The highly efficient manufacturing of atomic-scale smooth β-Ga_(2)O_(3)surface is fairly challenging because β-Ga_(2)O_(3)is a typical difficult-to-machine material.In this study,a novel plasma dry etching method na...The highly efficient manufacturing of atomic-scale smooth β-Ga_(2)O_(3)surface is fairly challenging because β-Ga_(2)O_(3)is a typical difficult-to-machine material.In this study,a novel plasma dry etching method named plasma-based atom-selective etching(PASE)is proposed to achieve the highly efficient,atomic-scale,and damage-free polishing of β-Ga_(2)O_(3).The plasma is excited through the inductive coupling principle and carbon tetrafluoride is utilized as the main reaction gas to etch β-Ga_(2)O_(3).The core of PASE polishing of β-Ga_(2)O_(3)is the remarkable lateral etching effect,which is ensured by both the intrinsic property of the surface and the extrinsic temperature condition.As revealed by density functional theory-based calculations,the intrinsic difference in the etching energy barrier of atoms at the step edge(2.36 eV)and in the terrace plane(4.37 eV)determines their difference in the etching rate,and their etching rate difference can be greatly enlarged by increasing the extrinsic temperature.The polishing of β-Ga_(2)O_(3)based on the lateral etching effect is further verified in the etching experiments.The Sa roughness of β-Ga_(2)O_(3)(001)substrate is reduced from 14.8 nm to 0.057 nm within 120 s,and the corresponding material removal rate reaches up to 20.96μm·min^(−1).The polished β-Ga_(2)O_(3)displays significantly improved crystalline quality and photoluminescence intensity,and the polishing effect of PASE is independent of the crystal face of β-Ga_(2)O_(3).In addition,the competition between chemical etching and physical reconstruction,which is determined by temperature and greatly affects the surface state of β-Ga_(2)O_(3),is deeply studied for the first time.These findings not only demonstrate the high-efficiency and high-quality polishing of β-Ga_(2)O_(3)via atmospheric plasma etching but also hold significant implications for guiding future plasma-based surface manufacturing of β-Ga_(2)O_(3).展开更多
Atomic-level manufacturing,as the "keystone" of future technology,marks the transformative shift from the micro/nano era based on "classical theory" to the atomic era grounded in "quantum theo...Atomic-level manufacturing,as the "keystone" of future technology,marks the transformative shift from the micro/nano era based on "classical theory" to the atomic era grounded in "quantum theory".It enables the precise control of matter arrangement and composition at the atomic scale,thereby achieving large-scale production of atomically precise and structured products.Electrochemical deposition(ECD),a typical "atom addition" fabrication method for electrochemical atomic and close-to-atomic scale manufacturing(EC-ACSM),enables precise control over material properties at the atomic scale,allowing breakthroughs in revolutionary performance of semiconductors,quantum computing,new materials,nanomedicine,etc.This review explores the fundamentals of EC-ACSM,particularly at the electrode/electrolyte interface,and investigates maskless ECD techniques,highlighting their advantages,limitations,and the role of in situ monitoring and advanced simulations in the process optimization.However,atomic electrochemical deposition faces significant challenges in precise control over atom-ion interactions,electrode-electrolyte interfacial dynamics,and surface defects.In the future,overcoming these obstacles is critical to advancing EC-ACSM and unlocking its full potential in scalability for industrial applications.EC-ACSM can drive the highly customized design of materials and offer strong technological support for the development of future science,ushering in a new atomic era of material innovation and device manufacturing.展开更多
We propose a method to measure the flatness of an object with a petal-like pattern generated by the interference of the measured orbital angular momentum(OAM)beam and the reference OAM beam which carries the opposite ...We propose a method to measure the flatness of an object with a petal-like pattern generated by the interference of the measured orbital angular momentum(OAM)beam and the reference OAM beam which carries the opposite OAM state.By calculating the difference between the petal rotation angle without/with the object,the thickness information of the object,and then the flatness information,can be evaluated.Furthermore,the direction of the object’s flatness can be determined by the petal’s clockwise/counterclockwise rotation.We theoretically analyze the relationship between the object’s thickness and petal rotation angle,and verify the proposed method by experiment.The experimental results show that the proposed method is a high precision flatness measurement and can obtain the convex/concave property of the flatness.For the 1.02 mm glass sample,the mean deviation of the flatness is 1.357×10^(-8) and the variance is 0.242×10^(-16).For the 0.50 mm glass sample,the mean deviation of the flatness is 1.931×10^(-8) and the variance is 2.405×10^(-16).Two different topological charges are adopted for the 2.00 mm glass sample,and their flatness deviations are 0.239×10^(-8)(ℓ=1)and 0.246×10^(-8)(ℓ=2),where their variances are 0.799×10^(-18)(ℓ=1)and 0.775×10^(-18)(ℓ=2),respectively.It is shown that the flatness measured by the proposed method is the same for the same sample when different topological charges are used.All results indicate that the proposed method may provide a high flatness measurement,and will be a promising way to measure the flatness.展开更多
