Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This pa...Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This paper proposes a novel fault line detection method using waveform fusion and one-dimensional convolutional neural networks(1-D CNN).After an SLG fault occurs,the first-half waves of zero-sequence currents are collected and superimposed with each other to achieve waveform fusion.The compelling feature of fused waveforms is extracted by 1-D CNN to determine whether the fused waveform source contains the fault line.Then,the 1-D CNN output is used to update the value of the counter in order to identify the fault line.Given the lack of fault data in existing distribution systems,the proposed method only needs a small quantity of data for model training and fault line detection.In addition,the proposed method owns fault-tolerant performance.Even if a few samples are misjudged,the fault line can still be detected correctly based on the full output results of 1-D CNN.Experimental results verified that the proposed method can work effectively under various fault conditions.展开更多
In resonant grounding systems,most single-phaseto-ground faults evolve from IAFs(Intermittent Arc Faults).Earlier detection of IAFs can facilitate fault avoidance.This work proposes a novel method based on machine lea...In resonant grounding systems,most single-phaseto-ground faults evolve from IAFs(Intermittent Arc Faults).Earlier detection of IAFs can facilitate fault avoidance.This work proposes a novel method based on machine learning for detecting IAFs in three steps.First,the feature of zero-sequence current is automatically extracted and selected by a newlydesigned FINET(“For IAFs,Neuron Elaboration Net”),instead of traditional feature selection based on time-frequency decomposition.Moreover,data of the zero-sequence current divided by different time windows are successively input into the trained FINET.A proposed PSF(principal-subordinate factor)analyses the results obtained from FINET to improve anti-interference in the mentioned IAF detection algorithm.Experiments using PSCAD/EMTDC software simulation data show the proposed method is feasible and highly adaptable.In addition,the detection result of on-site recorded data demonstrates the effectiveness of the proposed method in practical resonant grounding systems.展开更多
Vacuum well point is a new but faint soft ground treatment method. This work focuses on the consolidation behavior of a reconstituted soft clayey specimen under vacuum well point combined with surcharge loading. The l...Vacuum well point is a new but faint soft ground treatment method. This work focuses on the consolidation behavior of a reconstituted soft clayey specimen under vacuum well point combined with surcharge loading. The laboratory test was conducted through a vacuum-surcharge consolidation apparatus, and the vacuum loading scheme was adopted for vacuum pressure application to investigate the vacuum effect on soil consolidation. In the testing process, some key parameters such as vacuum pressure, pore water pressure and settlement deformation were timely recorded. Furthermore, the water content, void ratio and permeability coefficient of samples collected after loading were measured to reflect the consolidation characteristics. By comparing with the membrane system and membraneless system, something different was found for the vacuum well point method. The results indicate that the consolidation behavior of an axisymmetric single vacuum well point is almost identical to the behavior of vacuum preloading combined with prefabricated vertical drain(PVD), except for the distribution of the vacuum pressure along the well drain due to the structure of the vacuum well point. And the vacuum well point method may be useful for the improvement of soft clayey deposit in a certain depth.展开更多
Ground support systems are commonly used to mitigate the potential consequences of rockburst in burst prone mines.To assess the capacity of ground support systems when subjected to dynamic loading,simulated rockburst ...Ground support systems are commonly used to mitigate the potential consequences of rockburst in burst prone mines.To assess the capacity of ground support systems when subjected to dynamic loading,simulated rockburst tests using blasting were conducted at the Kiruna Mine.In this study,a numerical simulation for one of the field tests was conducted using the LS-DYNA code to investigate the dynamic response of the ground support systems including shotcrete and rockbolts.The numerical results showed a similar particle vibration pattern and a crack pattern to those of the field measurements.The effects of the detonator position and the charge configuration on the dynamic response of ground support systems are also discussed.Numerical results indicated that the peak particle vibrations on the tested panel increase along the direction of detonation propagation.It is difficult to use different charge concentrations in one borehole to investigate the effect of different dynamic loads on the dynamic response of support systems.Numerical results also indicated that 2D numerical modeling for simulated rockburst experiments could overestimate the dynamic response of ground support systems.展开更多
基金supported by the National Natural Science Foundation of China through the Project of Research of Flexible and Adaptive Arc-Suppression Method for Single-Phase Grounding Fault in Distribution Networks(No.51677030).
