Active shape models (ASM), consisting of a shape model and a local gray-level appearance model, can be used to locate the objects in images. In original ASM scheme, the model of object′s gray-level variations is base...Active shape models (ASM), consisting of a shape model and a local gray-level appearance model, can be used to locate the objects in images. In original ASM scheme, the model of object′s gray-level variations is based on the assumption of one-dimensional sampling and searching method. In this work a new way to model the gray-level appearance of the objects is explored, using a two-dimensional sampling and searching technique in a rectangular area around each landmark of object shape. The ASM based on this improvement is compared with the original ASM on an identical medical image set for task of spine localization. Experiments demonstrate that the method produces significantly fast, effective, accurate results for spine localization in medical images.展开更多
A novel idea,called the optimal shape subspace （OSS） is first proposed for optimizing active shape model （ASM） search.It is constructed from the principal shape subspace and the principal shape variance subspace.I...A novel idea,called the optimal shape subspace （OSS） is first proposed for optimizing active shape model （ASM） search.It is constructed from the principal shape subspace and the principal shape variance subspace.It allows the reconstructed shape to vary more than that reconstructed in the standard ASM shape space,hence it is more expressive in representing shapes in real life.Then a cost function is developed,based on a study on the search process.An optimal searching method using the feedback information provided by the evaluation cost is proposed to improve the performance of ASM alignment.Experimental results show that the proposed OSS can offer the maximum shape variation with reserving the principal information and a unique local optimal shape is acquired after optimal searching.The combination of OSS and optimal searching can improve the ASM performance greatly.展开更多
Active Shape Model （ASM） is a powerful statistical tool to extract the facial features of a face image under frontal view. It mainly relies on Principle Component Analysis （PCA） to statistically model the variabil...Active Shape Model （ASM） is a powerful statistical tool to extract the facial features of a face image under frontal view. It mainly relies on Principle Component Analysis （PCA） to statistically model the variability in the training set of example shapes. Independent Component Analysis （ICA） has been proven to be more efficient to extract face features than PCA. In this paper, we combine the PCA and ICA by the consecutive strategy to form a novel ASM. Firstly, an initial model, which shows the global shape variability in the training set, is generated by the PCA-based ASM. And then, the final shape model, which contains more local characters, is established by the ICA-based ASM. Experimental results verify that the accuracy of facial feature extraction is statistically significantly improved by applying the ICA modes after the PCA modes.展开更多
A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segme...A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segment lung fields from chest radiographs. The modified SIFT local descriptor, more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel at each resolution level during the segmentation optimization procedure. Experimental results show that the proposed method is more robust and accurate than the original ASMs in terms of an average overlap percentage and average contour distance in segmenting the lung fields from an available public database.展开更多
Multi- pass spray deposition shows apparent advantages in preparing large scale plates with rapid solidification. Shape model is promoted to obtain excellent shape. Three dimensional mathematical models considering mo...Multi- pass spray deposition shows apparent advantages in preparing large scale plates with rapid solidification. Shape model is promoted to obtain excellent shape. Three dimensional mathematical models considering motion of atomization cone and substrate, deposition distance and atomization parameters were used to predict deposited plate’s shape. The results can be used to optimize the process parameters.展开更多
Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on th...Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on the flowering stage, using its apparent structure features and colors. Additional phenological stages have been largely overlooked. The objective of this study was to improve a shape-model method(SMM) for extracting winter canola phenological stages from time-series top-of-canopy reflectance images collected by an unmanned aerial vehicle(UAV). The transformation equation of the SMM was refined to account for the multi-peak features of the temporal dynamics of three vegetation indices(VIs)(NDVI, EVI, and CI). An experiment with various seeding scenarios was conducted, including four different seeding dates and three seeding densities. Three mathematical functions: asymmetric Gaussian function(AGF), Fourier function, and double logistic function, were employed to fit timeseries vegetation indices to extract information about phenological stages. The refined SMM effectively estimated the phenological stages of canola, with a minimum root mean square error(RMSE) of 3.7 days for all phenological stages. The AGF function provided the best fitting performance, as it captured multiple peaks in the growth dynamics characteristics for all seeding date scenarios using four scaling parameters. For the three selected VIs, CIred-edgeachieved the greatest accuracy in estimating the phenological stage dates. This study demonstrates the high potential of the refined SMM for estimating winter canola phenology.展开更多
Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these meth...Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these methods,the efficiency and accuracy of the method based on statistical shape models in clinical applications require further improvement.This study proposes a virtual reduction method for pelvic fractures that uses statistical shape models and partial surface data of a broken pelvis.Simulated fracture and clinical case experiments were conducted to validate the accuracy and effectiveness of the proposed method.The simulated fracture experiments yielded an average error of 1.57±0.39 mm and a maximum error of 12.82±3.54 mm.The virtual reduction procedure takes approximately 40 s.Based on three clinical case experiments,the proposed method achieves an acceptable level of accuracy compared with manual reduction by a surgeon.The proposed method offers the advantages of shorter virtual reduction times and satisfactory reduction accuracy.In the future,it will be integrated into the preoperative planning system for pelvic fracture reduction,thereby improving patient outcomes.展开更多
