In order to provide a novel and more effective alternative to the commonly used relay protection testing device that outputs only the sinusoidal testing signals, the concept of fault waveform regenerator is proposed i...In order to provide a novel and more effective alternative to the commonly used relay protection testing device that outputs only the sinusoidal testing signals, the concept of fault waveform regenerator is proposed in this paper, together with its hardware structure and software flow chart. Fault waveform regenerator mainly depends on its power amplifiers (PAs) to regenerate the fault waveforms recorded by digital fault recorder (DFR). To counteract the PA’s inherent nonlinear distortions, a digital closed-loop modification technique that is different from the predistortion technique is conceived. And the experimental results verify the effectiveness of the fault waveform regenerator based on the digital closed-loop modification technique.展开更多
Vibration intensity and non-dimensional amplitude parameters are often used to extract the fault trend of rotary machines. But,they are the parameters related to energy,and can not describe the fault trend because of ...Vibration intensity and non-dimensional amplitude parameters are often used to extract the fault trend of rotary machines. But,they are the parameters related to energy,and can not describe the fault trend because of varying load and conditions or too slight change of vibration signal. For this reason,three non-dimensional parameters are presented,namely waveform repeatability factor,waveform jumping factor and waveform similarity factor,called as waveform factors jointly,which are based on statistics analysis for the waveform and sensitive to the change of signal waveform. When they are used to extract the fault trend of rotary machines as a kind of technology of instrument and meter,they can reflect the fault trend better than the vibration intensity,peak amplitude and margin index.展开更多
The accurate fault-cause identification for overhead transmission lines supports the operation and maintenance personnel in formulating targeted maintenance strategies and shortening the time of inspecting faulty line...The accurate fault-cause identification for overhead transmission lines supports the operation and maintenance personnel in formulating targeted maintenance strategies and shortening the time of inspecting faulty lines.With the goal of achieving“carbon peak and carbon neutrality”,the schemes for clean energy generation have rapidly developed.Moreover,new energy-consuming equipment has been widely connected to the power grid,and the operating characteristics of the power system have significantly changed.Consequently,these have impacted traditional fault identification methods.Based on the time-frequency characteristics of the fault waveform,new energy-related parameters,and deep learning model,this study proposes a fault identification method suitable for scenarios where a high proportion of new energy is connected to the power grid.Ten parameters related to the causes of transmission line fault and new energy connection scenarios are selected as model characteristic parameters.Further,a fault identification model based on adaptive deep belief networks was constructed,and its effect was verified by field data.展开更多
文摘In order to provide a novel and more effective alternative to the commonly used relay protection testing device that outputs only the sinusoidal testing signals, the concept of fault waveform regenerator is proposed in this paper, together with its hardware structure and software flow chart. Fault waveform regenerator mainly depends on its power amplifiers (PAs) to regenerate the fault waveforms recorded by digital fault recorder (DFR). To counteract the PA’s inherent nonlinear distortions, a digital closed-loop modification technique that is different from the predistortion technique is conceived. And the experimental results verify the effectiveness of the fault waveform regenerator based on the digital closed-loop modification technique.
文摘Vibration intensity and non-dimensional amplitude parameters are often used to extract the fault trend of rotary machines. But,they are the parameters related to energy,and can not describe the fault trend because of varying load and conditions or too slight change of vibration signal. For this reason,three non-dimensional parameters are presented,namely waveform repeatability factor,waveform jumping factor and waveform similarity factor,called as waveform factors jointly,which are based on statistics analysis for the waveform and sensitive to the change of signal waveform. When they are used to extract the fault trend of rotary machines as a kind of technology of instrument and meter,they can reflect the fault trend better than the vibration intensity,peak amplitude and margin index.
基金This work was supported by State Grid Science and Technology Project(B3440821K003).
文摘The accurate fault-cause identification for overhead transmission lines supports the operation and maintenance personnel in formulating targeted maintenance strategies and shortening the time of inspecting faulty lines.With the goal of achieving“carbon peak and carbon neutrality”,the schemes for clean energy generation have rapidly developed.Moreover,new energy-consuming equipment has been widely connected to the power grid,and the operating characteristics of the power system have significantly changed.Consequently,these have impacted traditional fault identification methods.Based on the time-frequency characteristics of the fault waveform,new energy-related parameters,and deep learning model,this study proposes a fault identification method suitable for scenarios where a high proportion of new energy is connected to the power grid.Ten parameters related to the causes of transmission line fault and new energy connection scenarios are selected as model characteristic parameters.Further,a fault identification model based on adaptive deep belief networks was constructed,and its effect was verified by field data.
