Various 3D modeling software has been developed for design and manufacturing. Most of the commercially available software uses native file formats, which may not be able to be read or understood by other software. Thi...Various 3D modeling software has been developed for design and manufacturing. Most of the commercially available software uses native file formats, which may not be able to be read or understood by other software. This paper deals with the development of a generic approach of a 3D model conversion program for virtual manufacturing （VM）, using a lexical analyzer generator Lex and the Open Graphic Library （OpenGL）. The program is able to convert 3D mesh data between four universal file formats, i.e., Stereolithography （STL）, Virtual Reality Modeling Language （VRML）, eXtensible Markup Language （XML）, and Object （OBJ）. Simple assembly functions can be applied to the imported models. The quaternion angle is used for object rotation to overcome the problem of gimbal lock or a loss of one degree of rotational freedom. The program has been validated by importing the neutral format models into the program, applying the transformation, saving the new models with a new coordinate system, and lastly exporting into other commercial software. The results showed that the program is able to render and re-arrange accurately the geometry data from the different universal file formats and that it can be used in VM. Therefore, the output models from a VM system can be transferred or imported to another VM system in a universal file format.展开更多
Designing reliable flight control for an autonomous helicopter requires a high performance dynamics model.In this paper,a nonlinear autoregressive with exogenous inputs (NLARX) model is selected as the mathematical st...Designing reliable flight control for an autonomous helicopter requires a high performance dynamics model.In this paper,a nonlinear autoregressive with exogenous inputs (NLARX) model is selected as the mathematical structure for identifying and controlling the flight of a small-scale helicopter.A neural network learning algorithm is combined with the NLARX model to identify the dynamic component of the rotorcraft unmanned aerial vehicle (RUAV).This identification process is based on the well-known gradient descent learning algorithm.As a case study,the multiple-input multiple-output (MIMO) model predictive control (MPC) is applied to control the pitch motion of the helicopter.Results of the neural network output model are closely match with the real flight data.The MPC also shows good performance under various conditions.展开更多
Surface roughness is an important parameter for ensuring that the dimension of geometry is within the permitted tolerance.The ideal surface roughness is determined by the feed rate and the geometry of the tool.However...Surface roughness is an important parameter for ensuring that the dimension of geometry is within the permitted tolerance.The ideal surface roughness is determined by the feed rate and the geometry of the tool.However,several uncontrollable factors including work material factors,tool angle,and machine tool vibration,may also influence surface roughness.The objective of this study was to compare the measured surface roughness (from experiment) to the theoretical surface roughness (from theoretical calculation) and to investigate the surface roughness resulting from two types of insert,‘C’ type and ‘T’ type.The experiment was focused on the turning process,using a lathe machine Colchester 6000.The feed rate was varied within the recommended feed rate range.We found that there were large deviations between the measured and theoretical surface roughness at a low feed rate (0.05 mm/r) from the application of both inserts.A work material factor of AISI D2 steel that affects the chip character is presumably responsible for this phenomenon.Interestingly,at a high feed rate (0.4 mm/r),the ‘C’ type insert resulted in 40% lower roughness compared to the ‘T’ type due to the difference in insert geometry.This study shows that the geometry of an insert may result in a different surface quality at a particular level of feed rate.展开更多
基金Project （No. RG060/09AET） supported by the University of Malaya Research Grant （UMRG）
文摘Various 3D modeling software has been developed for design and manufacturing. Most of the commercially available software uses native file formats, which may not be able to be read or understood by other software. This paper deals with the development of a generic approach of a 3D model conversion program for virtual manufacturing （VM）, using a lexical analyzer generator Lex and the Open Graphic Library （OpenGL）. The program is able to convert 3D mesh data between four universal file formats, i.e., Stereolithography （STL）, Virtual Reality Modeling Language （VRML）, eXtensible Markup Language （XML）, and Object （OBJ）. Simple assembly functions can be applied to the imported models. The quaternion angle is used for object rotation to overcome the problem of gimbal lock or a loss of one degree of rotational freedom. The program has been validated by importing the neutral format models into the program, applying the transformation, saving the new models with a new coordinate system, and lastly exporting into other commercial software. The results showed that the program is able to render and re-arrange accurately the geometry data from the different universal file formats and that it can be used in VM. Therefore, the output models from a VM system can be transferred or imported to another VM system in a universal file format.
基金Project (No.13-01-03-SF0024) supported by the MOSTI (Malaysia) Sciencefund: Hardware-in-the-Loop Simulation for Control System of Mini Scale Rotorcraft
文摘Designing reliable flight control for an autonomous helicopter requires a high performance dynamics model.In this paper,a nonlinear autoregressive with exogenous inputs (NLARX) model is selected as the mathematical structure for identifying and controlling the flight of a small-scale helicopter.A neural network learning algorithm is combined with the NLARX model to identify the dynamic component of the rotorcraft unmanned aerial vehicle (RUAV).This identification process is based on the well-known gradient descent learning algorithm.As a case study,the multiple-input multiple-output (MIMO) model predictive control (MPC) is applied to control the pitch motion of the helicopter.Results of the neural network output model are closely match with the real flight data.The MPC also shows good performance under various conditions.
基金Project supported by the Japan International Cooperation Agency (JICA) for AUNSEED/Net (No.JICA 8123227)a University Malaya Research Grant (UMRG) (No.RG 059 09AET),Malaysia
文摘Surface roughness is an important parameter for ensuring that the dimension of geometry is within the permitted tolerance.The ideal surface roughness is determined by the feed rate and the geometry of the tool.However,several uncontrollable factors including work material factors,tool angle,and machine tool vibration,may also influence surface roughness.The objective of this study was to compare the measured surface roughness (from experiment) to the theoretical surface roughness (from theoretical calculation) and to investigate the surface roughness resulting from two types of insert,‘C’ type and ‘T’ type.The experiment was focused on the turning process,using a lathe machine Colchester 6000.The feed rate was varied within the recommended feed rate range.We found that there were large deviations between the measured and theoretical surface roughness at a low feed rate (0.05 mm/r) from the application of both inserts.A work material factor of AISI D2 steel that affects the chip character is presumably responsible for this phenomenon.Interestingly,at a high feed rate (0.4 mm/r),the ‘C’ type insert resulted in 40% lower roughness compared to the ‘T’ type due to the difference in insert geometry.This study shows that the geometry of an insert may result in a different surface quality at a particular level of feed rate.