Background Deep 3D morphable models(deep 3DMMs)play an essential role in computer vision.They are used in facial synthesis,compression,reconstruction and animation,avatar creation,virtual try-on,facial recognition sys...Background Deep 3D morphable models(deep 3DMMs)play an essential role in computer vision.They are used in facial synthesis,compression,reconstruction and animation,avatar creation,virtual try-on,facial recognition systems and medical imaging.These applications require high spatial and perceptual quality of synthesised meshes.Despite their significance,these models have not been compared with different mesh representations and evaluated jointly with point-wise distance and perceptual metrics.Methods We compare the influence of different mesh representation features to various deep 3DMMs on spatial and perceptual fidelity of the reconstructed meshes.This paper proves the hypothesis that building deep 3DMMs from meshes represented with global representations leads to lower spatial reconstruction error measured with L_(1) and L_(2) norm metrics and underperforms on perceptual metrics.In contrast,using differential mesh representations which describe differential surface properties yields lower perceptual FMPD and DAME and higher spatial fidelity error.The influence of mesh feature normalisation and standardisation is also compared and analysed from perceptual and spatial fidelity perspectives.Results The results presented in this paper provide guidance in selecting mesh representations to build deep 3DMMs accordingly to spatial and perceptual quality objectives and propose combinations of mesh representations and deep 3DMMs which improve either perceptual or spatial fidelity of existing methods.展开更多
It is difficult to obtain the desired strip shape using Sendzimir rolling mills because small diameter work rolls can be easily deformed by the roiling force. To control the strip shape effectively, it is important to...It is difficult to obtain the desired strip shape using Sendzimir rolling mills because small diameter work rolls can be easily deformed by the roiling force. To control the strip shape effectively, it is important to understand the relationship between the behavior of the shape actuator and the variation of the strip shape. A numerical model based on the contact element method was proposed for the prediction of strip shape. In this numerical model, the re- lationships between the actuating forces, the roll deflections, the thickness profiles of the entry and exit sides, and the strip shape were considered. The proposed numerical model for strip shape prediction was evaluated by computer simulation and experiment with respect to various AS-U roll and first intermediate roll positions.展开更多
Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest ...Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height （dbh） can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter （h-d） models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods： We develop unconstrained generalized additive models （GAM） and shape constrained generalized additive models （SCAM） for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results： Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand, The definition of constraints leads only to marginal or minor decline in the model statistics like AIC An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting. Conclusions： We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.展开更多
Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pe...Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pendula Roth） in Norwa are presented. The Norwegian National Forest Inventory （NFI） is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputatio in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods： Generalized additive mixed models （gamm） are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand ag as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models （scare） were fit tc incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results： Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. / two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatial correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions： In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scare may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.展开更多
Some unavoidable factors in the process of cold strip shape measurement interfere with the shape meter, so the shape measuring results cannot reflect the true shape of the strip and the measuring precision is low. The...Some unavoidable factors in the process of cold strip shape measurement interfere with the shape meter, so the shape measuring results cannot reflect the true shape of the strip and the measuring precision is low. The influ- ences of the measuring error of the strip edges, the transverse temperature difference of the strip, the deflection of shape detection roller, and the shape of the strip coil on the shape measuring results were analyzed in detail, and the corresponding compensation models were established. The simulation calculation and analysis were carried out on a cold strip mill, and a number of disciplinarian cognitions were obtained.展开更多
A shape modeling of spray formed composite roll, which is utilized to predict the shape and dimension of roll during spray forming process, is developed in this paper. The influences of the principal spray forming par...A shape modeling of spray formed composite roll, which is utilized to predict the shape and dimension of roll during spray forming process, is developed in this paper. The influences of the principal spray forming parameters, such as the spatial distribution of melt mass flux, spray distance, rotating and translating speeds of substrate bar etc. , on the geometry and dimension of spray formed product were investigated.展开更多
It is of great significance to model the keyhole shape and dimensions to optimize the plasma arc welding process parameters. In this study, through employing a combined volumetric heat source mode, the weld pool in ke...It is of great significance to model the keyhole shape and dimensions to optimize the plasma arc welding process parameters. In this study, through employing a combined volumetric heat source mode, the weld pool in keyhole plasma arc welding is determined firstly, and then the dynamic force-balance condition on the interface between the plasma jet and the molten metal is dealt with in describing the keyhole formation inside the weld pool. The effects of welding current on the shape and size of keyhole are numerically analyzed. The sharp transformation from a partial keyhole to a full-penetration keyhole is quantitatively demonstrated.展开更多
文摘Active shape models (ASM), consisting of a shape model and a local gray-level appearance model, can be used to locate the objects in images. In original ASM scheme, the model of object′s gray-level variations is based on the assumption of one-dimensional sampling and searching method. In this work a new way to model the gray-level appearance of the objects is explored, using a two-dimensional sampling and searching technique in a rectangular area around each landmark of object shape. The ASM based on this improvement is compared with the original ASM on an identical medical image set for task of spine localization. Experiments demonstrate that the method produces significantly fast, effective, accurate results for spine localization in medical images.
