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
To achieve stable rolling,the influence of a tension mechanism of a large diameter ratio roll system on the rolling process of a strip flatness electromagnetic control rolling mill is studied.Through the analysis of t...To achieve stable rolling,the influence of a tension mechanism of a large diameter ratio roll system on the rolling process of a strip flatness electromagnetic control rolling mill is studied.Through the analysis of the rolling deformation zone,the deformation zone composition form of a large diameter ratio roll system and a calculation formula of neutral angle under tension are proposed.To analyze the effect of front and post tensions on the rolling characteristic and the strip flatness control characteristic,a three-dimensional rolling finite element(FE)model of a large diameter ratio roll system with the function of roll profile electromagnetic control is established by FE software and verified by a strip flatness electromagnetic control rolling mill.Based on the model,the strip thickness characteristic,metal transverse flow,strip flatness state,and adjustment range of the loaded roll gap are analyzed for different front and post tensions setting values.The results show that changing the front or post tension setting values can improve the single-pass reduction rate of a large diameter ratio roll system and have little effect on the flatness control ability of the strip flatness electromagnetic control rolling mill.展开更多
Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model wit...Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model with deep semantic segmentation networks is established.The interference areas in the real flatness image can be eliminated by the SLD model,and valid information can be retained.On this basis,the concept of image flatness is proposed for the first time.An image flatness representation(IFAR)model is established on the basis of an autoencoder with a new structure.The optimal structure of the bottleneck layer is 16×16×4,and the IFAR model exhibits a good representation effect.Moreover,interpretability analysis of the representation factors is carried out,and the difference and physical meaning of the representation factors for image flatness with different categories are analyzed.Image flatness with new defect morphologies(bilateral quarter waves and large middle waves)that are not present in the original dataset are generated by modifying the representation factors of the no wave image.Lastly,the SLD and IFAR models are used to detect and represent all the real flatness images on the test set.The average processing time for a single image is 11.42 ms,which is suitable for industrial applications.The research results provide effective methods and ideas for intelligent flatness detection technology based on machine vision.展开更多
Aiming at the problem of insufficient prediction accuracy of strip flatness at the outlet of cold tandem rolling,the prediction performance of strip flatness based on different ensemble methods was studied and a high-...Aiming at the problem of insufficient prediction accuracy of strip flatness at the outlet of cold tandem rolling,the prediction performance of strip flatness based on different ensemble methods was studied and a high-precision prediction ensemble model of strip flatness at the outlet was established.Firstly,based on linear regression(LR),K nearest neighbors(KNN),support vector regression,regression trees(RT),and backpropagation neural network(BPN),bagging,boosting,and stacking ensemble methods were used for ensemble experiments.Secondly,three existing ensemble models,i.e.,random forest,extreme random tree(ET)and extreme gradient boosting,were used to conduct experiments and compare the results.The research shows that bagging,boosting,and stacking three ensemble methods have the most significant improvement in the prediction accuracy of the regression trees model,which is increased by 5.28%,6.51%,and 5.32%,respectively.At the same time,the stacking ensemble method improves both the simple model and the complex model,and the improvement effect on the simple base model is the greatest,which is 4.69%higher than that of the base model KNN.Comparing all of the ensemble models,the stacking ensemble model of level-1(ET,AdaBoost-RT,LR,BPN)paired with level-2(LR)was discovered to be the best model(EALB-LR)and can be further studied for industrial applications.展开更多
A non-contact method for millimeter-scale inspection of material surface flatness via Laser-Induced Breakdown Spectroscopy(LIBS)is investigated experimentally.The experiment is performed using a planished surface of a...A non-contact method for millimeter-scale inspection of material surface flatness via Laser-Induced Breakdown Spectroscopy(LIBS)is investigated experimentally.The experiment is performed using a planished surface of an alloy steel sample to simulate its various flatness,ranging from 0 to 4.4 mm,by adjusting the laser focal plane to the surface distance with a step length of 0.2 mm.It is found that LIBS measurements are successful in inspecting the flatness differences among these simulated cases,implying that the method investigated here is feasible.It is also found that,for achieving the inspection of surface flatness within such a wide range,when univariate analysis is applied,a piecewise calibration model must be constructed.This is due to the complex dependence of plasma formation conditions on the surface flatness,which inevitably complicates the inspection procedure.To solve the problem,a multivariate analysis with the help of Back-Propagation Neural Network(BPNN)algorithms is applied to further construct the calibration model.By detailed analysis of the model performance,we demonstrate that a unified calibration model can be well established based on BPNN algorithms for unambiguous millimeter-scale range inspection of surface flatness with a resolution of about 0.2 mm.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
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
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
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
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