Nanogrinding of SiC wafers with high flatness and low subsurface damage was proposed and nanogrinding experiments were carried out on an ultra precision grinding machine with fine diamond wheels. Experimental results ...Nanogrinding of SiC wafers with high flatness and low subsurface damage was proposed and nanogrinding experiments were carried out on an ultra precision grinding machine with fine diamond wheels. Experimental results show that nanogrinding can produce flatness less than 1.0μm and a surface roughness Ra of 0.42nm. It is found that nanogrinding is capable of producing much flatter SiC wafers with a lower damage than double side lapping and mechanical polishing in much less time and it can replace double side lapping and mechanical polishing and reduce the removal amount of chemical mechanical polishing.展开更多
It is necessary for precise measurement to estimate the uncertainty of measurement result. When measuring flatness error in close way by pitch, usually the uncertainty of measurement result is independently estimated ...It is necessary for precise measurement to estimate the uncertainty of measurement result. When measuring flatness error in close way by pitch, usually the uncertainty of measurement result is independently estimated according to pitch points. By analyzing a concrete example, this paper proposed that the uncertainty should be evaluated by the correlation calculating method. This approach greatly improved the deficiencies of the assessment method according to independent measurement and enhanced measurement precision. It provides a reference value for uncertainty assessment in leveling a flat.展开更多
Steel strips are the main of steel products and flatness is an important quality indicator of steel strips. Flatness control is the key and highly difficult technique of strip mills. The bottle-neck restricting the im...Steel strips are the main of steel products and flatness is an important quality indicator of steel strips. Flatness control is the key and highly difficult technique of strip mills. The bottle-neck restricting the improvement of flatness control techniques is that the research on flatness theories and control mathematic models is not in accordance with the requirement of technique developments. To build a simple, rapid and accurate explicit formulation control model has become an urgent need for the development of flatness control technique. This paper puts forward the conception of dynamic effective matrix based on the effective matrix method for flatness control proposed by the authors under the consideration of the influence of the change of parameters in roiling processes on the effective matrix, and the concept is validated by industrial productions. Three methods of the effective matrix generation are induced： the calculation method based on the flatness prediction model; the calculation method based on the data excavation in rolling processes and the direct calculation method based on the network model. A fuzzy neural network effective matrix model is built based on the clusters, and then the network structure is optimized and the high-speed-calculation problem of the dynamic effective matrix is solved. The flatness control scheme for cold strip mills is proposed based on the dynamic effective matrix. On stand 5 of the 1 220 mm five-stand 4-high cold strip tandem mill, the industrial experiment with the control methods of tilting roll and bending roll is done by the control scheme of the static effective matrix and the dynamic effective matrix, respectively. The experiment result proves that the control effect of the dynamic effective matrix is much better than that of the static effective matrix. This paper proposes a new idea and method for the dynamic flatness control in the rolling processes of cold strip mills and develops the theory and model of the flatness control effective matrix method.展开更多
The existing research of the flatness control for strip cold rolling mainly focuses on the calculation of the optimum adjustment of individual flatness actuator in accordance with the flatness deviation , which is use...The existing research of the flatness control for strip cold rolling mainly focuses on the calculation of the optimum adjustment of individual flatness actuator in accordance with the flatness deviation , which is used for general flatness control.As the basis of flatness control system , the efficiencies of flatness actuators provide a quantitative description to the law of flatness control.Therefore , the determination of actuator efficiency factors is crucial in flatness control.The strategies of closed loop feedback flatness control and rolling force feed-forward control were established respectively based on actuator efficiency factors.For the purpose of obtaining accurate efficiency factors matrixes of flatness actuators , a self-learning model of actuator efficiency factors was established.The precision of actuator efficiency factors can be improved continuously by the input of correlative measured flatness data.Meanwhile , the self-learning model of actuator efficiency factors permits the application of this flatness control for all possible types of actuators and every stand type.The application results show that the self-learning model is capable of obtaining good flatness.展开更多
In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by usi...In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by using theory and in-telligent methods synthetically. The network model for rapidly calculating the theory effective matrix is established by the BP network optimized by the particle swarm algorithm. The network model for rapidly calculating the meas- urement effective matrix is established by the RBF network optimized by the cluster algorithm. The flatness control model can track the practical situation of roiling process by on-line selVlearning. The scheme for flatness control quantity calculation is established by combining the theory control matrix and the measurement control matrix. The simulation result indicates that the establishment of theory-intelligent dynamic matrix model of flatness control with stable control process and high precision supplies a new way and method for studying flatness on-line control model.展开更多
