To ensure the extreme performances of the new 6G services,applications will be deployed at deep edge,resulting in a serious challenge of distributed application addressing.This paper traces back the latest development...To ensure the extreme performances of the new 6G services,applications will be deployed at deep edge,resulting in a serious challenge of distributed application addressing.This paper traces back the latest development of mobile network application addressing,analyzes two novel addressing methods in carrier network,and puts forward a 6G endogenous application addressing scheme by integrating some of their essence into the 6G network architecture,combining the new 6G capabilities of computing&network convergence,endogenous intelligence,and communication-sensing integration.This paper further illustrates how that the proposed method works in 6G networks and gives preliminary experimental verification.展开更多
Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracer...Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.展开更多
The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally in...The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.展开更多
In order to improve the bidirectional associative memory(BAM) performance, a modified BAM model(MBAM) is used to enhance neural network(NN)’s memory capacity and error correction capability, theoretical analysis and ...In order to improve the bidirectional associative memory(BAM) performance, a modified BAM model(MBAM) is used to enhance neural network(NN)’s memory capacity and error correction capability, theoretical analysis and experiment results illuminate that MBAM performs much better than the original BAM. The MBAM is used in computer numeric control(CNC) machine fault diagnosis, it not only can complete fault diagnosis correctly but also have fairly high error correction capability for disturbed Input Information sequence.Moreover MBAM model is a more convenient and effective method of solving the problem of CNC electric system fault diagnosis.展开更多
The objective of this study is to develop an effective approach for product quality prediction in Computer Numerical Control turning of cantilever bars. A systematic predictive modelling procedure based on experimenta...The objective of this study is to develop an effective approach for product quality prediction in Computer Numerical Control turning of cantilever bars. A systematic predictive modelling procedure based on experimental investigations, neural network modelling and various statistical analysis tools is designed to produce the most accurate, practical and cost-effective prediction model. The modeling procedure begins by exploring the relationships between cutting parameters known to have an influence on quality characteristics of machined parts, such as dimensional errors, form errors and surface roughness, as well as their sensitivity to the process conditions. Based on these explorations and using numerous statistical tools, the most relevant variables to include in the prediction model are identified and fused using several artificial neural network architectures. An application on CNC turning of cantilever bars demonstrates that the proposed modeling procedure can be effectively and advantageously applied to quality characteristics prediction due to its simplicity, accuracy and efficiency. The experimental validation reveals that the resulting prediction model can correctly predict the quality characteristics of machined parts under variable machining conditions.展开更多
Nanocellulose,a natural polymeric nanomaterial,has attracted significant attention in enhanced oil recovery(EOR)applications due to its abundance,nanoscale,high oil-water interfacial adsorption ef-ficiency.In this stu...Nanocellulose,a natural polymeric nanomaterial,has attracted significant attention in enhanced oil recovery(EOR)applications due to its abundance,nanoscale,high oil-water interfacial adsorption ef-ficiency.In this study,surface-functionalized cellulose nanocrystals(SF-CNCs)were prepared via hy-drochloric acid hydrolysis and chemical modification,with adaptable nanosize and considerable dispersion stability in low-permeability reservoirs.The SF-CNCs were structurally characterized by FT-IR,Cryo-TEM,which have a diameter of 5-10 nm and a length of 100-200 nm.The SF-CNC dispersions possessed higher stability and stronger salt-tolerance than those of corresponding CNC dispersions,due to the strong hydrophilicity of the sulfonic acid group.It was synergistically used with a non-ionic surfactant(APG1214)to formulate a combined flooding system(0.1 wt%SF-CNC+0.2 wt%APG1214).The combined flooding system exhibits strong emulsification stability,low oil-water interfacial tension of o.03 mN/m,and the ability to alter the wettability for oil-wetting rocks.Furthermore,the combined system was_able to provide an optimum EOR efficiency of 20.2%in low-permeability cores with 30.13×10^(-3)μm^(2).Notably.it can enlarge the sweep volume and increase the displacement efficiency simultaneously.Overall,the newly formulated nanocellulose/surfactant combined system exhibits a remarkable EoR performance in low-permeability reservoirs.展开更多
基金supported by the National Key R&D Program of China(Project Number:2022YFB2902100).
