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Wu D.,Jimei University | Wu D.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Ren F.,Jimei University | Ren F.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | And 2 more authors.
Ocean Engineering | Year: 2016

Thrust allocation (TA) is an important part in dynamic positioning systems (DPS). The function of TA is to allocate the thrust and angle of each thruster so that the desired force and moment can be achieved. Based on our previous work, an adaptive hybrid artificial bee colony algorithm with chaotic search (AHABCC) is proposed in this study. This algorithm introduced a mutation operator from differential evolution (DE) and the social cognitive part of particle swarm optimization (PSO) to the honeybee and chaotic search strategies to scouts searching. The proportion of each search strategy selected is dynamically adjusted to achieve the optimization. Therefore, the AHABCC can automatically switch the search strategy for different bee colonies. The optimal search of AHABCC is faster compared to HABCC, and the probability of obtaining optimal results and avoiding local optimums is significantly increased. In addition, the power consumption of AHABCC is less than that of HABCC. The effectiveness of the AHABCC algorithm is demonstrated using simulations. © 2016 Elsevier Ltd. All rights reserved.


Rongjie W.,Jimei University | Rongjie W.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Yiju Z.,Sun Yat Sen University | Haifeng Z.,Jimei University
Circuits, Systems, and Signal Processing | Year: 2016

We consider the problem of sequential, blind source separation in some specific order from a mixture of sub- and sup-Gaussian sources. Three methods of separation are developed, specifically, kurtosis maximization using (a) particle swarm optimization, (b) differential evolution, and (c) artificial bee colony algorithm, all of which produce the separation in decreasing order of the absolute kurtosis based on the maximization of the kurtosis cost function. The validity of the methods was confirmed through simulation. Moreover, compared with other conventional methods, the proposed method separated the various sources with greater accuracy. Finally, we performed a real-world experiment to separate electroencephalogram (EEG) signals from a super-determined mixture with Gaussian noise. Whereas the conventional methods separate simultaneously EEG signals of interest along with noise, the result of this example shows the proposed methods recover from the outset solely those EEG signals of interest. This feature will be of benefit in many practical applications. © 2015, Springer Science+Business Media New York.


Wang R.,Jimei University | Wang R.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Zhan Y.,Sun Yat Sen University | Zhou H.,Jimei University
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2015

A post-nonlinear blind source separation method based on nonlinear principal component analysis and H∞ filtering is proposed. In this method, a cost function of nonlinear principal component analysis is constructed according to the post nonlinear mixture linear time-varying model, which is used to solve the time-varying confusion matrix; then the source signals mixed in the post-nonlinear observation signals are recovered through optimizing the cost function using H∞ filtering algorithm. This method only requires the statistics independent prior information of the source signals. The simulation results show that the proposed method can achieve the blind source separation of the source signals with sub- and super-Gaussian distribution with higher accuracy compared with other traditional algorithms. Moreover, the method can also achieve the post-nonlinear blind source separation of the source signals on-line and dynamically. © 2015, Science Press. All right reserved.


Wang R.,Jimei University | Wang R.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Zhan Y.,Sun Yat Sen University | Zhou H.,Jimei University
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2015

Aiming at the blind source separation problem of time-varying number of sources, a dynamic source number estimation method based on cross-validation technique is proposed. Then, an adaptive blind source separation algorithm based on natural gradient and Frobenius norm is deduced. The innovative blind separation algorithm does not require the assumption of any restrictions or constraints on source signals; therefore it is suitable for separating the sources obeying super- and sub-Gaussian distributions. At last, the effectiveness of the proposed method was verified in the simulation experiments for time-invariant and time-varying number of sources. ©, 2015, Science Press. All right reserved.


Wang R.,Jimei University | Wang R.,Sun Yat Sen University | Zhan Y.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Zhou H.,Jimei University | Zhou H.,Sun Yat Sen University
International Journal of Innovative Computing, Information and Control | Year: 2015

In a synchronous generator, the electrometrical coupling between the rotor and the rest of the system causes it to behave in a manner similar to a dam,per system,. We consider the problem of enhancing the stability of PID based on artificial bee colony algorithm controlled automatic voltage regulator in this article. Firstly, the generated strategy of initial value based on Logistic mapping and best-so-far selection were integrated into original artificial bee colony algorithm. Then parameters of PID were self-adjusted by using the proposed ABC algorithm, so as to realize self-tuning of automatic voltage regulator. The simulation results show that the proposed method can exhibit desired response of PID controlled AVR system. © 2015.