For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-inpu...For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-input and three output signals was proposed with Legendre orthodoxy polynomial as basic pattern, based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm. The model not only had definite physical meanings in its inner nodes, but also had strong self-adaptability, anti interference ability, high recognition precision, and high velocity, thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient, practical, and novel method for flatness pattern recognition.展开更多
In connection with the characteristics of multi-disturbance and nonlinearity of a system for flatness control in cold rolling process, a new intelligent PID control algorithm was proposed based on a cloud model, neura...In connection with the characteristics of multi-disturbance and nonlinearity of a system for flatness control in cold rolling process, a new intelligent PID control algorithm was proposed based on a cloud model, neural network and fuzzy integration. By indeterminacy artificial intelligence, the problem of fixing the membership functions of input variables and fuzzy rules was solved in an actual fuzzy system and the nonlinear mapping between variables was implemented by neural network. The algorithm has the adaptive learning ability of neural network and the indetermi- nacy of a cloud model in processing knowledge, which makes the fuzzy system have more persuasion in the process of knowledge inference, realizing the online adaptive regulation of PID parameters and avoiding the defects of the traditional PID controller. Simulation results show that the algorithm is simple, fast and robust with good control performance and application value.展开更多
In this article, we establish the route taken by the author, and his research group, to bring differential flatness to the realm of active disturbance rejection control （ADRC）. This avenue entitled： 1） generalized...In this article, we establish the route taken by the author, and his research group, to bring differential flatness to the realm of active disturbance rejection control （ADRC）. This avenue entitled： 1） generalized proportional integral observers （GPIO）, as natural state and disturbance observers for fiat systems, 2） generalized proportional integral （GPI） control, provided with extra integrations, to produce a modular controller known as flat filters （FF＇s） and, finally, 3） the establishing of an equivalence of observer based ADRC with FF＇s. The context is that of pure integration systems. The obtained controllers depend only on the order of the flat system and they are to be directly used on the basis of the available flat output signal in a universal, modular, fashion. The map is complemented with the relevant references where the intermediate techniques were illustrated and developed, over the years, in connection with laboratory experimental implementations.展开更多
In flatness measuring system, the flatness measuring signal can be affected by the deflection of flatness measuring roll. The stress on flatness measuring roll was analyzed and a deflection model for the flatness meas...In flatness measuring system, the flatness measuring signal can be affected by the deflection of flatness measuring roll. The stress on flatness measuring roll was analyzed and a deflection model for the flatness measuring roll was obtained by using the influence function method. The model was developed on the basis of the deformation of flatness measuring roll in roiling process and compensation curve was obtained. The results indicated that the set curve of flatness is in good agreement with the online measured curve of flatness, and good strip flatness can be obtained.展开更多
In cold rolling process,the flatness actuator efficiency is the basis of the flatness control system.The precision of flatness is determined by the setpoints of flatness actuators.In the presence of modeling uncertain...In cold rolling process,the flatness actuator efficiency is the basis of the flatness control system.The precision of flatness is determined by the setpoints of flatness actuators.In the presence of modeling uncertainties and unmodeled nonlinearities in rolling process,it is difficult to obtain efficiency factors and setpoints of flatness actuators accurately.Based on the production data,a method to obtain the flatness actuator efficiency by using partial least square(PLS)combined with orthogonal signal correction(OSC)was adopted.Compared with the experiential method and principal component analysis method,the OSC-PLS method shows superior performance in obtaining the flatness actuator efficiency factors at the last stand.Furthermore,kernel partial least square combined with artificial neural network(KPLS-ANN)was proposed to predict the flatness values and optimize the setpoints of flatness actuators.Compared with KPLS or ANN,KPLS-ANN shows the best predictive ability.The root mean square error,mean absolute error and mean absolute percentage error are 0.51 IU,0.34 IU and 0.09,respectively.After the setpoints of flatness actuators are optimized,KPLS-ANN shows better optimization ability.The result in an average flatness standard deviation is 2.22 IU,while the unoptimized value is 4.10 IU.展开更多
The strip flatness and crown control model is the foundation of automatic strip shape control. Considering the metal transverse flows and the inter stand second deformation, the trip flatness and crown control model h...The strip flatness and crown control model is the foundation of automatic strip shape control. Considering the metal transverse flows and the inter stand second deformation, the trip flatness and crown control model has been developed, which can be applied to CVC mills and PC mills as well as normal four-high mills. The strip flatness and crown control model has high precision, and has been successfully applied to the automatic strip shape control system reconstruction of Tangshan Ganglu 1 250 mm hot strip plant.展开更多
