To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue cr...To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.展开更多
In this paper, a hybrid approach was developed to investigate the transient responses of a multi span non uniform flexible spinning shaft with nonlinear and asymmetric supports. The non uniform spinning shaft with ...In this paper, a hybrid approach was developed to investigate the transient responses of a multi span non uniform flexible spinning shaft with nonlinear and asymmetric supports. The non uniform spinning shaft with variable parameters was modeled as a Bernoulli Euler beam column with sectional constant cross section properties by the finite element method. The supporting stiffness behavior of the nonlinear supports was described as a piecewise linear and asymmetric model. The equations of motion in the matrix form of a multi span non uniform spinning shaft with nonlinear and asymmetric supports were formulated using Hamilton's principle and the assumed mode method. As an example, a spinning rocket with many variable stiffness supports was numerically simulated by the direct integration method. The transient response and dynamic behavior of this rotate dynamic system are analyzed.展开更多
当电网出现有功缺额并导致频率跌落时,风电机组可以通过释放自身轴系动能为电网提供短时频率支撑(short-term frequency support,STFS)。如何利用有限的风电机组轴系动能最大限度地支撑电网频率,是当前研究的热点问题。针对风电机组可...当电网出现有功缺额并导致频率跌落时,风电机组可以通过释放自身轴系动能为电网提供短时频率支撑(short-term frequency support,STFS)。如何利用有限的风电机组轴系动能最大限度地支撑电网频率,是当前研究的热点问题。针对风电机组可释放动能和电网频率变化率约束下的电网最大频率偏差最小化问题,该文提出一种基于有功功率互补控制(active-power complementation control,ACC)的风电机组STFS策略,揭示STFS过程中风电机组的最小动能释放机理,并证明采用ACC释放全部轴系动能的STFS策略为上述问题的最优解。最后,基于含风电的电网动模实验平台的实验结果验证该文提出STFS策略的可行性与频率支撑效果。展开更多
基金This project is supported by National Natural Science Fundation of China (No. 50675066)Provincial Key Technologies R&D of Hunan, China (No. 05FJ2001)China Postdoctoral Science Foundation (No. 2005038006).
文摘To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.
文摘In this paper, a hybrid approach was developed to investigate the transient responses of a multi span non uniform flexible spinning shaft with nonlinear and asymmetric supports. The non uniform spinning shaft with variable parameters was modeled as a Bernoulli Euler beam column with sectional constant cross section properties by the finite element method. The supporting stiffness behavior of the nonlinear supports was described as a piecewise linear and asymmetric model. The equations of motion in the matrix form of a multi span non uniform spinning shaft with nonlinear and asymmetric supports were formulated using Hamilton's principle and the assumed mode method. As an example, a spinning rocket with many variable stiffness supports was numerically simulated by the direct integration method. The transient response and dynamic behavior of this rotate dynamic system are analyzed.
文摘当电网出现有功缺额并导致频率跌落时,风电机组可以通过释放自身轴系动能为电网提供短时频率支撑(short-term frequency support,STFS)。如何利用有限的风电机组轴系动能最大限度地支撑电网频率,是当前研究的热点问题。针对风电机组可释放动能和电网频率变化率约束下的电网最大频率偏差最小化问题,该文提出一种基于有功功率互补控制(active-power complementation control,ACC)的风电机组STFS策略,揭示STFS过程中风电机组的最小动能释放机理,并证明采用ACC释放全部轴系动能的STFS策略为上述问题的最优解。最后,基于含风电的电网动模实验平台的实验结果验证该文提出STFS策略的可行性与频率支撑效果。
