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Shanghai, China

Xie Y.,Shanghai Dianji University | Feng Y.,Nanjing University of Science and Technology | Qiu Y.,Nanjing University of Science and Technology
Renewable Energy | Year: 2013

Wind energy has been identified in China as an important alternative energy source to balance its energy mix. By the end of 2012, wind power (2%) has surpassed nuclear power to become China's 3rd largest energy resource of electricity, only behind thermal power and hydropower. The rapid growth of China wind power industry in recent years has made China become the biggest market in the world. Meanwhile, it has created a big market for educational institutions to provide wind energy related education and training. The main objective of this study is to review current wind energy education and training in Chinese universities and training centers. Most of wind energy courses are provided by public universities because they have been accredited by Ministry of Education of China to offer students different options, including full-time and part-time degrees in Bachelor, Master or Ph.D. On-the-job training also has tremendous demand from the professionals who prefer short-term courses or on-site courses. Generally, the development of wind energy education and training lags behind the growth of wind power industry. Our study highlights the major opportunities and future challenges in China wind energy education and training. © 2013 Elsevier Ltd. Source


Liu W.,Shanghai Dianji University
ICALIP 2012 - 2012 International Conference on Audio, Language and Image Processing, Proceedings | Year: 2012

The time delay estimation is an active research topic in the field of signal processing. Aiming on signals are on the low SNR conditions, a novel adaptive time delay estimation method is presented by using the fractional low order statistics. First, the signal noise ratio is improved via computing the fractional low order cross-covariation between two received signals and the fractional low order auto-covariation of a received signal. Second, they are put into two adaptive filters. The difference between peak locations of two filter weight efficiencies indicates the relative time delay between two received signals when they are convergent under least mean square criteria. Computer simulation studies show that the estimation performance of the proposed method is good, especially under heavier impulsive noise or lower signal noise ratio. © 2012 IEEE. Source


Wu B.,Shanghai Dianji University | Yu J.-b.,Shanghai University
Expert Systems with Applications | Year: 2010

In this paper, a neural network-based identification model is proposed for both mean and variance shifts in correlated processes. The proposed model uses a selective network ensemble approach named DPSOEN to obtain the improved generalization performance, which outperforms those of single neural network. The model is capable of on-line monitoring mean and variance shifts, and classifying the types of shifts without considering the occurrence of both mean and variance shifts in one time. This model is unique since all learning-based methods developed so far can only detect mean or variance shift, but are incapable of classifying types of shifts. The result is significant since it provides additional useful information about the process changes, which can greatly aid identification of assignable causes. The simulation results demonstrate that the model outperforms the conventional control charts in terms of average run length (ARL), and can classify the types of shifts in a real-mode. © 2009 Elsevier Ltd. All rights reserved. Source


Sun Z.,Shanghai Dianji University
Journal of the Korean Physical Society | Year: 2015

Lag projective synchronization (LPS) of chaotic systems with different fractional orders is investigated. A scheme of LPS is designed based on the stability of fractional nonlinear systems. LPS between two four-scroll hyperchaotic systems with different fractional orders is realized by using the scheme and is simulated by using a multi-step fractional differential transform method. All the theoretical analysis and simulation results show the effectiveness of the proposed controller. The work in this paper may accelerate the application of fractional-order chaotic systems in practice. © 2015, The Korean Physical Society. Source


Xie Y.,Shanghai Dianji University
Applied Mechanics and Materials | Year: 2014

China has great potential in offshore wind energy and makes an ambitious target for offshore wind power development. Operation and Maintenance (O&M) of offshore wind turbines become more and more important for China wind industry. This study introduces the current offshore wind power projects in China. Donghai Bridge Offshore Demonstration Wind Farm (Donghai Bridge Project) is the first commercial offshore wind power project in China, which was connected to grid in June 2010. O&M of Donghai Bridge Project represent the state-of-the-art of China offshore O&M. During the past two and half years, O&M of Donghai Bridge Project has gone through three phases and stepped into a steady stage. It's believed that analysis of O&M of Donghai Bridge Project is very helpful for China's offshore wind power in the future. © (2014) Trans Tech Publications, Switzerland. Source

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