Wang R.,Jimei University | Wang R.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Zhan Y.,Sun Yat Sen University | Zhou H.,Jimei University
Energies | Year: 2015

The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a single diode model and double diode model using this improved artificial bee colony. Experimental results clearly demonstrate the effectiveness of the proposed method and its superior performance compared to other competing methods. © 2015 by the authors.


Wu D.,Jimei University | Ren F.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering
Chinese Control Conference, CCC | Year: 2015

The complex interference from ocean environment and the complicated ship shape and structure result in the model uncertainties of dynamic positioning system (DPS). Due to the inaccuracy and coupling of model, it is difficult to adjust it well for common method. This paper introduces the active disturbance rejection controller (ADRC) to control the ship moving and positioning with DPS because of its independence from accurate model and easy to decouple. In this study, the biogeography-based optimization (BBO) is employed to optimize the parameters of ADRC which are not easy to adjust artificially. Finally, the presented method is verified effectively by computer simulations. © 2015 Technical Committee on Control Theory, Chinese Association of Automation.


Wu D.,Jimei University | Wu D.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering | Chen T.,Henan University of Technology | Li A.,Dalian Maritime University
Sensors (Switzerland) | Year: 2016

A robot-based three-dimensional (3D) measurement system is presented. In the presented system, a structured light vision sensor is mounted on the arm of an industrial robot. Measurement accuracy is one of the most important aspects of any 3D measurement system. To improve the measuring accuracy of the structured light vision sensor, a novel sensor calibration approach is proposed to improve the calibration accuracy. The approach is based on a number of fixed concentric circles manufactured in a calibration target. The concentric circle is employed to determine the real projected centres of the circles. Then, a calibration point generation procedure is used with the help of the calibrated robot. When enough calibration points are ready, the radial alignment constraint (RAC) method is adopted to calibrate the camera model. A multilayer perceptron neural network (MLPNN) is then employed to identify the calibration residuals after the application of the RAC method. Therefore, the hybrid pinhole model and the MLPNN are used to represent the real camera model. Using a standard ball to validate the effectiveness of the presented technique, the experimental results demonstrate that the proposed novel calibration approach can achieve a highly accurate model of the structured light vision sensor. © 2016 by the authors; licensee MDPI, Basel, Switzerland.


Zhu J.,Jimei University | Chen W.,Jimei University | Chen W.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering
Applied Thermal Engineering | Year: 2015

Many research results suggested that a good estimation model often played a crucial role in the design, optimization and analysis for the HVAC system, especially during the preliminary design stage. Based on the multivariate linear regression analysis method, this paper presented a simple and high-accuracy prediction model by adding a dynamic correction factor. Newly developed model was not only particularly used to the marine rotary desiccant air-conditioning, but also its veracity and reliability were verified by a series of sample data and three evaluation indicators. Meanwhile, the prediction and optimization schemes of system performance are also introduced in detail. As expected, it was found that the dynamic correction factor can make the fitting value of prediction model close to the real value infinitely, and almost achieved linear fitting perfectly. As the number of correction increased, the residual and the residual standard deviation close to zero rapidly, and the relative error doubled decreased nearly. Besides, the square of multiple coefficient correlation (R2) of the prediction models reached 0.999 after the seventh corrected and the relative error much less than 1%. Furthermore, it was believed that the methodology developed here can be applied to other related fields. © 2015 Elsevier Ltd. All rights reserved.


Zhu J.,Jimei University | Chen W.,Jimei University | Chen W.,Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering
Energy | Year: 2014

A novel marine rotary desiccant A/C (air-conditioning) system was developed and studied to improve energy utilization efficiency of ship A/C. The orthogonal experiment was first carried out to investigate the influence of various parameters of the marine rotary desiccant A/C system. During the orthogonal experiment the analysis of variance was used to exclude interference from the secondary influencing factor on system performance. The significant influencing factors of system were studied in great detail using the first and second laws of thermodynamics to find optimal setting parameters for best system performance. It is suggested from the analysis results that as regeneration temperature increases, the COPth (thermal coefficient of performance) and exergy efficiency of system (νe) decreases by 46.9% and 38.8% respectively. They decrease in proportion to the increase of the temperature. νe reaches its maximum value of about 23.5% when the inlet humidity ratio of process air is 22g/kg. Besides, the exergy loss of system concentrates on the regeneration air heater, the desiccant wheel and the regeneration air leaving the desiccant wheel, which account for 68.4%-81% of the total exergy loss. It can be concluded that applying the marine rotary desiccant A/C in high-temperature and high-humidity marine environment is advantageous. © 2014 Elsevier Ltd.

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