TEV sensors to the outer wall of the existing facilities. Experiment and analysis of TEV signal propagation using finite-difference time-domain (FDTD) method are carried out for an iron box model which simulates a tank of an actual transformer. Results revealed that TEV signal caused by PD dominantly consists of two kinds of frequency components; i.e. high-frequency component of 500 MHz and low-frequency one of 30 MHz. Namely, the high frequency component of TEV signal propagates from the aperture of the bushing, while the low-frequency component flows through the ground line. Furthermore, it was found that the high-frequency component contained in the TEV signal is attributed to the resonant frequency determined by the size of the metal tank. As a result, if the magnitude and the frequency band of detected TEV signal are known, it is possible to determine where the discharge source is located inside or outside of the metal tank.
Ricardo Albarracin - One of the best experts on this subject based on the ideXlab platform.
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partial discharge monitoring on metal enclosed switchgear with distributed non contact sensors
2018Co-Authors: Chongxing Zhang, Ming Ren, Wenguang Huang, Jierui Zhou, Xuze Gao, Ming Dong, Ricardo AlbarracinAbstract:Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient Earth Voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium Voltage switchgear and improving its operation and maintenance level.
Masahiro Kozako - One of the best experts on this subject based on the ideXlab platform.
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consideration of generation mechanism of low frequency component of partial discharge signal detected by transient Earth Voltage
2018Co-Authors: Hiromasa Yoshizumi, Masahiro Kozako, Masayuki Hikita, Yuuki Fujii, Yusuke Nakamura, Yusuke Nakano, Hiroaki ChoAbstract:Transient Earth Voltage (TEV) detection method is drawing attention for its readiness to be installed just on the outer wall of existing equipment, and is useful for partial discharge (PD) detection. The purpose of this research is to establish reliable insulation diagnosis technique of high Voltage equipment based on partial discharge detection using TEV method. Our previous study showed that TEV sensor dominantly detects high (several 100 MHz) and low frequency (several 10 MHz) components attributed to the electromagnetic wave propagating through space and discharge current flowing through the ground line, respectively. To investigate a mechanism of generated low frequency components further, this paper deals with the effect of the length of PD measurement circuit on the low frequency component detected by TEV sensor by experiments and simulation of electromagnetic wave propagation using finite difference time domain (FDTD) method. As a result, it was found that the low frequency component includes two different kinds of dominant resonance frequencies determined by assuming the measurement circuit to act as a lumped constant electric circuit and as an antenna such as dipole antenna and loop antenna.
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classification of partial discharge sources using waveform parameters and phase resolved partial discharge pattern as input for the artificial neural network
2018Co-Authors: Taufik Rossal Sukma, Masahiro Kozako, Masayuki Hikita, Umar Khayam, Ryouya Sugawara, Hina Yoshikawa, Osamu Eda, Masanori Otsuka, Hiroshi Kaneko, Yasuharu ShiinaAbstract:Partial discharge (PD) is one of electrical phenomena which might occur in high Voltage (HV) equipment and can be used for diagnosing the condition of the equipment. Artificial neural network (ANN) is then utilized to classify PD source in HV equipment. PD measurements were conducted to generate waveform parameters in laboratory using four kinds of artificial PD sources, three kinds of noise sources by three kinds of sensors (transient Earth Voltage (TEV) sensor, surface current sensor (SCS) and high frequency current transformer (HFCT)). Nine waveform parameters from one PD event were used for training and testing the ANN (ANN_ WP). For further comparison, phase-resolved partial discharge (PRPD) pattern was also generated and used as input data for training and testing the other ANN (ANN_PR). Results reveal that ANN_ WP provides >96% of recognition rate while ANN_PR gives >90% of recognition rate. Furthermore, the ANNs are then tested using new different artificial void defect. The results show that the ANN_ WP predicted new PD data as void defect with 92 % probability while the ANN_PR prediction probability was found 96%. These results indicate that the waveform parameters can be used as an input data for ANN as well as PRPD pattern to provide sufficient accuracy for identifying the PD source. The results suggest a possibility that developed ANNs can be used as a decision-support tool in HV equipment diagnosis by comparing PD data obtained in the field.
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grounding effect on transient Earth Voltage signal induced by partial discharge in metal box model
2017Co-Authors: Hiromasa Yoshizumi, Takaaki Koga, Masahiro Kozako, Masayuki Hikita, Yuuki Fujii, Yusuke Nakamura, Hiroaki ChoAbstract:This paper deals with advancement of insulation diagnosis technology for high Voltage equipment by partial discharge (PD) detection using transient Earth Voltage (TEV) detection method. Our previous study showed that detected TEV signal contains both high-frequency and low-frequency components around 500 MHz and 30 MHz, respectively. To further investigate the principle of detecting the low frequency components, this paper presents experiment and finite difference time domain analysis of TEV signal propagation. Results revealed that the signal intensity detected by TEV sensor with grounding is about five to six times as much as that without the grounding. Furthermore, when grounded, the low frequency components tend to be strongly detected. In other words, it is suggested that PD current including the low frequency component is induced on the surface of the metal box via the ground line, and this component greatly influences the TEV detection intensity.
