To analyze the effects on motion characteristics of mechanisms of dimensional variations, a study on random dimensional deviation generation techniques for 3D models on the basis of the present mechanical modeling sof...To analyze the effects on motion characteristics of mechanisms of dimensional variations, a study on random dimensional deviation generation techniques for 3D models on the basis of the present mechanical modeling software was carried out, which utilized the redeveloped interfaces provided by the modeling software to develop a random dimensional deviation generation system with certain probability distribution characteristics. This system has been used to perform modeling and simulation of the specific mechanical time delayed mechanism under multiple deviation varieties, simulation results indicate the dynamic characteristics of the mechanism are influenced significantly by the dimensional deviation in the tolerance distribution range, which should be emphasized in the design.展开更多
The vertices of an infinite locally finite tree T are labelled by a collection of i.i.d.real random variables{Xo}ver which defines a tree indexed walk So=∑X,.We introduce and study the oscillations of the walk.
Machining is as old as humanity, and changes in temperature in both the machine’s internal and external environments can be of great concern as they affect the machine’s thermal stability and, thus, the machine’s d...Machining is as old as humanity, and changes in temperature in both the machine’s internal and external environments can be of great concern as they affect the machine’s thermal stability and, thus, the machine’s dimensional accuracy. This paper is a continuation of our earlier work, which aimed to analyze the effect of the internal temperature of a machine tool as the machine is put into operation and vary the external temperature, the machine floor temperature. Some experiments are carried out under controlled conditions to study how machine tool components get heated up and how this heating up affects the machine’s accuracy due to thermally induced deviations. Additionally, another angle is added by varying the machine floor temperature. The parameters mentioned above are explored in line with the overall thermal stability of the machine tool and its dimensional accuracy. A Robodrill CNC machine tool is used. The CNC was first soaked with thermal energy by gradually raising the machine floor temperature to a certain level before putting the machine in operation. The machine was monitored, and analytical methods were deplored to evaluate thermal stability. Secondly, the machine was run idle for some time under raised floor temperature before it was put into operation. Data was also collected and analyzed. It is observed that machine thermal stability can be achieved in several ways depending on how the above parameters are joggled. This paper, in conclusion, reinforces the idea of machine tool warm-up process in conjunction with a carefully analyzed and established machine floor temperature variation for the approximation of the machine tool’s thermally stability to map the long-time behavior of the machine tool.展开更多
A new concept of convergence （R-convergence） of a sequence of measures is applied to characterize global minimizers in a functional space as a sequence of approximate solutions in finite-dimensional spaces. A deviat...A new concept of convergence （R-convergence） of a sequence of measures is applied to characterize global minimizers in a functional space as a sequence of approximate solutions in finite-dimensional spaces. A deviation integral approach is used to find such solutions. For a constrained problem, a penalized deviation integral algorithm is proposed to convert it to unconstrained ones. A numerical example on an optimal control problem with non-convex state constraints is given to show the effectiveness of the algorithm.展开更多
Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outl...Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outlier. In this work, an effective outlier detection method based on multi-dimensional clustering and local density(ODBMCLD) is proposed. ODBMCLD firstly identifies the center objects by the local density peak of data objects, and clusters the whole dataset based on the center objects. Then, outlier objects belonging to different clusters will be marked as candidates of abnormal data. Finally, the top N points among these abnormal candidates are chosen as final anomaly objects with high outlier factors. The feasibility and effectiveness of the method are verified by experiments.展开更多
In all machining processes, tool wear is a natural phenomenon and it leads to tool failure. The growing demands for high productivity of machining need use of high cutting velocity and feed rate. Such machining inhere...In all machining processes, tool wear is a natural phenomenon and it leads to tool failure. The growing demands for high productivity of machining need use of high cutting velocity and feed rate. Such machining inherently produces high cutting temperature, which not only reduces tool life but also impairs the product quality. Metal cutting fluid changes the performance of machining operations because of their lubrication, cooling and chip flushing functions, but the use of cutting fluid has become more problematic in terms of both employee health and environmental pollution. The minimization of cutting fluid also leads to economical benefits by way of saving lubricant costs and workpiece/tool/machine cleaning cycle time. The concept of minimum quantity lubrication (MQL) has been suggested since a decade ago as a means of addressing the issues of environmental intru- siveness and occupational hazards associated with the airborne cutting fluid particles on factory shop floors. This paper deals with experimental investigation on the role of MQL by vegetable oil on cutting temperature, tool wear, surface roughness and dimen- sional deviation in turning AISI-1060 steel at industrial speed-feed combinations by uncoated carbide insert. The encouraging results include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction.展开更多
针对当前路径规划算法在高维复杂环境下,存在障碍物信息处理不充分、搜索效率与路径质量难以平衡等问题,提出了一种基于自适应概率偏差的改进算法——APB-RRT*算法(Adaptive Probability Bias RRT*)。首先依据障碍物类型设定安全距离,...针对当前路径规划算法在高维复杂环境下,存在障碍物信息处理不充分、搜索效率与路径质量难以平衡等问题,提出了一种基于自适应概率偏差的改进算法——APB-RRT*算法(Adaptive Probability Bias RRT*)。首先依据障碍物类型设定安全距离,在保障安全的基础上将采样空间划分为m×m×m个子区域,引入参考路径邻近性评价函数,动态调整子区域采样概率,加快了算法的收敛速度,减少了冗余节点。同时,融合基于环境感知的自适应偏置策略和变步长调节机制,提高了路径搜索效率。最后,为遵循机械臂运动学特性,采用分段贪婪算法结合三次样条插值法对路径进行平滑约束,确保了路径的连续性和可执行性。仿真实验结果表明,该文算法规划出的路径最接近理想最优路径。展开更多
基金Sponsored by the Ministerial Level Advanced Research Foundation (9153C9387029389C775)
文摘To analyze the effects on motion characteristics of mechanisms of dimensional variations, a study on random dimensional deviation generation techniques for 3D models on the basis of the present mechanical modeling software was carried out, which utilized the redeveloped interfaces provided by the modeling software to develop a random dimensional deviation generation system with certain probability distribution characteristics. This system has been used to perform modeling and simulation of the specific mechanical time delayed mechanism under multiple deviation varieties, simulation results indicate the dynamic characteristics of the mechanism are influenced significantly by the dimensional deviation in the tolerance distribution range, which should be emphasized in the design.