Non-uniformity of temperature distribution across strip width direction is the ultimate reason why the flatness defect occurs on the strip after cooling process although the strip is flat at the exit of finishing mill...Non-uniformity of temperature distribution across strip width direction is the ultimate reason why the flatness defect occurs on the strip after cooling process although the strip is flat at the exit of finishing mill.One thermal , microstructural and mechanical coupling analysis model for predicting flatness change of steel strip during the run-out table cooling process was established using ABAQUS finite element software.K Esaka phase transformation kinetics model was employed to calculate the phase transformation , and coupled with temperature calculation using the user subroutine program HETVAL.Elasto-plasticity constitutive equations of steel material , in which conventional elastic and plastic strains , thermal strain , phase transformation strain and transformation induced plastic strain were considered , were derived and programmed in the user subroutine program UMAT.The conclusion that flatness of steel strip will develop to edge wave defect under the functions of the differential thermal and microstructural behaviors across strip width during the run-out table cooling procedure was acquired through the analysis results of this model.Calculation results of this analysis model agree well with the actual measurements and observation.展开更多
Using the effective matrix methods of flatness and profile control synthetically, the flatness and profile in- tegration control scheme for tandem cold mills is built in order to increase flatness and profile control ...Using the effective matrix methods of flatness and profile control synthetically, the flatness and profile in- tegration control scheme for tandem cold mills is built in order to increase flatness and profile control precision of tan- dem cold mills. Corresponding control strategies are adopted for various control objectives of different stands and the coordination control strategies of various stands are given, which makes the on-line flatness control cooperate with on-line profile control and implements the parallel control of different stands. According to the measured flatness and profile data of some 1550 mm tandem cold mills, the control scheme is verified and the result indicates that the scheme has high flatness and profile control precision with steady and reliable control process. A new way and method is supplied for researching shade control of tandem cold mills.展开更多
A simple plate crown model was introduced,and the crown-flatness vector analysis method was analyzed.Based on the plate rolling technology,the rolling schedule design of elongation phase is divided into three steps.Fi...A simple plate crown model was introduced,and the crown-flatness vector analysis method was analyzed.Based on the plate rolling technology,the rolling schedule design of elongation phase is divided into three steps.First step is to calculate the reductions of first pass of elongation making full use of the mill capability to decrease the total pass number.The second step is to calculate the pass reduction for the last three or four passes to control crown and flatness by crown-flatness vector analysis method.In the third step,the maximum rolling force limit and the total pass number are adjusted to make the plate gauge at exit equal to target gauge with satisfactory flatness.The on-line application shows that this method is effective.展开更多
In the traditional flatness pattern recognition neural network, the topologic configurations need to be rebuilt with a changing width of cold strip. Furthermore, the large learning assignment, slow convergence, and lo...In the traditional flatness pattern recognition neural network, the topologic configurations need to be rebuilt with a changing width of cold strip. Furthermore, the large learning assignment, slow convergence, and local minimum in the network are observed. Moreover, going by the structure of the traditional neural network, according to experience, the model is time-consuming and complex. Thus, a new approach of flatness pattern recognition is proposed based on the CMAC （cerebellar model articulation controllers） neural network. The difference in fuzzy distances between samples and the basic patterns is introduced as the input of the CMAC network. Simultaneously, the adequate learning rate is improved in the error correction algorithm of this neural network. The new approach with advantages, such as high learning speed, good generalization, and easy implementation, is efficient and intelligent. The simulation results show that the speed and accuracy of the flatness pattern recognition model are obviously im proved.展开更多
To adapt to the new requirement of the developing flatness control theory and technology, cubic patterns were introduced on the basis of the traditional linear, quadratic and quartic flatness basic patterns. Linear, q...To adapt to the new requirement of the developing flatness control theory and technology, cubic patterns were introduced on the basis of the traditional linear, quadratic and quartic flatness basic patterns. Linear, quadratic, cubic and quartic Legendre orthogonal polynomials were adopted to express the flatness basic patterns. In order to over- come the defects live in the existent recognition methods based on fuzzy, neural network and support vector regres- sion （SVR） theory, a novel flatness pattern recognition method based on least squares support vector regression （LS-SVR） was proposed. On this basis, for the purpose of determining the hyper-parameters of LS-SVR effectively and enhan- cing the recognition accuracy and generalization performance of the model, particle swarm optimization algorithm with leave-one-out （LOO） error as fitness function was adopted. To overcome the disadvantage of high computational complexity of naive cross-validation algorithm, a novel fast cross-validation algorithm was introduced to calculate the LOO error of LDSVR. Results of experiments on flatness data calculated by theory and a 900HC cold-rolling mill practically measured flatness signals demonstrate that the proposed approach can distinguish the types and define the magnitudes of the flatness defects effectively with high accuracy, high speed and strong generalization ability.展开更多
