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
Large property contrasts between materials in a fault zone and the surrounding rock are often produced by repeating earthquakes. Fault zones are usually characterized by fluid concentration, clay-rich fault gouge, inc...Large property contrasts between materials in a fault zone and the surrounding rock are often produced by repeating earthquakes. Fault zones are usually characterized by fluid concentration, clay-rich fault gouge, increased porosity, and dilatant cracks. Thus, fault zones are thought to have reduced seismic velocities than the surrounding rocks. In this article, we first investigated the synthetic waveforms at a linear array across a vertical fault zone by using 3D finite difference simulation. Synthetic waveforms show that when sources are close to, inside, or below the fault zone, both arrival times and waveforms of P-and S-waves vary systematically across the fault zone due to reflections and transmissions from boundaries of the low-velocity fault zone. The arrival-time patterns and waveform characteristics can be used to determine the fault zone structure. Then, we applied this method to the aftershock waveform data of the 1992 Landers M7.4 and the 2008 Wenchuan （汶川） M8.0 earthquakes. Landers waveform data reveal a low-velocity zone with a width of approximately 270-370 m, and P-and S-wave velocity reductions relative to the host rock of approximately 35%-60%; Wenchuan waveform data suggest a low-velocity zone with a width of approximately 220-300 m, and P-and S-wave velocities drop relative to the host rock of approximately 55%.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
由于柔性多状态开关(soft normal open point,SNOP)复杂的控制策略及其弱馈特性,传统配电网故障定位方法难以适用于柔性互联配电网(flexible distribution network,FDN)。因此,文中提出一种利用电流正序分量波形相似性进行FDN故障区段...由于柔性多状态开关(soft normal open point,SNOP)复杂的控制策略及其弱馈特性,传统配电网故障定位方法难以适用于柔性互联配电网(flexible distribution network,FDN)。因此,文中提出一种利用电流正序分量波形相似性进行FDN故障区段定位的方法。首先,针对SNOP的典型控制策略,分析FDN的短路故障特征。其次,计算配电网中不同故障位置电流正序分量的Tanimoto系数,通过对比不同位置的电流正序分量波形相似性,构建FDN短路故障定位判据,并通过Teager能量算子(Teager energy operation,TEO)实现故障时刻的精确定位,利用智能配电终端(smart terminal unit,STU)传递信息。最后,通过建模仿真对所提方法进行分析验证,结果表明该方法能够对故障区段进行准确定位,不受故障位置、故障类型、过渡电阻、采样频率及通信延时等因素的影响,验证了该方法的可行性与有效性。展开更多
Multiple faults are easily confused with single faults.In order to identify multiple faults more accurately,a highly efficient learning method is proposed based on a double parallel two-hidden-layer extreme learning m...Multiple faults are easily confused with single faults.In order to identify multiple faults more accurately,a highly efficient learning method is proposed based on a double parallel two-hidden-layer extreme learning machine,called DPTELM.The DPT-ELM method is a variant of an extreme learning machine(ELM).There are some issues with ELM.First,achieving a high accuracy requires too many hidden nodes;second,the direct connection between the input layer and the output layer is ignored.Accordingly,to deal with the above-mentioned problems,DPT-ELM extends the single-hidden-layer ELM to a two-hidden-layer ELM,which can achieve a desired performance with fewer hidden nodes.In addition,a direct connection is built between the input layer and the output layer.Since the input layer weights and the thresholds of the two hidden layers are determined randomly,this