文摘Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This paper proposes a novel fault line detection method using waveform fusion and one-dimensional convolutional neural networks(1-D CNN).After an SLG fault occurs,the first-half waves of zero-sequence currents are collected and superimposed with each other to achieve waveform fusion.The compelling feature of fused waveforms is extracted by 1-D CNN to determine whether the fused waveform source contains the fault line.Then,the 1-D CNN output is used to update the value of the counter in order to identify the fault line.Given the lack of fault data in existing distribution systems,the proposed method only needs a small quantity of data for model training and fault line detection.In addition,the proposed method owns fault-tolerant performance.Even if a few samples are misjudged,the fault line can still be detected correctly based on the full output results of 1-D CNN.Experimental results verified that the proposed method can work effectively under various fault conditions.
基金sponsored by the National Natural Science Foundation of China (No.51677030).
文摘In resonant grounding systems,most single-phaseto-ground faults evolve from IAFs(Intermittent Arc Faults).Earlier detection of IAFs can facilitate fault avoidance.This work proposes a novel method based on machine learning for detecting IAFs in three steps.First,the feature of zero-sequence current is automatically extracted and selected by a newlydesigned FINET(“For IAFs,Neuron Elaboration Net”),instead of traditional feature selection based on time-frequency decomposition.Moreover,data of the zero-sequence current divided by different time windows are successively input into the trained FINET.A proposed PSF(principal-subordinate factor)analyses the results obtained from FINET to improve anti-interference in the mentioned IAF detection algorithm.Experiments using PSCAD/EMTDC software simulation data show the proposed method is feasible and highly adaptable.In addition,the detection result of on-site recorded data demonstrates the effectiveness of the proposed method in practical resonant grounding systems.
基金Projects(41202220,41472278)supported by the National Natural Science Foundation of ChinaProject(20120022120003)supported by the Research Fund for the Doctoral Program of Higher Education,ChinaProject(2652012065)supported by the Fundamental Research Funds for Central Universities,China
文摘Vacuum well point is a new but faint soft ground treatment method. This work focuses on the consolidation behavior of a reconstituted soft clayey specimen under vacuum well point combined with surcharge loading. The laboratory test was conducted through a vacuum-surcharge consolidation apparatus, and the vacuum loading scheme was adopted for vacuum pressure application to investigate the vacuum effect on soil consolidation. In the testing process, some key parameters such as vacuum pressure, pore water pressure and settlement deformation were timely recorded. Furthermore, the water content, void ratio and permeability coefficient of samples collected after loading were measured to reflect the consolidation characteristics. By comparing with the membrane system and membraneless system, something different was found for the vacuum well point method. The results indicate that the consolidation behavior of an axisymmetric single vacuum well point is almost identical to the behavior of vacuum preloading combined with prefabricated vertical drain(PVD), except for the distribution of the vacuum pressure along the well drain due to the structure of the vacuum well point. And the vacuum well point method may be useful for the improvement of soft clayey deposit in a certain depth.
基金supported by the Centre of Advanced Mining&Metallurgy(CAMM2)at Lulea University of Technologythe support from the project of SLIM funded by the European Union’s Horizon 2020 research and innovation program under grant agreement N°730294.
文摘Ground support systems are commonly used to mitigate the potential consequences of rockburst in burst prone mines.To assess the capacity of ground support systems when subjected to dynamic loading,simulated rockburst tests using blasting were conducted at the Kiruna Mine.In this study,a numerical simulation for one of the field tests was conducted using the LS-DYNA code to investigate the dynamic response of the ground support systems including shotcrete and rockbolts.The numerical results showed a similar particle vibration pattern and a crack pattern to those of the field measurements.The effects of the detonator position and the charge configuration on the dynamic response of ground support systems are also discussed.Numerical results indicated that the peak particle vibrations on the tested panel increase along the direction of detonation propagation.It is difficult to use different charge concentrations in one borehole to investigate the effect of different dynamic loads on the dynamic response of support systems.Numerical results also indicated that 2D numerical modeling for simulated rockburst experiments could overestimate the dynamic response of ground support systems.