The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digita...The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.展开更多
基金supported by the National Natural Science Foundation of China(52375437,52035009)the Natural Science Foundation of Guangdong Province(2024B1515020027)+2 种基金the Shenzhen Science and Technology Program(Grant No.KQTD20170810110250357)for the financial supportthe assistance of SUSTech Core Research Facilitiessupported by Shenzhen Engineering Research Center for Semiconductorspecific Equipment。
文摘The highly efficient manufacturing of atomic-scale smooth β-Ga_(2)O_(3)surface is fairly challenging because β-Ga_(2)O_(3)is a typical difficult-to-machine material.In this study,a novel plasma dry etching method named plasma-based atom-selective etching(PASE)is proposed to achieve the highly efficient,atomic-scale,and damage-free polishing of β-Ga_(2)O_(3).The plasma is excited through the inductive coupling principle and carbon tetrafluoride is utilized as the main reaction gas to etch β-Ga_(2)O_(3).The core of PASE polishing of β-Ga_(2)O_(3)is the remarkable lateral etching effect,which is ensured by both the intrinsic property of the surface and the extrinsic temperature condition.As revealed by density functional theory-based calculations,the intrinsic difference in the etching energy barrier of atoms at the step edge(2.36 eV)and in the terrace plane(4.37 eV)determines their difference in the etching rate,and their etching rate difference can be greatly enlarged by increasing the extrinsic temperature.The polishing of β-Ga_(2)O_(3)based on the lateral etching effect is further verified in the etching experiments.The Sa roughness of β-Ga_(2)O_(3)(001)substrate is reduced from 14.8 nm to 0.057 nm within 120 s,and the corresponding material removal rate reaches up to 20.96μm·min^(−1).The polished β-Ga_(2)O_(3)displays significantly improved crystalline quality and photoluminescence intensity,and the polishing effect of PASE is independent of the crystal face of β-Ga_(2)O_(3).In addition,the competition between chemical etching and physical reconstruction,which is determined by temperature and greatly affects the surface state of β-Ga_(2)O_(3),is deeply studied for the first time.These findings not only demonstrate the high-efficiency and high-quality polishing of β-Ga_(2)O_(3)via atmospheric plasma etching but also hold significant implications for guiding future plasma-based surface manufacturing of β-Ga_(2)O_(3).
基金the support from the National Natural Science Foundation of China (Grant Nos. 52405447 and 52275299)the National Key Research and Development Program of China (Grant No. 2021YFB1716200)the Key Research and Development Program of Jiangxi Province in China (Grant No. 20232BBE50011)。
文摘Atomic-level manufacturing,as the "keystone" of future technology,marks the transformative shift from the micro/nano era based on "classical theory" to the atomic era grounded in "quantum theory".It enables the precise control of matter arrangement and composition at the atomic scale,thereby achieving large-scale production of atomically precise and structured products.Electrochemical deposition(ECD),a typical "atom addition" fabrication method for electrochemical atomic and close-to-atomic scale manufacturing(EC-ACSM),enables precise control over material properties at the atomic scale,allowing breakthroughs in revolutionary performance of semiconductors,quantum computing,new materials,nanomedicine,etc.This review explores the fundamentals of EC-ACSM,particularly at the electrode/electrolyte interface,and investigates maskless ECD techniques,highlighting their advantages,limitations,and the role of in situ monitoring and advanced simulations in the process optimization.However,atomic electrochemical deposition faces significant challenges in precise control over atom-ion interactions,electrode-electrolyte interfacial dynamics,and surface defects.In the future,overcoming these obstacles is critical to advancing EC-ACSM and unlocking its full potential in scalability for industrial applications.EC-ACSM can drive the highly customized design of materials and offer strong technological support for the development of future science,ushering in a new atomic era of material innovation and device manufacturing.
基金supported by the National Natural Science Foundation of China(Grant No.62375140)the Open Research Fund of National Laboratory of Solid State Microstructures(Grant No.M36055).
文摘We propose a method to measure the flatness of an object with a petal-like pattern generated by the interference of the measured orbital angular momentum(OAM)beam and the reference OAM beam which carries the opposite OAM state.By calculating the difference between the petal rotation angle without/with the object,the thickness information of the object,and then the flatness information,can be evaluated.Furthermore,the direction of the object’s flatness can be determined by the petal’s clockwise/counterclockwise rotation.We theoretically analyze the relationship between the object’s thickness and petal rotation angle,and verify the proposed method by experiment.The experimental results show that the proposed method is a high precision flatness measurement and can obtain the convex/concave property of the flatness.For the 1.02 mm glass sample,the mean deviation of the flatness is 1.357×10^(-8) and the variance is 0.242×10^(-16).For the 0.50 mm glass sample,the mean deviation of the flatness is 1.931×10^(-8) and the variance is 2.405×10^(-16).Two different topological charges are adopted for the 2.00 mm glass sample,and their flatness deviations are 0.239×10^(-8)(ℓ=1)and 0.246×10^(-8)(ℓ=2),where their variances are 0.799×10^(-18)(ℓ=1)and 0.775×10^(-18)(ℓ=2),respectively.It is shown that the flatness measured by the proposed method is the same for the same sample when different topological charges are used.All results indicate that the proposed method may provide a high flatness measurement,and will be a promising way to measure the flatness.