simplifies the improved model and shortens the calculation time.Additionally,to improve the signal to noise ratio(SNR),an adaptive waveform decomposition(AWD)algorithm is used to denoise the vibration signal.Then,the denoised signal is used to extract the eigenvalues by the time-domain and frequency-domain methods.Finally,the eigenvalues are input to the DPT-ELM classifier.In this paper,two groups of rolling bearing data at different speeds,which were collected from a real experimental platform,are used to test the method.Each set of data includes three single fault states,two complex fault states and a healthy state.The experimental results demonstrate that the DPT-ELM method achieves fast learning speed and a high accuracy.Moreover,based on 10-fold cross-validation,it proves to be an effective method to improve the accuracy with fewer hidden nodes.展开更多
中压配电网中的部分瞬时故障在发展为永久故障之前可能会多次发生,而准确辨识这类重复发生的瞬时故障有助于实现故障预警、减少永久性故障的发生并且提高供电可靠性。通过建立瞬时故障的暂态等值电路并对其故障电流进行分析,表明重复性...中压配电网中的部分瞬时故障在发展为永久故障之前可能会多次发生,而准确辨识这类重复发生的瞬时故障有助于实现故障预警、减少永久性故障的发生并且提高供电可靠性。通过建立瞬时故障的暂态等值电路并对其故障电流进行分析,表明重复性瞬时故障在发展为永久性故障的过程中,故障电流具有强相似性。文中提出了一种基于零序电流波形相似度的重复性瞬时故障辨识方法。采用改进动态时间规划(dynamic time warping,DTW)算法计算零序电流的近似波形和暂态波形序列间的距离。而后通过DTW距离获得波形相似度,实现重复性瞬时故障的辨识。通过大量PSCAD/EMTDC仿真数据以及现场实测数据,验证了所提辨识算法在多种影响因素下的准确性和有效性。展开更多
针对长距离输电行波波头精确标定困难、行波波速难以准确选取等问题,提出了一种基于虚拟故障波形匹配的行波网络定位方法。首先分析行波在输电网络中的传播特性,对传播过程各环节建立等效模型。利用改进的深度优先搜索(depth first sear...针对长距离输电行波波头精确标定困难、行波波速难以准确选取等问题,提出了一种基于虚拟故障波形匹配的行波网络定位方法。首先分析行波在输电网络中的传播特性,对传播过程各环节建立等效模型。利用改进的深度优先搜索(depth first search,DFS)算法,实现任意故障位置到测量点行波传播路径搜索。进而根据路径信息构建行波传播模型。结合动态虚拟故障思路,利用行波传播模型模拟各测量点虚拟故障行波波形。最后提出虚拟故障与真实故障行波波形自适应匹配方法,构造行波波形匹配率来衡量虚拟故障与真实故障位置的差异性。通过PSCAD仿真平台验证,该方法无需标定初始波头到达时间,降低了波速误差,实现了故障精确定位。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supported by the Open Fund of the Key Labo-ratory of Geo-detection (China University of Geosciences, Bei-jing),Ministry of Education (No. GDL0708)
文摘Large property contrasts between materials in a fault zone and the surrounding rock are often produced by repeating earthquakes. Fault zones are usually characterized by fluid concentration, clay-rich fault gouge, increased porosity, and dilatant cracks. Thus, fault zones are thought to have reduced seismic velocities than the surrounding rocks. In this article, we first investigated the synthetic waveforms at a linear array across a vertical fault zone by using 3D finite difference simulation. Synthetic waveforms show that when sources are close to, inside, or below the fault zone, both arrival times and waveforms of P-and S-waves vary systematically across the fault zone due to reflections and transmissions from boundaries of the low-velocity fault zone. The arrival-time patterns and waveform characteristics can be used to determine the fault zone structure. Then, we applied this method to the aftershock waveform data of the 1992 Landers M7.4 and the 2008 Wenchuan （汶川） M8.0 earthquakes. Landers waveform data reveal a low-velocity zone with a width of approximately 270-370 m, and P-and S-wave velocity reductions relative to the host rock of approximately 35%-60%; Wenchuan waveform data suggest a low-velocity zone with a width of approximately 220-300 m, and P-and S-wave velocities drop relative to the host rock of approximately 55%.
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.
