In intelligentmanufacturing processes such as aerospace production,computer numerical control(CNC)machine tools require real-time optimization of process parameters to meet precision machining demands.These dynamic op...In intelligentmanufacturing processes such as aerospace production,computer numerical control(CNC)machine tools require real-time optimization of process parameters to meet precision machining demands.These dynamic operating conditions increase the risk of fatigue damage in CNC machine tool bearings,highlighting the urgent demand for rapid and accurate fault diagnosis methods that can maintain production efficiency and extend equipment uptime.However,varying conditions induce feature distribution shifts,and scarce fault samples limitmodel generalization.Therefore,this paper proposes a causal-Transformer-based meta-learning(CTML)method for bearing fault diagnosis in CNC machine tools,comprising three core modules:(1)the original bearing signal is transformed into a multi-scale time-frequency feature space using continuous wavelet transform;(2)a causal-Transformer architecture is designed to achieve feature extraction and fault classification based on the physical causal law of fault propagation;(3)the above mechanisms are integrated into a model-agnostic meta-learning(MAML)framework to achieve rapid cross-condition adaptation through an adaptive gradient pruning strategy.Experimental results using the multiple bearing dataset show that under few-shot cross-condition scenarios(3-way 1-shot and 3-way 5-shot),the proposed CTML outperforms benchmark models(e.g.,Transformer,domain adversarial neural networks(DANN),and MAML)in terms of classification accuracy and sensitivity to operating conditions,while maintaining a moderate level of model complexity.展开更多
The prediction of tool wear in CNC machine tools is a critical aspect of ensuring the efficient operation and longevity of manufacturing equipment.Tool wear significantly impacts machining accuracy,surface finish qual...The prediction of tool wear in CNC machine tools is a critical aspect of ensuring the efficient operation and longevity of manufacturing equipment.Tool wear significantly impacts machining accuracy,surface finish quality,and operational downtime,making its prediction essential for proactive maintenance strategies.This paper explores the integration of Digital Twin technology with tool wear prediction models to enhance the precision and reliability of wear forecasting in CNC machines.We review existing methodologies for tool wear prediction,including physics-based models,data-driven approaches,and hybrid models,with an emphasis on their strengths and limitations.Furthermore,the paper highlights the role of Digital Twin technology in creating real-time,virtual replicas of CNC machines that can dynamically monitor tool wear and provide actionable insights for optimization.By leveraging real-time data and advanced simulation techniques,Digital Twin-based prediction models offer significant improvements over traditional methods.The paper concludes by discussing future directions for integrating machine learning,deep learning,and real-time data analytics into the tool wear prediction process,ultimately contributing to the development of more intelligent and adaptive manufacturing systems.展开更多
Thermal errors in CNC machine tools,particularly those involving the spindle,significantly affect machining accuracy and performance.These errors,caused by temperature fluctuations in the spindle and surrounding compo...Thermal errors in CNC machine tools,particularly those involving the spindle,significantly affect machining accuracy and performance.These errors,caused by temperature fluctuations in the spindle and surrounding components,result in dimensional deviations that can lead to poor part quality and reduced precision in high-speed manufacturing processes.This paper explores thermal error modeling and compensation methods for the spindle of five-axis CNC machine tools.A detailed analysis of the heat generation,transfer mechanisms,and finite element analysis(FEA)is presented to develop accurate thermal error models.Compensation techniques,such as model-based methods,sensor-based methods,real-time compensation algorithms,and hybrid approaches,are critically reviewed.This study also discusses the challenges in real-time compensation and the integration of thermal error compensation with machine tool control systems.The objective is to provide a comprehensive understanding of thermal error phenomena and their compensation strategies,ultimately contributing to the enhancement of machining accuracy in advanced manufacturing applications.展开更多
To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acq...To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acquisition, knowledge representation and reasoning used in CNC programming were researched. The CNC programming system functional architecture of impeller parts based on knowledge based engineering(KBE) was constructed. The structural model of the general knowledge-based system(KBS) was also constructed. The KBS of CNC programming system was established through synthesizing database technology and knowledge base theory. And in the context of corporate needs, based on the knowledge-driven manufacturing platform(i.e. UG CAD/CAM), VC++6.0 and UG/Open, the KBS and UG CAD/CAM were integrated seamlessly and the intelligent CNC programming KBE system for the impeller parts was developed by integrating KBE and UG CAD/CAM system. A method to establish standard process templates was proposed, so as to develop the intelligent CNC programming system in which CNC machining process and process parameters were standardized by using this KBE system. For the impeller parts processing, the method applied in the development of the prototype system is proven to be viable, feasible and practical.展开更多
运动过程的升降速控制是CNC(Com puter num ericalcontrol)系统开发中的关键技术难题之一。文中在分别分析了数控系统中梯形、S型和直线加抛物型升降速曲线的基础上,对这几种控制方法各自的优缺点及适用场合进行了比较,并着重讨论了速...运动过程的升降速控制是CNC(Com puter num ericalcontrol)系统开发中的关键技术难题之一。文中在分别分析了数控系统中梯形、S型和直线加抛物型升降速曲线的基础上,对这几种控制方法各自的优缺点及适用场合进行了比较,并着重讨论了速度时间曲线是直线加抛物型的升降速曲线在由步进电机驱动的经济型数控系统中的应用,实验证明。展开更多
基金the National Key Research and Development Program of China(Grant No.2022YFB3302700)the National Natural Science Foundation of China(Grant No.52375486)the Shanghai Rising-Star Program(Grant No.22QB1404200).
