Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificia...Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities.展开更多
Mold manufacturing Extended Enterprise （EE） has the following characteristics： distributed in locality, tight cooperation and frequent information exchange. It needs a collaborative, highly efficient, reliable and ...Mold manufacturing Extended Enterprise （EE） has the following characteristics： distributed in locality, tight cooperation and frequent information exchange. It needs a collaborative, highly efficient, reliable and intelligent manufacturing management system. The background of the Collaborative Manufacturing is introduced. A mold Collaborative Manufacturing Execution System （c-MES） is proposed. The feature of Web Service platform is analyzed. The necessity and feasibility of importing the Web Service to mold c-MES are discussed. Based on Web Service, the model of mold c-MES is built. Every module＇ s function is described in detail, including the functions it supplies and the mechanism of information interaction among them. The feasibility of mold c-MES model is validated by a real mold manufacturing case.展开更多
Fuzzy neural networks （FNN） based on Gaussian membership functions can effectively control the motion of underwater vehicles. However, their operating processes and training algorithms are complicated, placing great...Fuzzy neural networks （FNN） based on Gaussian membership functions can effectively control the motion of underwater vehicles. However, their operating processes and training algorithms are complicated, placing great demands on embedded hardware. This paper presents an advanced FNN with an S membership function matching the motion characteristics of mini underwater vehicles with wings. A leaming algorithm was then developed. Simulation results showed that the modified FNN is a simpler algorithm with faster calculations and improves responsiveness, compared with a Gaussian membership function-based FNN. It is applicable for mini underwater vehicles that don＇t need accurate positioning but must have good maneuverability.展开更多
文摘Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities.
文摘Mold manufacturing Extended Enterprise （EE） has the following characteristics： distributed in locality, tight cooperation and frequent information exchange. It needs a collaborative, highly efficient, reliable and intelligent manufacturing management system. The background of the Collaborative Manufacturing is introduced. A mold Collaborative Manufacturing Execution System （c-MES） is proposed. The feature of Web Service platform is analyzed. The necessity and feasibility of importing the Web Service to mold c-MES are discussed. Based on Web Service, the model of mold c-MES is built. Every module＇ s function is described in detail, including the functions it supplies and the mechanism of information interaction among them. The feasibility of mold c-MES model is validated by a real mold manufacturing case.
基金the Fundamental Research Foundation of Harbin Engineering University Foundation under Grant No.HEUFT08001
文摘Fuzzy neural networks （FNN） based on Gaussian membership functions can effectively control the motion of underwater vehicles. However, their operating processes and training algorithms are complicated, placing great demands on embedded hardware. This paper presents an advanced FNN with an S membership function matching the motion characteristics of mini underwater vehicles with wings. A leaming algorithm was then developed. Simulation results showed that the modified FNN is a simpler algorithm with faster calculations and improves responsiveness, compared with a Gaussian membership function-based FNN. It is applicable for mini underwater vehicles that don＇t need accurate positioning but must have good maneuverability.
