Shanghai, China

Time filter

Source Type

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.

Hui F.,Shanghai Dianji University
Advanced Materials Research | Year: 2011

Based the defects of global optimal model falling into local optimum easily and local model with slow convergence speed during traditional PSO algorithm solving a complex high-dimensional and multi-peak function, a two sub-swarms particle optimization algorithm is proposed. All particles are divided into two equivalent parts. One part particles adopts global evolution model, while the other part uses local evolution model. If the global optimal fitness of the whole population stagnates for some iteration, a golden rule is introduced into local evolution model. This strategy can substitute the partial perfect particles of local evolution for the equivalent worse particles of global evolution model. So, some particles with advantage are joined into the whole population to make the algorithm keep active all the time. Compared with classic PSO and PSO-GL(A dynamic global and local combined particle swarm optimization algorithm, PSO-GL), the results show that the proposed PSO in this paper can get more effective performance over the other two algorithm in the simulation experiment for four benchmark testing function. © (2011) Trans Tech Publications, Switzerland.

Sun Z.W.,Shanghai Dianji University
Indian Journal of Physics | Year: 2013

Function projective synchronization (FPS) of two novel hyperchaotic systems with four-scroll attractors, which have been found up to the present, is investigated. Adaptive control is employed in the situation that system parameters are unknown. Based on Lyapunov stability theory, an adaptive controller and a parameter update law are designed so that the two systems can be synchronized asymptotically by FPS. Numerical simulation is provided to show the effectiveness of the proposed adaptive controller and the parameter update law. © 2012 Indian Association for the Cultivation of Science.

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.

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.

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.

Liu W.,Shanghai Dianji University
2012 IEEE International Conference on Mechatronics and Automation, ICMA 2012 | Year: 2012

Aiming to impulsive noises and low signal-to-noise ratio environment, a novel robust time delay estimation approach (referred to as the SR-FLOC) is addressed. Based on stochastic resonance technique and the fractional lower order covariance, the SR-FLOC can detect the delay of narrow-band signals with impulsive noises. Signal-to-noise ratio of the reference and detected signals is improved via the SR effect between noisy signals and bistable nonlinear dynamical systems. The SR effect is realized by tuning system parameters to their op ti ma l values under the maximum symmetric covariation coefficient criterion. Then the fractional lower order covariance function between outputs of two SR systems is computed. The delay is estimated by obtaining the location of this fractional lower order covariance function peak. The performance of the SR-FLOC algorithm is verified through computer simulations by using sin signals. © 2012 IEEE.

Chen G.,Shanghai Dianji University
Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010 | Year: 2010

When basic particle swarm optimization algorithm (PSO) is used to resolve some complex problems, its global optimal model usually falls into local optimal value and its local model has slowest convergence velocity in the later stage of evolution. So, a simplified particle swarm optimization algorithm is proposed. Firstly, all particles in whole swarm are divided into three categories, denoted as the better particles, the ordinary particles and the worse particles according to their fitness. After the velocity equation of PSO is analyzed, the velocity part of PSO's iteration equations is removed rationally. Then, these three types of particles evolve dynamically according to three corresponding kinds of simplified algorithm models. Then, PSO, other two improved PSOs with good optimization performance at present and simplified PSO proposed by this paper all are used to resolve the optimization problems of four widely used test functions, and the results show that simplified PSO has better optimization performance than others. © 2010 IEEE.

Chen T.,Shanghai Dianji University
ICEIE 2010 - 2010 International Conference on Electronics and Information Engineering, Proceedings | Year: 2010

The application of advanced virtual reality technology and product exchange technology is the main process of the virtual prototype for supporting virtual assembly of product life cycle. Taking a typically complex mechanical product - pumps as an example, this paper analyzed the assembly model of mechanical products, built the virtual assembly scene, and applied the DFA and virtual reality technology to implement the virtual assembly, virtual operation and real-time interaction through VRML and Script nodes in the virtual environment. Meanwhile, by applying the method of Bounding Boxes, the collision detection analysis during the process of assembly is completed. It presented a new design and implementation method for developing complex machinery. © 2010 IEEE.

Zhang X.F.,Shanghai Dianji University
Advanced Materials Research | Year: 2014

Wind is one of the most promising sources of alternative energy. The construction of wind farms grows quickly in China. It is necessary for stakeholders to estimate investment costs and make good decisions on a wind power project by making a budget for the investment. However, the identification of rational investment practices is technically challenging because of the lack of scientific tools to evaluate optimal decisions. A multi-criteria evaluation method was proposed to select rational investment strategy for wind farm construction. The method is based on the analytic hierarchy process (AHP) together with a technique for order preference by similarity to ideal solution (TOPSIS). A decision problem hierarchy with three layers were investigated. The top layer is an objective layer for evaluating the investment rationality. The intermediate layer includes three evaluation criteria, that is, configuration of wind turbine generator systems, physical environment and social environment. Some relative and important indicators for each criterion are in the low layer. The evaluation results illustrate that the proposed method is practical and helpful to indentify the investment rationality for wind farms. © (2014) Trans Tech Publications, Switzerland.

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