文摘In intelligentmanufacturing processes such as aerospace production,computer numerical control(CNC)machine tools require real-time optimization of process parameters to meet precision machining demands.These dynamic operating conditions increase the risk of fatigue damage in CNC machine tool bearings,highlighting the urgent demand for rapid and accurate fault diagnosis methods that can maintain production efficiency and extend equipment uptime.However,varying conditions induce feature distribution shifts,and scarce fault samples limitmodel generalization.Therefore,this paper proposes a causal-Transformer-based meta-learning(CTML)method for bearing fault diagnosis in CNC machine tools,comprising three core modules:(1)the original bearing signal is transformed into a multi-scale time-frequency feature space using continuous wavelet transform;(2)a causal-Transformer architecture is designed to achieve feature extraction and fault classification based on the physical causal law of fault propagation;(3)the above mechanisms are integrated into a model-agnostic meta-learning(MAML)framework to achieve rapid cross-condition adaptation through an adaptive gradient pruning strategy.Experimental results using the multiple bearing dataset show that under few-shot cross-condition scenarios(3-way 1-shot and 3-way 5-shot),the proposed CTML outperforms benchmark models(e.g.,Transformer,domain adversarial neural networks(DANN),and MAML)in terms of classification accuracy and sensitivity to operating conditions,while maintaining a moderate level of model complexity.
文摘The prediction of tool wear in CNC machine tools is a critical aspect of ensuring the efficient operation and longevity of manufacturing equipment.Tool wear significantly impacts machining accuracy,surface finish quality,and operational downtime,making its prediction essential for proactive maintenance strategies.This paper explores the integration of Digital Twin technology with tool wear prediction models to enhance the precision and reliability of wear forecasting in CNC machines.We review existing methodologies for tool wear prediction,including physics-based models,data-driven approaches,and hybrid models,with an emphasis on their strengths and limitations.Furthermore,the paper highlights the role of Digital Twin technology in creating real-time,virtual replicas of CNC machines that can dynamically monitor tool wear and provide actionable insights for optimization.By leveraging real-time data and advanced simulation techniques,Digital Twin-based prediction models offer significant improvements over traditional methods.The paper concludes by discussing future directions for integrating machine learning,deep learning,and real-time data analytics into the tool wear prediction process,ultimately contributing to the development of more intelligent and adaptive manufacturing systems.
文摘Thermal errors in CNC machine tools,particularly those involving the spindle,significantly affect machining accuracy and performance.These errors,caused by temperature fluctuations in the spindle and surrounding components,result in dimensional deviations that can lead to poor part quality and reduced precision in high-speed manufacturing processes.This paper explores thermal error modeling and compensation methods for the spindle of five-axis CNC machine tools.A detailed analysis of the heat generation,transfer mechanisms,and finite element analysis(FEA)is presented to develop accurate thermal error models.Compensation techniques,such as model-based methods,sensor-based methods,real-time compensation algorithms,and hybrid approaches,are critically reviewed.This study also discusses the challenges in real-time compensation and the integration of thermal error compensation with machine tool control systems.The objective is to provide a comprehensive understanding of thermal error phenomena and their compensation strategies,ultimately contributing to the enhancement of machining accuracy in advanced manufacturing applications.
基金Project(12ZT14)supported by the Natural Science Foundation of Shanghai Municipal Education Commission,China
文摘To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acquisition, knowledge representation and reasoning used in CNC programming were researched. The CNC programming system functional architecture of impeller parts based on knowledge based engineering(KBE) was constructed. The structural model of the general knowledge-based system(KBS) was also constructed. The KBS of CNC programming system was established through synthesizing database technology and knowledge base theory. And in the context of corporate needs, based on the knowledge-driven manufacturing platform(i.e. UG CAD/CAM), VC++6.0 and UG/Open, the KBS and UG CAD/CAM were integrated seamlessly and the intelligent CNC programming KBE system for the impeller parts was developed by integrating KBE and UG CAD/CAM system. A method to establish standard process templates was proposed, so as to develop the intelligent CNC programming system in which CNC machining process and process parameters were standardized by using this KBE system. For the impeller parts processing, the method applied in the development of the prototype system is proven to be viable, feasible and practical.
文摘运动过程的升降速控制是CNC(Com puter num ericalcontrol)系统开发中的关键技术难题之一。文中在分别分析了数控系统中梯形、S型和直线加抛物型升降速曲线的基础上,对这几种控制方法各自的优缺点及适用场合进行了比较,并着重讨论了速度时间曲线是直线加抛物型的升降速曲线在由步进电机驱动的经济型数控系统中的应用,实验证明。