The dynamic model of cold rolling mill based on strip flatness and thickness integrated control was proposed,containing the following sub-models:the rolling process model,the dynamic model of rolls along axial directi...The dynamic model of cold rolling mill based on strip flatness and thickness integrated control was proposed,containing the following sub-models:the rolling process model,the dynamic model of rolls along axial direction,and the compensation model.Based on the rule of volume flow rate,the dynamic rolling process model was built.The work roll and backup roll were taken as elastic continuous bodies,the effect of shear and moment of inertia were taken into consideration,and then the dynamic model of rolls was built.The two models were coupled together,and the dynamic model of rolling mill was built.In the dynamic model,the thermal expansion of the rolls,the wear of the rolls and other related parameters can not be considered.In order to compensate the dynamic model,the coupled static model of rolls and strip was applied.Then,according to the inner relationship of these models,the dynamic model and the compensation model were coupled,and the dynamic model of rolling mill based on the strip flatness and thickness integrated control was built.The dynamic simulation of the rolling process was made,and the dynamic thickness and the dynamic flatness information were obtained.This model not only provides a theory basis for the virtual rolling,but also provides a platform for the application of advanced control theory.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
The roll contour pattern and variety of work and backup rolls in service and its effect on profile and flatness control performance in 1 700 mm hot strip mill at Wuhan Iron and Steel(Group) Corporation were tested and...The roll contour pattern and variety of work and backup rolls in service and its effect on profile and flatness control performance in 1 700 mm hot strip mill at Wuhan Iron and Steel(Group) Corporation were tested and analyzed by the developed finite element models of different typical roll contours configurations.A rather smooth local work roll contour near strip edges and an increase in rolled length can be obtained by application of long stroke work roll shifting system with conventional work roll contours that is incapable of the crown control.In comparison with the conventional backup and work roll contours configuration,the crown control range by the roll bending force enhances by 12.79% and the roll gap stiffness increases by 25.26% with the developed asymmetry self-compensating work rolls(ASR) and varying contact backup rolls(VCR).A better strip profile and flatness quality,an increase in coil numbers within the rolling campaign and a significant alleviated effect of severe work roll wear contours on performance of edge drop control are achieved by the application of ASR with crown control and wear control ability in downstream stand F5 and VCR in all stands of 1 700 mm hot strip mill.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
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
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
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
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supported by the Natural Science Foundation of Hebei Province of China(Grant No.E2021203129).
文摘To achieve stable rolling,the influence of a tension mechanism of a large diameter ratio roll system on the rolling process of a strip flatness electromagnetic control rolling mill is studied.Through the analysis of the rolling deformation zone,the deformation zone composition form of a large diameter ratio roll system and a calculation formula of neutral angle under tension are proposed.To analyze the effect of front and post tensions on the rolling characteristic and the strip flatness control characteristic,a three-dimensional rolling finite element(FE)model of a large diameter ratio roll system with the function of roll profile electromagnetic control is established by FE software and verified by a strip flatness electromagnetic control rolling mill.Based on the model,the strip thickness characteristic,metal transverse flow,strip flatness state,and adjustment range of the loaded roll gap are analyzed for different front and post tensions setting values.The results show that changing the front or post tension setting values can improve the single-pass reduction rate of a large diameter ratio roll system and have little effect on the flatness control ability of the strip flatness electromagnetic control rolling mill.
基金supported by the National Natural Science Foundation of China(No.U21A20118)the National Key Laboratory of Metal Forming Technology and Heavy Equipment,China National Heavy Machinery Research Institute Co.,Ltd.(No.S2208100.W04).
文摘Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model with deep semantic segmentation networks is established.The interference areas in the real flatness image can be eliminated by the SLD model,and valid information can be retained.On this basis,the concept of image flatness is proposed for the first time.An image flatness representation(IFAR)model is established on the basis of an autoencoder with a new structure.The optimal structure of the bottleneck layer is 16×16×4,and the IFAR model exhibits a good representation effect.Moreover,interpretability analysis of the representation factors is carried out,and the difference and physical meaning of the representation factors for image flatness with different categories are analyzed.Image flatness with new defect morphologies(bilateral quarter waves and large middle waves)that are not present in the original dataset are generated by modifying the representation factors of the no wave image.Lastly,the SLD and IFAR models are used to detect and represent all the real flatness images on the test set.The average processing time for a single image is 11.42 ms,which is suitable for industrial applications.The research results provide effective methods and ideas for intelligent flatness detection technology based on machine vision.
基金This study was supported by the National Key Research and Development Program of China(No.2017YFB0304100)Key Projects of the National Natural Science Foundation of China(No.51634002).