基金Project (50975040) supported by the National Natural Science Foundation of China
文摘Nanogrinding of SiC wafers with high flatness and low subsurface damage was proposed and nanogrinding experiments were carried out on an ultra precision grinding machine with fine diamond wheels. Experimental results show that nanogrinding can produce flatness less than 1.0μm and a surface roughness Ra of 0.42nm. It is found that nanogrinding is capable of producing much flatter SiC wafers with a lower damage than double side lapping and mechanical polishing in much less time and it can replace double side lapping and mechanical polishing and reduce the removal amount of chemical mechanical polishing.
文摘It is necessary for precise measurement to estimate the uncertainty of measurement result. When measuring flatness error in close way by pitch, usually the uncertainty of measurement result is independently estimated according to pitch points. By analyzing a concrete example, this paper proposed that the uncertainty should be evaluated by the correlation calculating method. This approach greatly improved the deficiencies of the assessment method according to independent measurement and enhanced measurement precision. It provides a reference value for uncertainty assessment in leveling a flat.
基金supported by National Natural Science Foundation of China(Grant No. 50675186)Hebei Provincial Major Natural Science Foundation of China (Grant No. E2006001038)
文摘Steel strips are the main of steel products and flatness is an important quality indicator of steel strips. Flatness control is the key and highly difficult technique of strip mills. The bottle-neck restricting the improvement of flatness control techniques is that the research on flatness theories and control mathematic models is not in accordance with the requirement of technique developments. To build a simple, rapid and accurate explicit formulation control model has become an urgent need for the development of flatness control technique. This paper puts forward the conception of dynamic effective matrix based on the effective matrix method for flatness control proposed by the authors under the consideration of the influence of the change of parameters in roiling processes on the effective matrix, and the concept is validated by industrial productions. Three methods of the effective matrix generation are induced： the calculation method based on the flatness prediction model; the calculation method based on the data excavation in rolling processes and the direct calculation method based on the network model. A fuzzy neural network effective matrix model is built based on the clusters, and then the network structure is optimized and the high-speed-calculation problem of the dynamic effective matrix is solved. The flatness control scheme for cold strip mills is proposed based on the dynamic effective matrix. On stand 5 of the 1 220 mm five-stand 4-high cold strip tandem mill, the industrial experiment with the control methods of tilting roll and bending roll is done by the control scheme of the static effective matrix and the dynamic effective matrix, respectively. The experiment result proves that the control effect of the dynamic effective matrix is much better than that of the static effective matrix. This paper proposes a new idea and method for the dynamic flatness control in the rolling processes of cold strip mills and develops the theory and model of the flatness control effective matrix method.
基金Item Sponsored by National Science and Technology Support Plan of China ( 2011BAF15B01 , 2011BAF15B03 )Provincial Natural Science Foundation of Hebei of China ( E2011203004 )
文摘The existing research of the flatness control for strip cold rolling mainly focuses on the calculation of the optimum adjustment of individual flatness actuator in accordance with the flatness deviation , which is used for general flatness control.As the basis of flatness control system , the efficiencies of flatness actuators provide a quantitative description to the law of flatness control.Therefore , the determination of actuator efficiency factors is crucial in flatness control.The strategies of closed loop feedback flatness control and rolling force feed-forward control were established respectively based on actuator efficiency factors.For the purpose of obtaining accurate efficiency factors matrixes of flatness actuators , a self-learning model of actuator efficiency factors was established.The precision of actuator efficiency factors can be improved continuously by the input of correlative measured flatness data.Meanwhile , the self-learning model of actuator efficiency factors permits the application of this flatness control for all possible types of actuators and every stand type.The application results show that the self-learning model is capable of obtaining good flatness.
基金Item Sponsored by National High-Tech Research and Development Project of China(2009AA04Z143)Natural Science Foundation of Hebei Province of China(E2006001038)Hebei Provincial Science and Technology Project of China(10212101D)
文摘In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by using theory and in-telligent methods synthetically. The network model for rapidly calculating the theory effective matrix is established by the BP network optimized by the particle swarm algorithm. The network model for rapidly calculating the meas- urement effective matrix is established by the RBF network optimized by the cluster algorithm. The flatness control model can track the practical situation of roiling process by on-line selVlearning. The scheme for flatness control quantity calculation is established by combining the theory control matrix and the measurement control matrix. The simulation result indicates that the establishment of theory-intelligent dynamic matrix model of flatness control with stable control process and high precision supplies a new way and method for studying flatness on-line control model.
