The development of new robot structures, in particular of parallel kinematic machines（PKM）, is widely systematized by different structure synthesis methods. Recent research increasingly focuses on PKM with less than...The development of new robot structures, in particular of parallel kinematic machines（PKM）, is widely systematized by different structure synthesis methods. Recent research increasingly focuses on PKM with less than six degrees of freedom（DOF）. However, an overall comparison and evaluation of these structures is missing. In order to compare symmetrical PKM with three translational DOF, different evaluation criteria are used. Workspace, maximum actuation forces and velocities, power, actuator stiffness, accuracy and transmission behavior are taken into account to investigate strengths and weaknesses of the PKMs. A selection scheme based on possible configurations of translational PKM including different frame configurations is presented. Moreover, an optimization method based on a genetic algorithm is described to determine the geometric parameters of the selected PKM for an exemplary load case and a prescribed workspace. The values of the mentioned criteria are determined for all considered PKM with respect to certain boundary conditions. The distribution and spreading of these values within the prescribed workspace is presented by using box plots for each criterion. Thereby, the performance characteristics of the different structures can be compared directly. The results show that there is no ＂best＂ PKM. Further inquiries such as dynamic or stiffness analysis are necessary to extend the comparison and to finally select a PKM.展开更多
A novel symmetrical 3-degree-of-freedom(DOF) parallel kinematic manipulator(PKM) is firstly presented,which is named 3-P(Qu) RU.According to the structure feature,a double closed loop vector method is proposed to inve...A novel symmetrical 3-degree-of-freedom(DOF) parallel kinematic manipulator(PKM) is firstly presented,which is named 3-P(Qu) RU.According to the structure feature,a double closed loop vector method is proposed to investigate this PKM.Based on this method,kinematic,velocity and error models of this manipulator are established respectively.Since3-PRS PKM has been applied successfully in practice and its structure is similar to the 3-P(Qu) RU PKM,corresponding models of a 3-PRS PKM are given and a performance comparison study between them is investigated on workspace,manipulator dexterity,position error and error sensitivity.The comparison results reveal that the 3-P(Qu) RU PKM has the advantage on velocity performance and the disadvantage on accuracy performance.This novel 3-P(Qu) RU PKM is an available selection for a tool head of a hybrid machine tool and the analysis is greatly helpful for the further applications of this manipulator.展开更多
In this paper, we propose a parallel computing technique for content-based image retrieval （CBIR） system. This technique is mainly used for single node with multi-core processor, which is different from those based ...In this paper, we propose a parallel computing technique for content-based image retrieval （CBIR） system. This technique is mainly used for single node with multi-core processor, which is different from those based on cluster or network computing architecture. Due to its specific applications （such as medical image processing） and the harsh terms of hardware resource requirement, the CBIR system has been prevented from being widely used. With the increasing volume of the image database, the widespread use of multi-core processors, and the requirement of the retrieval accuracy and speed, we need to achieve a retrieval strategy which is based on multi-core processor to make the retrieval faster and more convenient than before. Experimental results demonstrate that this parallel architecture can significantly improve the performance of retrieval system. In addition, we also propose an efficient parallel technique with the combinations of the cluster and the multi-core techniques, which is supposed to gear to the new trend of the cloud computing.展开更多
文摘The development of new robot structures, in particular of parallel kinematic machines（PKM）, is widely systematized by different structure synthesis methods. Recent research increasingly focuses on PKM with less than six degrees of freedom（DOF）. However, an overall comparison and evaluation of these structures is missing. In order to compare symmetrical PKM with three translational DOF, different evaluation criteria are used. Workspace, maximum actuation forces and velocities, power, actuator stiffness, accuracy and transmission behavior are taken into account to investigate strengths and weaknesses of the PKMs. A selection scheme based on possible configurations of translational PKM including different frame configurations is presented. Moreover, an optimization method based on a genetic algorithm is described to determine the geometric parameters of the selected PKM for an exemplary load case and a prescribed workspace. The values of the mentioned criteria are determined for all considered PKM with respect to certain boundary conditions. The distribution and spreading of these values within the prescribed workspace is presented by using box plots for each criterion. Thereby, the performance characteristics of the different structures can be compared directly. The results show that there is no ＂best＂ PKM. Further inquiries such as dynamic or stiffness analysis are necessary to extend the comparison and to finally select a PKM.
基金Supported by the National Natural Science Foundation of China(No.51575307,51225503)the Science and Technology Major Project-Advanced NC Machine Tools & Basic Manufacturing Equipments(No.2013ZX04004021,2014ZX04002051)Top-Notch Young Talents Program of China
文摘A novel symmetrical 3-degree-of-freedom(DOF) parallel kinematic manipulator(PKM) is firstly presented,which is named 3-P(Qu) RU.According to the structure feature,a double closed loop vector method is proposed to investigate this PKM.Based on this method,kinematic,velocity and error models of this manipulator are established respectively.Since3-PRS PKM has been applied successfully in practice and its structure is similar to the 3-P(Qu) RU PKM,corresponding models of a 3-PRS PKM are given and a performance comparison study between them is investigated on workspace,manipulator dexterity,position error and error sensitivity.The comparison results reveal that the 3-P(Qu) RU PKM has the advantage on velocity performance and the disadvantage on accuracy performance.This novel 3-P(Qu) RU PKM is an available selection for a tool head of a hybrid machine tool and the analysis is greatly helpful for the further applications of this manipulator.
基金supported by the Natural Science Foundation of Shanghai (Grant No.08ZR1408200)the Shanghai Leading Academic Discipline Project (Grant No.J50103)the Open Project Program of the National Laboratory of Pattern Recognition
文摘In this paper, we propose a parallel computing technique for content-based image retrieval （CBIR） system. This technique is mainly used for single node with multi-core processor, which is different from those based on cluster or network computing architecture. Due to its specific applications （such as medical image processing） and the harsh terms of hardware resource requirement, the CBIR system has been prevented from being widely used. With the increasing volume of the image database, the widespread use of multi-core processors, and the requirement of the retrieval accuracy and speed, we need to achieve a retrieval strategy which is based on multi-core processor to make the retrieval faster and more convenient than before. Experimental results demonstrate that this parallel architecture can significantly improve the performance of retrieval system. In addition, we also propose an efficient parallel technique with the combinations of the cluster and the multi-core techniques, which is supposed to gear to the new trend of the cloud computing.
文摘数据驱动的多元化发展导致数据异构性增强、维度提升和特征量规模扩大,给贸易经济分析带来更大挑战。为了提高贸易经济分析的科学性,采用非平行超平面支持向量机算法(support vector machine,SVM)对贸易经济进行预测分析。首先,根据贸易经济影响因素进行主成分分析,获取影响贸易经济的关键特征,并对特征进行量化和去噪处理。然后,采用广义特征值最接近支持向量机(proximal support vector machine via generalized eigenvalues,GEPSVM)进行贸易经济预测分类。根据预测指标要求,选择核函数GEPSVM算法(KGEPSVM算法)对分类的非平行超平面求解,通过类别划分函数获得经济预测结果。实证分析表明,对比常用的非平行超平面支持向量机算法,所提算法的贸易经济预测性能更优,而且在常用贸易经济指标的预测中,表现出较高预测精度和稳定性。
