The polymer electrolyte membrane(PEM) fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,...
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The polymer electrolyte membrane(PEM) fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this *** improve the performance,the static neural network and variable neural network are used to build the black-box *** static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required ***,the hybrid dynamic model is validated with a 500 W PEM fuel *** static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.
Using computer vision technique to detect coal level of coal bin, a kind of non-contact depth measurement method of coal bunker was put forward based on binocular vision and W-SIFT image feature matching algorithm. Th...
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Using computer vision technique to detect coal level of coal bin, a kind of non-contact depth measurement method of coal bunker was put forward based on binocular vision and W-SIFT image feature matching algorithm. Through the wavelet compression coding and scale invariant feature transform algorithm, remove all kinds of redundancy in image and keep important information. By adaptive regulating based on template of the changing scale factors and dealing with the coal bit image waiting for the binocular view registration, multi-scale spatial could be created for extracting feature points in coal level image. The left and right view is compared, and extraction feature points for in-depth matching based on the bidirectional registration strategy of binocular view so that we can more accurate restore the 3D information. According to the W-SIFT matching algorithm, prior calibration left and right image so that we can get internal and external parameters of visual sensor, then, determine the coal bunker coal bit depth value based on the coordinate transformation formula. Using the new algorithm to detect coal level, The result is satisfy compared with the traditional SIFT algorithm.
The hydraulic excavator energy-saving research mainly embodies the following three measures: to improve the performance of diesel engine and hydraulic component, to improve the hydraulic system, and to improve the po...
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The hydraulic excavator energy-saving research mainly embodies the following three measures: to improve the performance of diesel engine and hydraulic component, to improve the hydraulic system, and to improve the power matching of diesel-hydraulic system-actuator. Although the above measures have certain energy-saving effect, but because the hydraulic excavator load changes frequently and fluctuates dramatically, so the diesel engine often works in high-speed and light load condition, and the fuel consumption is higher. Therefore, in order to improve the economy of diesel engine in light load, and reduce the fuel consumption of hydraulic excavator, energy management concept is proposed based on diesel engine cylinder deactivation technology. By comparing the universal characteristic under diesel normal and deactivated cylinder condition, the mechanism that fuel consumption can be reduced significantly by adopting cylinder deactivation technology under part of loads condition can be clarified. The simulation models for hydraulic system and diesel engine are established by using AMESim software, and fuel combustion consumption by using cylinder-deactivation-technology is studied through digital simulation approach. In this way, the zone of cylinder deactivation is specified. The testing system for the excavator with this technology is set up based on simulated results, and the results show that the diesel engine can still work at high efficiency with part of loads after adopting this technology; fuel consumption is dropped down to 11% and 13% under economic and heavy-load mode respectively under the condition of driving requirements. The research provides references to the energy-saving study of the hydraulic excavators.
Dynamic image stabilization precision of an optical image-stable device is a key technical ***,a fast dynamic image stabilization precision test system for an optical image-stable device is developed.A large-aperture ...
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Dynamic image stabilization precision of an optical image-stable device is a key technical ***,a fast dynamic image stabilization precision test system for an optical image-stable device is developed.A large-aperture collimator with a designed cross divisional board is used to simulate the infinity *** image-stable device is installed on the motion simulator with six degrees of freedom which is used to simulate the moving state of the *** CCD camera installed behind the eyepiece lens of the image-stable device acquires images rapidly and in real *** local energy maxima center of the cross light spot can be acquired accurately through the proposed algorithm using the Hessian *** addition,to deal with the CCD non-uniformity,an adaptive non-uniformity correction algorithm based on bi-dimensional empirical mode decomposition is *** actual test results for the proposed method show that the test error of dynamic image stabilization is less than 0.7,and the time for the frame image acquisition and processing is less than 10 ms,which demonstrates the effectiveness of the test system.
An implementation of adaptive filtering, composed of an unsupervised adaptive filter (UAF), a multi-step forward linear predictor (FLP), and an unsupervised multi-step adaptive predictor (UMAP), is built for sup...
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An implementation of adaptive filtering, composed of an unsupervised adaptive filter (UAF), a multi-step forward linear predictor (FLP), and an unsupervised multi-step adaptive predictor (UMAP), is built for suppressing impulsive noise in unknown circumstances. This filtering scheme, called unsupervised robust adaptive filter (URAF), possesses a switching structure, which ensures the robustness against impulsive noise. The FLP is used to detect the possible impulsive noise added to the signal, if the signal is "impulse-free", the filter UAF can estimate the clean sig- nal. If there exists impulsive noise, the impulse corrupted samples are replaced by predicted ones from the FLP, and then the UMAP estimates the clean signal. Both the simulation and experimental results show that the URAF has a better rate of convergence than the most recent universal filter, and is effective to restrict large disturbance like impulsive noise when the universal filter fails.
作者:
Chen, ChaoDuan, Xing-GuangWang, Xing-TaoZhu, Xiang-YuLi, MengIntelligent Robotics Institute
Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System School of Mechatronical Engineering Beijing Institute of Technology #5Zhongguancun South Street Haidian Beijing China China
As the complex anatomical structure of the maxillofacial region, the surgery in this area is high risk and difficult to implement. Then, a multi-arm medical robot assisted maxillofacial surgery using optical navigatio...
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The content based image retrieval (CBIR) is aimed to find the most similar images from a collection of images or a database to the query image according to the visual or semantic similarity. Current image retrieval al...
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The overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive met...
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Synchronization and pinning control of complex networks is to regulate the agents' behavior and improve network performance. In this article, we review some recent developments in pinning control. Stability algori...
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Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targe...
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Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targets with complex properties. In this paper, a method for 3D deployment optimization of sensor network based on an improved Particle Swarm Optimization (PSO) algorithm is proposed. Many factors such as coverage scale, detection probability and resource utilization are synthetically considered to optimize the sensor network's overall detection performance. To evaluate the network's performance, four indexes are presented and the 3D deployment space is divided into different height levels. Accordingly, the mathematical model is formulated by weighting the performance indexes and height levels due to their importance degrees. In order to solve the optimization problem, an algorithm called WCPSO is carried out, which has a dynamic inertia weight and adaptable acceleration constants. Verified by the simulation results, the presented 3D deployment optimization method effectively improves the sensor network's detection performance. The method in this paper can provide guidance and technical reference in future application of relevant research.
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