A new algorithm was developed to correctly identify fault conditions and accurately monitor fault development in a mine hoist. The new method is based on the Wavelet Packet Transform (WPT) and kernel PCA (Kernel Princ...A new algorithm was developed to correctly identify fault conditions and accurately monitor fault development in a mine hoist. The new method is based on the Wavelet Packet Transform (WPT) and kernel PCA (Kernel Principal Compo- nent Analysis, KPCA). For non-linear monitoring systems the key to fault detection is the extracting of main features. The wavelet packet transform is a novel technique of signal processing that possesses excellent characteristics of time-frequency localization. It is suitable for analysing time-varying or transient signals. KPCA maps the original input features into a higher dimension feature space through a non-linear mapping. The principal components are then found in the higher dimen- sion feature space. The KPCA transformation was applied to extracting the main nonlinear features from experimental fault feature data after wavelet packet transformation. The results show that the proposed method affords credible fault detection and identification.展开更多
A condition monitoring method of deep-hole drilling based on multi-sensor information fusion is discussed. The signal of vibration and cutting force are collected when the condition of deep-hole drilling on stainless ...A condition monitoring method of deep-hole drilling based on multi-sensor information fusion is discussed. The signal of vibration and cutting force are collected when the condition of deep-hole drilling on stainless steel 0Cr17Ni4Cu4Nb is normal or abnormal. Four eigenvectors are extracted on time-domain and frequency-domain analysis of the signals. Then the four eigenvectors are combined and sent to neural networks to dispose. The fusion results indicate that multi-sensor information fusion is superior to single-sensor information, and that cutting force signal can reflect the condition of cutting tool better than vibration signal.展开更多
Medium voltage distribution networks usually suffer from single-ground arcing fault,especially high impedance arcing fault.Moreover,induced intermittent arcing faults can severely endanger the reliability and safety o...Medium voltage distribution networks usually suffer from single-ground arcing fault,especially high impedance arcing fault.Moreover,induced intermittent arcing faults can severely endanger the reliability and safety of power systems.The arc model is important for high impedance arcing fault suppression and detection to effectively eliminate the single-ground arcing fault.This paper proposes an improved arc model,which is concise and explicit,based on a single-ground arcing fault conducted on a 10 kV experimental platform under different fault conditions.Characteristic parameters of single-ground arcing faults are obtained based on test results.Furthermore,characteristic parameters under different fault conditions of the improved arc model are presented.Finally,verification of the improved arc model is supported by PSCAD-EMTDC.Comparisons of the proposed arc model between three typical black-box arc models indicate that the proposed model has better performance and higher accuracy than that of the three typical arc models as fault resistance is in a range of 0.1 kΩto 2.4 kΩ.Thus,its accuracy is acceptable and it is helpful to the simulation and suppression of arc fault overvoltage.展开更多
针对模块化多电平统一电能质量调节器(modular multilevel unified power quality conditioner, MMC-UPQC)六桥臂结构下的单相桥臂故障问题,提出了一种五桥臂拓扑,这种新型拓扑可实现故障情况下的电能质量补偿。首先,对MMC-UPQC串并联...针对模块化多电平统一电能质量调节器(modular multilevel unified power quality conditioner, MMC-UPQC)六桥臂结构下的单相桥臂故障问题,提出了一种五桥臂拓扑,这种新型拓扑可实现故障情况下的电能质量补偿。首先,对MMC-UPQC串并联侧的数学模型进行分析,提出了一种复合模型预测控制(hybrid model predictive control,H-MPC),所提控制方法结合了有限集模型预测控制(finite-control-set model predictive control, FCS-MPC)以及快速模型预测控制(fast model predictive control, F-MPC)。然后,通过构建两侧独立的价值函数减少了控制方法的计算量,同时也实现了五桥臂解耦控制。最后,相比传统线性(例如PI)和非线性(例如无源控制passivity-based control,PBC)的控制策略,所提复合模型预测控制在电压补偿、负序电压抑制以及谐波电流补偿等方面具有一定优势,并在一定程度上避免了复杂的参数整定及坐标变化环节。仿真实验结果证明了所提控制方法的可行性和优越性。展开更多
针对容错模式下的统一电能质量调节器(Unified Power Quality Conditioner,UPQC),提出了一种五桥臂形式的新型拓扑结构,实现故障下的电能质量扰动综合补偿。在此基础上,对串联变流器和并联变流器进行统一建模,提出了一种基于有限集模型...针对容错模式下的统一电能质量调节器(Unified Power Quality Conditioner,UPQC),提出了一种五桥臂形式的新型拓扑结构,实现故障下的电能质量扰动综合补偿。在此基础上,对串联变流器和并联变流器进行统一建模,提出了一种基于有限集模型预测控制(Finite Control Set Model Predictive Control,FCS-MPC)的五桥臂UPQC控制策略。相比传统线性控制策略,所提算法构建了统一的预测模型以及整合优化的价值函数,实现串联变流器与并联变流器的协同控制,提高了两侧变流器的补偿精度、暂态性能以及响应速度,有效降低了控制算法的复杂度和参数调节难度,并具有较高的参数鲁棒性。仿真结果验证了所提算法的可行性和有效性。展开更多
基金Projects 50674086 supported by the National Natural Science Foundation of ChinaBS2006002 by the Society Development Science and Technology Planof Jiangsu Province20060290508 by the Doctoral Foundation of Ministry of Education of China
文摘A new algorithm was developed to correctly identify fault conditions and accurately monitor fault development in a mine hoist. The new method is based on the Wavelet Packet Transform (WPT) and kernel PCA (Kernel Principal Compo- nent Analysis, KPCA). For non-linear monitoring systems the key to fault detection is the extracting of main features. The wavelet packet transform is a novel technique of signal processing that possesses excellent characteristics of time-frequency localization. It is suitable for analysing time-varying or transient signals. KPCA maps the original input features into a higher dimension feature space through a non-linear mapping. The principal components are then found in the higher dimen- sion feature space. The KPCA transformation was applied to extracting the main nonlinear features from experimental fault feature data after wavelet packet transformation. The results show that the proposed method affords credible fault detection and identification.