文摘To ensure the extreme performances of the new 6G services,applications will be deployed at deep edge,resulting in a serious challenge of distributed application addressing.This paper traces back the latest development of mobile network application addressing,analyzes two novel addressing methods in carrier network,and puts forward a 6G endogenous application addressing scheme by integrating some of their essence into the 6G network architecture,combining the new 6G capabilities of computing&network convergence,endogenous intelligence,and communication-sensing integration.This paper further illustrates how that the proposed method works in 6G networks and gives preliminary experimental verification.
基金Supported by Natural Science Foundation of Shaanxi Province of China(Grant No.2021JM010)Suzhou Municipal Natural Science Foundation of China(Grant Nos.SYG202018,SYG202134).
文摘Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.
文摘The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.
文摘In order to improve the bidirectional associative memory(BAM) performance, a modified BAM model(MBAM) is used to enhance neural network(NN)’s memory capacity and error correction capability, theoretical analysis and experiment results illuminate that MBAM performs much better than the original BAM. The MBAM is used in computer numeric control(CNC) machine fault diagnosis, it not only can complete fault diagnosis correctly but also have fairly high error correction capability for disturbed Input Information sequence.Moreover MBAM model is a more convenient and effective method of solving the problem of CNC electric system fault diagnosis.
文摘The objective of this study is to develop an effective approach for product quality prediction in Computer Numerical Control turning of cantilever bars. A systematic predictive modelling procedure based on experimental investigations, neural network modelling and various statistical analysis tools is designed to produce the most accurate, practical and cost-effective prediction model. The modeling procedure begins by exploring the relationships between cutting parameters known to have an influence on quality characteristics of machined parts, such as dimensional errors, form errors and surface roughness, as well as their sensitivity to the process conditions. Based on these explorations and using numerous statistical tools, the most relevant variables to include in the prediction model are identified and fused using several artificial neural network architectures. An application on CNC turning of cantilever bars demonstrates that the proposed modeling procedure can be effectively and advantageously applied to quality characteristics prediction due to its simplicity, accuracy and efficiency. The experimental validation reveals that the resulting prediction model can correctly predict the quality characteristics of machined parts under variable machining conditions.
基金the China National Postdoctoral Program for Innovative Talents(Bx20200386)China Postdoctoral Science Foundation(2021M703586)+1 种基金Key Program of National Natural Science Foundation of China(52130401)National Natural Science Foundation of China(52204064,52104055)for financial support.
文摘Nanocellulose,a natural polymeric nanomaterial,has attracted significant attention in enhanced oil recovery(EOR)applications due to its abundance,nanoscale,high oil-water interfacial adsorption ef-ficiency.In this study,surface-functionalized cellulose nanocrystals(SF-CNCs)were prepared via hy-drochloric acid hydrolysis and chemical modification,with adaptable nanosize and considerable dispersion stability in low-permeability reservoirs.The SF-CNCs were structurally characterized by FT-IR,Cryo-TEM,which have a diameter of 5-10 nm and a length of 100-200 nm.The SF-CNC dispersions possessed higher stability and stronger salt-tolerance than those of corresponding CNC dispersions,due to the strong hydrophilicity of the sulfonic acid group.It was synergistically used with a non-ionic surfactant(APG1214)to formulate a combined flooding system(0.1 wt%SF-CNC+0.2 wt%APG1214).The combined flooding system exhibits strong emulsification stability,low oil-water interfacial tension of o.03 mN/m,and the ability to alter the wettability for oil-wetting rocks.Furthermore,the combined system was_able to provide an optimum EOR efficiency of 20.2%in low-permeability cores with 30.13×10^(-3)μm^(2).Notably.it can enlarge the sweep volume and increase the displacement efficiency simultaneously.Overall,the newly formulated nanocellulose/surfactant combined system exhibits a remarkable EoR performance in low-permeability reservoirs.