基金Item Sponsored by National Natural Science Foundation of China and Shanghai Baosteel Group Co(50675186)Provincial Natural Science Foundation of Hebei Province of China(E2006001038)
文摘For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-input and three output signals was proposed with Legendre orthodoxy polynomial as basic pattern, based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm. The model not only had definite physical meanings in its inner nodes, but also had strong self-adaptability, anti interference ability, high recognition precision, and high velocity, thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient, practical, and novel method for flatness pattern recognition.
基金Sponsored by National High-tech Research and Development Project of China(2009AA04Z143)Natural Science Foundation of Hebei Province of China(E2006001038)Science and Technology Project of Hebei Province of China(10212101D)
文摘In connection with the characteristics of multi-disturbance and nonlinearity of a system for flatness control in cold rolling process, a new intelligent PID control algorithm was proposed based on a cloud model, neural network and fuzzy integration. By indeterminacy artificial intelligence, the problem of fixing the membership functions of input variables and fuzzy rules was solved in an actual fuzzy system and the nonlinear mapping between variables was implemented by neural network. The algorithm has the adaptive learning ability of neural network and the indetermi- nacy of a cloud model in processing knowledge, which makes the fuzzy system have more persuasion in the process of knowledge inference, realizing the online adaptive regulation of PID parameters and avoiding the defects of the traditional PID controller. Simulation results show that the algorithm is simple, fast and robust with good control performance and application value.
文摘In this article, we establish the route taken by the author, and his research group, to bring differential flatness to the realm of active disturbance rejection control （ADRC）. This avenue entitled： 1） generalized proportional integral observers （GPIO）, as natural state and disturbance observers for fiat systems, 2） generalized proportional integral （GPI） control, provided with extra integrations, to produce a modular controller known as flat filters （FF＇s） and, finally, 3） the establishing of an equivalence of observer based ADRC with FF＇s. The context is that of pure integration systems. The obtained controllers depend only on the order of the flat system and they are to be directly used on the basis of the available flat output signal in a universal, modular, fashion. The map is complemented with the relevant references where the intermediate techniques were illustrated and developed, over the years, in connection with laboratory experimental implementations.
基金Item Sponsored by National Natural Science Foundation of China(50534020)
文摘In flatness measuring system, the flatness measuring signal can be affected by the deflection of flatness measuring roll. The stress on flatness measuring roll was analyzed and a deflection model for the flatness measuring roll was obtained by using the influence function method. The model was developed on the basis of the deformation of flatness measuring roll in roiling process and compensation curve was obtained. The results indicated that the set curve of flatness is in good agreement with the online measured curve of flatness, and good strip flatness can be obtained.
基金This study is financially supported by the National Key Research and Development Program of China(No.2017YFB0304100)the National Natural Science Foundation of China(Nos.51774084,51704067,and 51634002)+1 种基金the Fundamental Research Funds for the Central Universities(Nos.N160704004,N170708020,and N2004010)Liaoning Revitalization Talents Program(XLYC1907065).
文摘In cold rolling process,the flatness actuator efficiency is the basis of the flatness control system.The precision of flatness is determined by the setpoints of flatness actuators.In the presence of modeling uncertainties and unmodeled nonlinearities in rolling process,it is difficult to obtain efficiency factors and setpoints of flatness actuators accurately.Based on the production data,a method to obtain the flatness actuator efficiency by using partial least square(PLS)combined with orthogonal signal correction(OSC)was adopted.Compared with the experiential method and principal component analysis method,the OSC-PLS method shows superior performance in obtaining the flatness actuator efficiency factors at the last stand.Furthermore,kernel partial least square combined with artificial neural network(KPLS-ANN)was proposed to predict the flatness values and optimize the setpoints of flatness actuators.Compared with KPLS or ANN,KPLS-ANN shows the best predictive ability.The root mean square error,mean absolute error and mean absolute percentage error are 0.51 IU,0.34 IU and 0.09,respectively.After the setpoints of flatness actuators are optimized,KPLS-ANN shows better optimization ability.The result in an average flatness standard deviation is 2.22 IU,while the unoptimized value is 4.10 IU.
基金Item Sponsored by National Natural Science Foundation of China (50534020)
文摘The strip flatness and crown control model is the foundation of automatic strip shape control. Considering the metal transverse flows and the inter stand second deformation, the trip flatness and crown control model has been developed, which can be applied to CVC mills and PC mills as well as normal four-high mills. The strip flatness and crown control model has high precision, and has been successfully applied to the automatic strip shape control system reconstruction of Tangshan Ganglu 1 250 mm hot strip plant.