文摘The vertices of an infinite locally finite tree T are labelled by a collection of i.i.d.real random variables{Xo}ver which defines a tree indexed walk So=∑X,.We introduce and study the oscillations of the walk.
基金Project supported by China Postdoctoral Science Foundation （20100481488）, Key Fund Project of Advanced Research of the Weapon Equipment （9140A33040512JB3401）.
文摘Machining is as old as humanity, and changes in temperature in both the machine’s internal and external environments can be of great concern as they affect the machine’s thermal stability and, thus, the machine’s dimensional accuracy. This paper is a continuation of our earlier work, which aimed to analyze the effect of the internal temperature of a machine tool as the machine is put into operation and vary the external temperature, the machine floor temperature. Some experiments are carried out under controlled conditions to study how machine tool components get heated up and how this heating up affects the machine’s accuracy due to thermally induced deviations. Additionally, another angle is added by varying the machine floor temperature. The parameters mentioned above are explored in line with the overall thermal stability of the machine tool and its dimensional accuracy. A Robodrill CNC machine tool is used. The CNC was first soaked with thermal energy by gradually raising the machine floor temperature to a certain level before putting the machine in operation. The machine was monitored, and analytical methods were deplored to evaluate thermal stability. Secondly, the machine was run idle for some time under raised floor temperature before it was put into operation. Data was also collected and analyzed. It is observed that machine thermal stability can be achieved in several ways depending on how the above parameters are joggled. This paper, in conclusion, reinforces the idea of machine tool warm-up process in conjunction with a carefully analyzed and established machine floor temperature variation for the approximation of the machine tool’s thermally stability to map the long-time behavior of the machine tool.
基金Project supported by the National Natural Science Foundation of China(No.11071158)Shanghai Leading Academic Discipline Project(No.S30104)
文摘A new concept of convergence （R-convergence） of a sequence of measures is applied to characterize global minimizers in a functional space as a sequence of approximate solutions in finite-dimensional spaces. A deviation integral approach is used to find such solutions. For a constrained problem, a penalized deviation integral algorithm is proposed to convert it to unconstrained ones. A numerical example on an optimal control problem with non-convex state constraints is given to show the effectiveness of the algorithm.
基金Project(61362021)supported by the National Natural Science Foundation of ChinaProject(2016GXNSFAA380149)supported by Natural Science Foundation of Guangxi Province,China+1 种基金Projects(2016YJCXB02,2017YJCX34)supported by Innovation Project of GUET Graduate Education,ChinaProject(2011KF11)supported by the Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education,China
文摘Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outlier. In this work, an effective outlier detection method based on multi-dimensional clustering and local density(ODBMCLD) is proposed. ODBMCLD firstly identifies the center objects by the local density peak of data objects, and clusters the whole dataset based on the center objects. Then, outlier objects belonging to different clusters will be marked as candidates of abnormal data. Finally, the top N points among these abnormal candidates are chosen as final anomaly objects with high outlier factors. The feasibility and effectiveness of the method are verified by experiments.
基金Project (No. DEARS/CASR/R-01/2001/D-934 (30)) supported by Directorate of Advisory Extension and Research Services (DAERS), Committee for Advanced Studies & Research (CASR), BUET, Dhaka, Bangladesh
文摘In all machining processes, tool wear is a natural phenomenon and it leads to tool failure. The growing demands for high productivity of machining need use of high cutting velocity and feed rate. Such machining inherently produces high cutting temperature, which not only reduces tool life but also impairs the product quality. Metal cutting fluid changes the performance of machining operations because of their lubrication, cooling and chip flushing functions, but the use of cutting fluid has become more problematic in terms of both employee health and environmental pollution. The minimization of cutting fluid also leads to economical benefits by way of saving lubricant costs and workpiece/tool/machine cleaning cycle time. The concept of minimum quantity lubrication (MQL) has been suggested since a decade ago as a means of addressing the issues of environmental intru- siveness and occupational hazards associated with the airborne cutting fluid particles on factory shop floors. This paper deals with experimental investigation on the role of MQL by vegetable oil on cutting temperature, tool wear, surface roughness and dimen- sional deviation in turning AISI-1060 steel at industrial speed-feed combinations by uncoated carbide insert. The encouraging results include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction.
文摘针对当前路径规划算法在高维复杂环境下,存在障碍物信息处理不充分、搜索效率与路径质量难以平衡等问题,提出了一种基于自适应概率偏差的改进算法——APB-RRT*算法(Adaptive Probability Bias RRT*)。首先依据障碍物类型设定安全距离,在保障安全的基础上将采样空间划分为m×m×m个子区域,引入参考路径邻近性评价函数,动态调整子区域采样概率,加快了算法的收敛速度,减少了冗余节点。同时,融合基于环境感知的自适应偏置策略和变步长调节机制,提高了路径搜索效率。最后,为遵循机械臂运动学特性,采用分段贪婪算法结合三次样条插值法对路径进行平滑约束,确保了路径的连续性和可执行性。仿真实验结果表明,该文算法规划出的路径最接近理想最优路径。