文摘A condition monitoring method of deep-hole drilling based on multi-sensor information fusion is discussed. The signal of vibration and cutting force are collected when the condition of deep-hole drilling on stainless steel 0Cr17Ni4Cu4Nb is normal or abnormal. Four eigenvectors are extracted on time-domain and frequency-domain analysis of the signals. Then the four eigenvectors are combined and sent to neural networks to dispose. The fusion results indicate that multi-sensor information fusion is superior to single-sensor information, and that cutting force signal can reflect the condition of cutting tool better than vibration signal.
基金supported by National Natural Science Foundation of China under Grant No.51477018 and No.52077019。
文摘Medium voltage distribution networks usually suffer from single-ground arcing fault,especially high impedance arcing fault.Moreover,induced intermittent arcing faults can severely endanger the reliability and safety of power systems.The arc model is important for high impedance arcing fault suppression and detection to effectively eliminate the single-ground arcing fault.This paper proposes an improved arc model,which is concise and explicit,based on a single-ground arcing fault conducted on a 10 kV experimental platform under different fault conditions.Characteristic parameters of single-ground arcing faults are obtained based on test results.Furthermore,characteristic parameters under different fault conditions of the improved arc model are presented.Finally,verification of the improved arc model is supported by PSCAD-EMTDC.Comparisons of the proposed arc model between three typical black-box arc models indicate that the proposed model has better performance and higher accuracy than that of the three typical arc models as fault resistance is in a range of 0.1 kΩto 2.4 kΩ.Thus,its accuracy is acceptable and it is helpful to the simulation and suppression of arc fault overvoltage.
文摘针对模块化多电平统一电能质量调节器(modular multilevel unified power quality conditioner, MMC-UPQC)六桥臂结构下的单相桥臂故障问题,提出了一种五桥臂拓扑,这种新型拓扑可实现故障情况下的电能质量补偿。首先,对MMC-UPQC串并联侧的数学模型进行分析,提出了一种复合模型预测控制(hybrid model predictive control,H-MPC),所提控制方法结合了有限集模型预测控制(finite-control-set model predictive control, FCS-MPC)以及快速模型预测控制(fast model predictive control, F-MPC)。然后,通过构建两侧独立的价值函数减少了控制方法的计算量,同时也实现了五桥臂解耦控制。最后,相比传统线性(例如PI)和非线性(例如无源控制passivity-based control,PBC)的控制策略,所提复合模型预测控制在电压补偿、负序电压抑制以及谐波电流补偿等方面具有一定优势,并在一定程度上避免了复杂的参数整定及坐标变化环节。仿真实验结果证明了所提控制方法的可行性和优越性。
文摘针对容错模式下的统一电能质量调节器(Unified Power Quality Conditioner,UPQC),提出了一种五桥臂形式的新型拓扑结构,实现故障下的电能质量扰动综合补偿。在此基础上,对串联变流器和并联变流器进行统一建模,提出了一种基于有限集模型预测控制(Finite Control Set Model Predictive Control,FCS-MPC)的五桥臂UPQC控制策略。相比传统线性控制策略,所提算法构建了统一的预测模型以及整合优化的价值函数,实现串联变流器与并联变流器的协同控制,提高了两侧变流器的补偿精度、暂态性能以及响应速度,有效降低了控制算法的复杂度和参数调节难度,并具有较高的参数鲁棒性。仿真结果验证了所提算法的可行性和有效性。