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partial discharge detection and induced surface current analysis using transient Earth Voltage method for high Voltage equipment
2016Co-Authors: Akihiko Itose, Masahiro Kozako, Masayuki HikitaAbstract:This study deals with advancement of insulation diagnosis technology by partial discharge (PD) detection with transient Earth Voltage (TEV) signal in high Voltage equipment such as oil-filled transformer. TEV detection method allows to detect signals by attaching TEV sensors to the outer wall of the existing facilities. Experiment and analysis of TEV signal propagation using finite-difference time-domain (FDTD) method are carried out for an iron box model which simulates a tank of an actual transformer. Results revealed that TEV signal caused by PD dominantly consists of two kinds of frequency components; i.e. high-frequency component of 500 MHz and low-frequency one of 30 MHz. Namely, the high frequency component of TEV signal propagates from the aperture of the bushing, while the low-frequency component flows through the ground line. Furthermore, it was found that the high-frequency component contained in the TEV signal is attributed to the resonant frequency determined by the size of the metal tank. As a result, if the magnitude and the frequency band of detected TEV signal are known, it is possible to determine where the discharge source is located inside or outside of the metal tank.
Ming Ren - One of the best experts on this subject based on the ideXlab platform.
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partial discharge monitoring on metal enclosed switchgear with distributed non contact sensors
2018Co-Authors: Chongxing Zhang, Ming Ren, Wenguang Huang, Jierui Zhou, Xuze Gao, Ming Dong, Ricardo AlbarracinAbstract:Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient Earth Voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium Voltage switchgear and improving its operation and maintenance level.
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transient Earth Voltage measurement in pd detection of artificial defect models in hbox sf _ 6
2012Co-Authors: Ming Ren, Ming Dong, Zhong Ren, Huadong Peng, Aici QiuAbstract:This paper mainly discussed the utilization of transient Earth Voltage measurement (TEVM) in partial discharge (PD) detection of gas insulation switchgear. Four typical artificial defect models in SF6 such as spikes fixed on high Voltage (HV) conductor, suspended metals, voids in dielectric, and metal particles on the surface of dielectric had been used as test objects in ac PD experiments with the aid of the synchronized PD signals sampled from a transient Earth Voltage sensor, photomultiplier, Rogowski monitor, and PDCheck system. The measuring results of TEVM results, which included the phase distribution of PD, the relative amplitude, and the pulse number of different Voltage thresholds, showed good consistency with three other methods and had better sensitivity of detection in spark or corona PD patterns. For further study, the frequency distributions of the three PD patterns were analyzed and discussed for understanding the different measurement sensitivities showed in different typical defects in SF6 . In addition, TEVM was applied to detect PD under oscillating impulse Voltage. As an example, the needle-plane electrode with short gap was adopted under 613.2-kHz oscillating impulse, which showed the effectiveness in this kind of detection.
Ming Dong - One of the best experts on this subject based on the ideXlab platform.
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partial discharge monitoring on metal enclosed switchgear with distributed non contact sensors
2018Co-Authors: Chongxing Zhang, Ming Ren, Wenguang Huang, Jierui Zhou, Xuze Gao, Ming Dong, Ricardo AlbarracinAbstract:Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient Earth Voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium Voltage switchgear and improving its operation and maintenance level.
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transient Earth Voltage measurement in pd detection of artificial defect models in hbox sf _ 6
2012Co-Authors: Ming Ren, Ming Dong, Zhong Ren, Huadong Peng, Aici QiuAbstract:This paper mainly discussed the utilization of transient Earth Voltage measurement (TEVM) in partial discharge (PD) detection of gas insulation switchgear. Four typical artificial defect models in SF6 such as spikes fixed on high Voltage (HV) conductor, suspended metals, voids in dielectric, and metal particles on the surface of dielectric had been used as test objects in ac PD experiments with the aid of the synchronized PD signals sampled from a transient Earth Voltage sensor, photomultiplier, Rogowski monitor, and PDCheck system. The measuring results of TEVM results, which included the phase distribution of PD, the relative amplitude, and the pulse number of different Voltage thresholds, showed good consistency with three other methods and had better sensitivity of detection in spark or corona PD patterns. For further study, the frequency distributions of the three PD patterns were analyzed and discussed for understanding the different measurement sensitivities showed in different typical defects in SF6 . In addition, TEVM was applied to detect PD under oscillating impulse Voltage. As an example, the needle-plane electrode with short gap was adopted under 613.2-kHz oscillating impulse, which showed the effectiveness in this kind of detection.
