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1.
This paper presents the stability improvement results of hybrid doubly fed induction generator (DFIG)-based and permanent magnet generator (PMG)-based offshore wind farms (OWFs) using a static synchronous series compensator (SSSC). An adaptive-network-based fuzzy inference system (ANFIS) controller of the proposed SSSC is designed to render adequate damping characteristics to the studied system. A frequency-domain approach based on a linearized system model using eigenvalue technique analysis is performed. A time-domain scheme based on a nonlinear system model subject to a three-phase short circuit fault at infinite bus with variations in the signal transmission delays has also been investigated to compare the damping of the studied system in cases of with and without controller. The simulation results with MATLAB/SIMULINK toolbox have been presented. It can be concluded from the simulation results that the proposed SSSC joined with the designed ANFIS damping controller can offer adequate damping performance to the studied hybrid DFIG-based and PMG-based OWFs under severe disturbance. 相似文献
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This paper presents an analytical solution to the non-uniform pressure on thick-walled cylinder. The formulation is based on the linear elasticity theory (plain strain) and stress function method. As an example, the proposed solution is used to model the stress distribution due to non-uniform steel reinforcement corrosion in concrete. The model is formulated considering different scenarios of corrosion pressure distribution. It is validated against the finite element model for different cases of non-uniform pressure distributions. The results show that the corrosion-induced cracks are likely to start just beyond the anodic zone. This is confirmed by the experimental tests on concrete cylinder exposed to non-uniform accelerated corrosion of steel reinforcement. The model can be effectively used to calculate the distribution of corrosion-induced stresses in concrete. 相似文献
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Today’s information technologies involve increasingly intelligent systems, which come at the cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring-point and long-term data which make equipment health prediction a “big data” problem. It is difficult to extract information from such condition monitoring data to accurately estimate or predict health statuses. Deep learning is a powerful tool for big data processing that is widely utilized in image and speech recognition applications, and can also provide effective predictions in industrial processes. This paper proposes the Long Short-term Memory Integrating Principal Component Analysis based on Human Experience (HEPCA-LSTM), which uses operational time-series data for equipment health prognostics. Principal component analysis based on human experience is first conducted to extract condition parameters from the condition monitoring system. The long short-term memory (LSTM) framework is then constructed to predict the target status. Finally, a dynamic update of the prediction model with incoming data is performed at a certain interval to prevent any model misalignment caused by the drifting of relevant variables. The proposed model is validated on a practical case and found to outperform other prediction methods. It utilizes a powerful deep learning analysis method, the LSTM, to fully process big condition monitoring series data; it effectively extracts the features involved with human experience and takes dynamic updates into consideration. 相似文献
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Interactions between financial time series are complex and changeable in both time and frequency domains. To reveal the evolution characteristics of the time-varying relations between bivariate time series from a multi-resolution perspective, this study introduces an approach combining wavelet analysis and complex networks. In addition, to reduce the influence the phase lag between the time series has on the correlations, we propose dynamic time-warping (DTW) correlation coefficients to reflect the correlation degree between bivariate time series. Unlike previous studies that symbolized the time series only based on the correlation strength, the second-level symbol is set according to the correlation length during the coarse-graining process. This study presents a novel method to analyze bivariate time series and provides more information for investors and decision makers when investing in the stock market. We choose the closing prices of two stocks in China’s market as the sample and explore the evolutionary behavior of correlation modes from different resolutions. Furthermore, we perform experiments to discover the critical correlation modes between the bull market and the bear market on the high-resolution scale, the clustering effect during the financial crisis on the middle-resolution scale, and the potential pseudo period on the low-resolution scale. The experimental results exactly match reality, which provides powerful evidence to prove that our method is effective in financial time series analysis. 相似文献
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目标RCS动态数据的分布特征研究 总被引:1,自引:0,他引:1
复杂目标在不同视向的RCS分布特征是不同的,传统模型对此都没有给出详细的结果。文中以某歼击机和直升机为对象,应用X^2。分布、对数正态分布和瑞利分布模型,以及Kolmogomv拟合优度检验方法,研究其RCS动态测量数据的统计分布特征,得到了在一定显著性水平下,两种目标在不同视向角下对三种模型的拟合效果,同时得到应用X^2。分布拟合时模型半自由度随视向角的分布情况。在显著性水平为0.05时,对于在较短时间内录得的复杂目标动态RCS数据,应用X^2分布可以取得较好的拟合效果。文中结果精确地描述了目标RCS的起伏特征,能够为目标回波的精确模拟与检测提供可靠的依据。 相似文献
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指出了由VG7S变频器拖动的电梯系统运转停止时序分析中的几个主要问题,探讨了使用中的抗干扰技术,并对常用控制端子的设定方法和部分调试要点作了较为详尽的说明。 相似文献
10.
This letter investigates the scattering characteristic of the rivets on aircraft.The electric Field Integral Equation (EFIE)is used with the moment to calculate the current distribution on the surface of the rivet.With the application of Gaussian integral corresponding triangular cell,the time to fill the Z matrix is greatly reduced.Finally,the RCS of a type of rivet on aircraft is analyzed. 相似文献