文摘Non-uniformity of temperature distribution across strip width direction is the ultimate reason why the flatness defect occurs on the strip after cooling process although the strip is flat at the exit of finishing mill.One thermal , microstructural and mechanical coupling analysis model for predicting flatness change of steel strip during the run-out table cooling process was established using ABAQUS finite element software.K Esaka phase transformation kinetics model was employed to calculate the phase transformation , and coupled with temperature calculation using the user subroutine program HETVAL.Elasto-plasticity constitutive equations of steel material , in which conventional elastic and plastic strains , thermal strain , phase transformation strain and transformation induced plastic strain were considered , were derived and programmed in the user subroutine program UMAT.The conclusion that flatness of steel strip will develop to edge wave defect under the functions of the differential thermal and microstructural behaviors across strip width during the run-out table cooling procedure was acquired through the analysis results of this model.Calculation results of this analysis model agree well with the actual measurements and observation.
基金Sponsored by National High-Tech Research and Development Project of China (2009AA04Z143)Hebei Provincial Great Natural Science Foundation of China (E2006001038)Hebei Provincial Science and Technology Project of China (10212101D)
文摘Using the effective matrix methods of flatness and profile control synthetically, the flatness and profile in- tegration control scheme for tandem cold mills is built in order to increase flatness and profile control precision of tan- dem cold mills. Corresponding control strategies are adopted for various control objectives of different stands and the coordination control strategies of various stands are given, which makes the on-line flatness control cooperate with on-line profile control and implements the parallel control of different stands. According to the measured flatness and profile data of some 1550 mm tandem cold mills, the control scheme is verified and the result indicates that the scheme has high flatness and profile control precision with steady and reliable control process. A new way and method is supplied for researching shade control of tandem cold mills.
基金Item Sponsored by National Natural Science Foundation of China(50104004)
文摘A simple plate crown model was introduced,and the crown-flatness vector analysis method was analyzed.Based on the plate rolling technology,the rolling schedule design of elongation phase is divided into three steps.First step is to calculate the reductions of first pass of elongation making full use of the mill capability to decrease the total pass number.The second step is to calculate the pass reduction for the last three or four passes to control crown and flatness by crown-flatness vector analysis method.In the third step,the maximum rolling force limit and the total pass number are adjusted to make the plate gauge at exit equal to target gauge with satisfactory flatness.The on-line application shows that this method is effective.
基金National Natural Science Foundation of China (50675186)
文摘In the traditional flatness pattern recognition neural network, the topologic configurations need to be rebuilt with a changing width of cold strip. Furthermore, the large learning assignment, slow convergence, and local minimum in the network are observed. Moreover, going by the structure of the traditional neural network, according to experience, the model is time-consuming and complex. Thus, a new approach of flatness pattern recognition is proposed based on the CMAC （cerebellar model articulation controllers） neural network. The difference in fuzzy distances between samples and the basic patterns is introduced as the input of the CMAC network. Simultaneously, the adequate learning rate is improved in the error correction algorithm of this neural network. The new approach with advantages, such as high learning speed, good generalization, and easy implementation, is efficient and intelligent. The simulation results show that the speed and accuracy of the flatness pattern recognition model are obviously im proved.
基金Sponsored by National Natural Science Foundation of China (50675186)
文摘To adapt to the new requirement of the developing flatness control theory and technology, cubic patterns were introduced on the basis of the traditional linear, quadratic and quartic flatness basic patterns. Linear, quadratic, cubic and quartic Legendre orthogonal polynomials were adopted to express the flatness basic patterns. In order to over- come the defects live in the existent recognition methods based on fuzzy, neural network and support vector regres- sion （SVR） theory, a novel flatness pattern recognition method based on least squares support vector regression （LS-SVR） was proposed. On this basis, for the purpose of determining the hyper-parameters of LS-SVR effectively and enhan- cing the recognition accuracy and generalization performance of the model, particle swarm optimization algorithm with leave-one-out （LOO） error as fitness function was adopted. To overcome the disadvantage of high computational complexity of naive cross-validation algorithm, a novel fast cross-validation algorithm was introduced to calculate the LOO error of LDSVR. Results of experiments on flatness data calculated by theory and a 900HC cold-rolling mill practically measured flatness signals demonstrate that the proposed approach can distinguish the types and define the magnitudes of the flatness defects effectively with high accuracy, high speed and strong generalization ability.
基金Project(E2015203354)supported by Natural Science Foundation of Steel United Research Fund of Hebei Province,ChinaProject(ZD2016100)supported by the Science and the Technology Research Key Project of High School of Hebei Province,China+1 种基金Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,ChinaProject(16LGY015)supported by the Basic Research Special Breeding of Yanshan University,China
文摘The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.
