The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of t...The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of the module definition model (MDM) is discussed in detail. Itis composed of two models: the part definition model (PDM) and the module assembly model(MAM). The PDM and MAM are built and their structures are given. Using object-oriented know-ledge representation and based on these models, an intelligent support system of modular design forheavy duty NC machine tools is developed and implemented This system has been applied to thepractical use of Wuhan Heavy Duty Machine Tool Works展开更多
A new generalized modular design (GMD) method is proposed based on designpractice of frame structure of hydraulic press machines. By building a series of flexible modules(FMs), design knowledge and structure features ...A new generalized modular design (GMD) method is proposed based on designpractice of frame structure of hydraulic press machines. By building a series of flexible modules(FMs), design knowledge and structure features are integrated into parametric models. Then,parametric design and variational analysis methods for GMD are presented according to user defineddesign objectives and customized product characteristics. A FM-centered GMD system is developed andsuccessfully used in the rapid design of relevant products.展开更多
A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a n...A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.展开更多
The kinematic design of a reconfigurable miniature parallel kinematic machineis dealt with. It shows that the reconfigurability may be realized by packaging a tripod-basedparallel mechanism with fixed length struts in...The kinematic design of a reconfigurable miniature parallel kinematic machineis dealt with. It shows that the reconfigurability may be realized by packaging a tripod-basedparallel mechanism with fixed length struts into a compact and rigid frame with which the differentconfigurations can be formed. Utilizing a dual parameter model, the influences of the geometricalparameters on the dexterous performance and the workspace/machine volume ratio are investigated. Anovel global performance index for the dimensional synthesis is proposed and optimized, resulting ina set of dimensionless geometrical parameters.展开更多
The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,f...The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,fault tree analysis(FTA)method,based on static logic and static failure mechanism is no longer applicable for dynamic systems reliability analysis.Dynamic fault tree(DFT)analysis method can solve this problem effectively.In this method,DFT first should be pretreated to get a simplified fault tree(FT);then the FT was modularized to get the independent static subtrees and dynamic subtrees.Binary decision diagram(BDD)analysis method was used to analyze static subtrees,while an approximation algorithm was used to deal with dynamic subtrees.When the scale of each subtree is smaller than the system scale,the analysis efficiency can be improved significantly.At last,the usefulness of this DFT analysis method was proved by applying it to analyzing the reliability of electrical system.展开更多
文摘The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of the module definition model (MDM) is discussed in detail. Itis composed of two models: the part definition model (PDM) and the module assembly model(MAM). The PDM and MAM are built and their structures are given. Using object-oriented know-ledge representation and based on these models, an intelligent support system of modular design forheavy duty NC machine tools is developed and implemented This system has been applied to thepractical use of Wuhan Heavy Duty Machine Tool Works
文摘A new generalized modular design (GMD) method is proposed based on designpractice of frame structure of hydraulic press machines. By building a series of flexible modules(FMs), design knowledge and structure features are integrated into parametric models. Then,parametric design and variational analysis methods for GMD are presented according to user defineddesign objectives and customized product characteristics. A FM-centered GMD system is developed andsuccessfully used in the rapid design of relevant products.
基金Project(9140A18010210KG01) supported by the Departmental Pre-Research Fund of China
文摘A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.
基金This project is supported by National Natural Science Foundation of China (No.50075059) Tianjin Science and Technology Commission (No. 99370111 andNo.003802111).
文摘The kinematic design of a reconfigurable miniature parallel kinematic machineis dealt with. It shows that the reconfigurability may be realized by packaging a tripod-basedparallel mechanism with fixed length struts into a compact and rigid frame with which the differentconfigurations can be formed. Utilizing a dual parameter model, the influences of the geometricalparameters on the dexterous performance and the workspace/machine volume ratio are investigated. Anovel global performance index for the dimensional synthesis is proposed and optimized, resulting ina set of dimensionless geometrical parameters.
文摘The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,fault tree analysis(FTA)method,based on static logic and static failure mechanism is no longer applicable for dynamic systems reliability analysis.Dynamic fault tree(DFT)analysis method can solve this problem effectively.In this method,DFT first should be pretreated to get a simplified fault tree(FT);then the FT was modularized to get the independent static subtrees and dynamic subtrees.Binary decision diagram(BDD)analysis method was used to analyze static subtrees,while an approximation algorithm was used to deal with dynamic subtrees.When the scale of each subtree is smaller than the system scale,the analysis efficiency can be improved significantly.At last,the usefulness of this DFT analysis method was proved by applying it to analyzing the reliability of electrical system.