文摘Aiming at the problem of insufficient prediction accuracy of strip flatness at the outlet of cold tandem rolling,the prediction performance of strip flatness based on different ensemble methods was studied and a high-precision prediction ensemble model of strip flatness at the outlet was established.Firstly,based on linear regression(LR),K nearest neighbors(KNN),support vector regression,regression trees(RT),and backpropagation neural network(BPN),bagging,boosting,and stacking ensemble methods were used for ensemble experiments.Secondly,three existing ensemble models,i.e.,random forest,extreme random tree(ET)and extreme gradient boosting,were used to conduct experiments and compare the results.The research shows that bagging,boosting,and stacking three ensemble methods have the most significant improvement in the prediction accuracy of the regression trees model,which is increased by 5.28%,6.51%,and 5.32%,respectively.At the same time,the stacking ensemble method improves both the simple model and the complex model,and the improvement effect on the simple base model is the greatest,which is 4.69%higher than that of the base model KNN.Comparing all of the ensemble models,the stacking ensemble model of level-1(ET,AdaBoost-RT,LR,BPN)paired with level-2(LR)was discovered to be the best model(EALB-LR)and can be further studied for industrial applications.
基金supported in part by the National Key Research and Development Program of China(No.2022YFA1602500)National Natural Science Foundation of China program(No.U2241288).
文摘A non-contact method for millimeter-scale inspection of material surface flatness via Laser-Induced Breakdown Spectroscopy(LIBS)is investigated experimentally.The experiment is performed using a planished surface of an alloy steel sample to simulate its various flatness,ranging from 0 to 4.4 mm,by adjusting the laser focal plane to the surface distance with a step length of 0.2 mm.It is found that LIBS measurements are successful in inspecting the flatness differences among these simulated cases,implying that the method investigated here is feasible.It is also found that,for achieving the inspection of surface flatness within such a wide range,when univariate analysis is applied,a piecewise calibration model must be constructed.This is due to the complex dependence of plasma formation conditions on the surface flatness,which inevitably complicates the inspection procedure.To solve the problem,a multivariate analysis with the help of Back-Propagation Neural Network(BPNN)algorithms is applied to further construct the calibration model.By detailed analysis of the model performance,we demonstrate that a unified calibration model can be well established based on BPNN algorithms for unambiguous millimeter-scale range inspection of surface flatness with a resolution of about 0.2 mm.
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.
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.
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 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Project(E2012203177)supported by the Natural Science Foundation of Hebei Province,ChinaProject(2011BAF15B01)supported by the National Science and Technology Support Plan of China+1 种基金Project(E2006001038)supported by Great Natural Science Foundation of Hebei Province,ChinaProject(NECSR-201202)supported by Open Project Program of National Engineering Research Center for Equipment and Technology of Cold Strip Rolling,China
文摘The dynamic model of cold rolling mill based on strip flatness and thickness integrated control was proposed,containing the following sub-models:the rolling process model,the dynamic model of rolls along axial direction,and the compensation model.Based on the rule of volume flow rate,the dynamic rolling process model was built.The work roll and backup roll were taken as elastic continuous bodies,the effect of shear and moment of inertia were taken into consideration,and then the dynamic model of rolls was built.The two models were coupled together,and the dynamic model of rolling mill was built.In the dynamic model,the thermal expansion of the rolls,the wear of the rolls and other related parameters can not be considered.In order to compensate the dynamic model,the coupled static model of rolls and strip was applied.Then,according to the inner relationship of these models,the dynamic model and the compensation model were coupled,and the dynamic model of rolling mill based on the strip flatness and thickness integrated control was built.The dynamic simulation of the rolling process was made,and the dynamic thickness and the dynamic flatness information were obtained.This model not only provides a theory basis for the virtual rolling,but also provides a platform for the application of advanced control theory.
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.
基金Project(20040311890) supported by the Science and Technology Development Foundation of University of Science and Technology Beijing
文摘The roll contour pattern and variety of work and backup rolls in service and its effect on profile and flatness control performance in 1 700 mm hot strip mill at Wuhan Iron and Steel(Group) Corporation were tested and analyzed by the developed finite element models of different typical roll contours configurations.A rather smooth local work roll contour near strip edges and an increase in rolled length can be obtained by application of long stroke work roll shifting system with conventional work roll contours that is incapable of the crown control.In comparison with the conventional backup and work roll contours configuration,the crown control range by the roll bending force enhances by 12.79% and the roll gap stiffness increases by 25.26% with the developed asymmetry self-compensating work rolls(ASR) and varying contact backup rolls(VCR).A better strip profile and flatness quality,an increase in coil numbers within the rolling campaign and a significant alleviated effect of severe work roll wear contours on performance of edge drop control are achieved by the application of ASR with crown control and wear control ability in downstream stand F5 and VCR in all stands of 1 700 mm hot strip mill.
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.
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.