文摘由于柔性多状态开关(soft normal open point,SNOP)复杂的控制策略及其弱馈特性,传统配电网故障定位方法难以适用于柔性互联配电网(flexible distribution network,FDN)。因此,文中提出一种利用电流正序分量波形相似性进行FDN故障区段定位的方法。首先,针对SNOP的典型控制策略,分析FDN的短路故障特征。其次,计算配电网中不同故障位置电流正序分量的Tanimoto系数,通过对比不同位置的电流正序分量波形相似性,构建FDN短路故障定位判据,并通过Teager能量算子(Teager energy operation,TEO)实现故障时刻的精确定位,利用智能配电终端(smart terminal unit,STU)传递信息。最后,通过建模仿真对所提方法进行分析验证,结果表明该方法能够对故障区段进行准确定位,不受故障位置、故障类型、过渡电阻、采样频率及通信延时等因素的影响,验证了该方法的可行性与有效性。
基金supported by National Natural Science Foundation of China(51675035/51375037)
文摘Multiple faults are easily confused with single faults.In order to identify multiple faults more accurately,a highly efficient learning method is proposed based on a double parallel two-hidden-layer extreme learning machine,called DPTELM.The DPT-ELM method is a variant of an extreme learning machine(ELM).There are some issues with ELM.First,achieving a high accuracy requires too many hidden nodes;second,the direct connection between the input layer and the output layer is ignored.Accordingly,to deal with the above-mentioned problems,DPT-ELM extends the single-hidden-layer ELM to a two-hidden-layer ELM,which can achieve a desired performance with fewer hidden nodes.In addition,a direct connection is built between the input layer and the output layer.Since the input layer weights and the thresholds of the two hidden layers are determined randomly,this simplifies the improved model and shortens the calculation time.Additionally,to improve the signal to noise ratio(SNR),an adaptive waveform decomposition(AWD)algorithm is used to denoise the vibration signal.Then,the denoised signal is used to extract the eigenvalues by the time-domain and frequency-domain methods.Finally,the eigenvalues are input to the DPT-ELM classifier.In this paper,two groups of rolling bearing data at different speeds,which were collected from a real experimental platform,are used to test the method.Each set of data includes three single fault states,two complex fault states and a healthy state.The experimental results demonstrate that the DPT-ELM method achieves fast learning speed and a high accuracy.Moreover,based on 10-fold cross-validation,it proves to be an effective method to improve the accuracy with fewer hidden nodes.
文摘中压配电网中的部分瞬时故障在发展为永久故障之前可能会多次发生,而准确辨识这类重复发生的瞬时故障有助于实现故障预警、减少永久性故障的发生并且提高供电可靠性。通过建立瞬时故障的暂态等值电路并对其故障电流进行分析,表明重复性瞬时故障在发展为永久性故障的过程中,故障电流具有强相似性。文中提出了一种基于零序电流波形相似度的重复性瞬时故障辨识方法。采用改进动态时间规划(dynamic time warping,DTW)算法计算零序电流的近似波形和暂态波形序列间的距离。而后通过DTW距离获得波形相似度,实现重复性瞬时故障的辨识。通过大量PSCAD/EMTDC仿真数据以及现场实测数据,验证了所提辨识算法在多种影响因素下的准确性和有效性。
文摘针对长距离输电行波波头精确标定困难、行波波速难以准确选取等问题,提出了一种基于虚拟故障波形匹配的行波网络定位方法。首先分析行波在输电网络中的传播特性,对传播过程各环节建立等效模型。利用改进的深度优先搜索(depth first search,DFS)算法,实现任意故障位置到测量点行波传播路径搜索。进而根据路径信息构建行波传播模型。结合动态虚拟故障思路,利用行波传播模型模拟各测量点虚拟故障行波波形。最后提出虚拟故障与真实故障行波波形自适应匹配方法,构造行波波形匹配率来衡量虚拟故障与真实故障位置的差异性。通过PSCAD仿真平台验证,该方法无需标定初始波头到达时间,降低了波速误差,实现了故障精确定位。