基金21st Century Education Revitalization Project (No.301703201).
文摘A novel idea,called the optimal shape subspace （OSS） is first proposed for optimizing active shape model （ASM） search.It is constructed from the principal shape subspace and the principal shape variance subspace.It allows the reconstructed shape to vary more than that reconstructed in the standard ASM shape space,hence it is more expressive in representing shapes in real life.Then a cost function is developed,based on a study on the search process.An optimal searching method using the feedback information provided by the evaluation cost is proposed to improve the performance of ASM alignment.Experimental results show that the proposed OSS can offer the maximum shape variation with reserving the principal information and a unique local optimal shape is acquired after optimal searching.The combination of OSS and optimal searching can improve the ASM performance greatly.
文摘Active Shape Model （ASM） is a powerful statistical tool to extract the facial features of a face image under frontal view. It mainly relies on Principle Component Analysis （PCA） to statistically model the variability in the training set of example shapes. Independent Component Analysis （ICA） has been proven to be more efficient to extract face features than PCA. In this paper, we combine the PCA and ICA by the consecutive strategy to form a novel ASM. Firstly, an initial model, which shows the global shape variability in the training set, is generated by the PCA-based ASM. And then, the final shape model, which contains more local characters, is established by the ICA-based ASM. Experimental results verify that the accuracy of facial feature extraction is statistically significantly improved by applying the ICA modes after the PCA modes.
基金The National Natural Science Foundation of China(No60271033)
文摘A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segment lung fields from chest radiographs. The modified SIFT local descriptor, more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel at each resolution level during the segmentation optimization procedure. Experimental results show that the proposed method is more robust and accurate than the original ASMs in terms of an average overlap percentage and average contour distance in segmenting the lung fields from an available public database.
文摘Multi- pass spray deposition shows apparent advantages in preparing large scale plates with rapid solidification. Shape model is promoted to obtain excellent shape. Three dimensional mathematical models considering motion of atomization cone and substrate, deposition distance and atomization parameters were used to predict deposited plate’s shape. The results can be used to optimize the process parameters.
基金supported by the National Natural Science Foundation of China (51909228)the Postdoctoral Science Foundation of China (2020M671623)the ‘‘Blue Project” of Yangzhou University。
文摘Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on the flowering stage, using its apparent structure features and colors. Additional phenological stages have been largely overlooked. The objective of this study was to improve a shape-model method(SMM) for extracting winter canola phenological stages from time-series top-of-canopy reflectance images collected by an unmanned aerial vehicle(UAV). The transformation equation of the SMM was refined to account for the multi-peak features of the temporal dynamics of three vegetation indices(VIs)(NDVI, EVI, and CI). An experiment with various seeding scenarios was conducted, including four different seeding dates and three seeding densities. Three mathematical functions: asymmetric Gaussian function(AGF), Fourier function, and double logistic function, were employed to fit timeseries vegetation indices to extract information about phenological stages. The refined SMM effectively estimated the phenological stages of canola, with a minimum root mean square error(RMSE) of 3.7 days for all phenological stages. The AGF function provided the best fitting performance, as it captured multiple peaks in the growth dynamics characteristics for all seeding date scenarios using four scaling parameters. For the three selected VIs, CIred-edgeachieved the greatest accuracy in estimating the phenological stage dates. This study demonstrates the high potential of the refined SMM for estimating winter canola phenology.
基金supported by the National Key Research and Development Program of China(2020YFB1313800)the Key Research and Development Program of Shandong Province,China(2022CXGC020510).
文摘Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these methods,the efficiency and accuracy of the method based on statistical shape models in clinical applications require further improvement.This study proposes a virtual reduction method for pelvic fractures that uses statistical shape models and partial surface data of a broken pelvis.Simulated fracture and clinical case experiments were conducted to validate the accuracy and effectiveness of the proposed method.The simulated fracture experiments yielded an average error of 1.57±0.39 mm and a maximum error of 12.82±3.54 mm.The virtual reduction procedure takes approximately 40 s.Based on three clinical case experiments,the proposed method achieves an acceptable level of accuracy compared with manual reduction by a surgeon.The proposed method offers the advantages of shorter virtual reduction times and satisfactory reduction accuracy.In the future,it will be integrated into the preoperative planning system for pelvic fracture reduction,thereby improving patient outcomes.
基金Supported by the Centre for Digital Entertainment at Bournemouth University by the UK Engineering and Physical Sciences Research Council(EPSRC)EP/L016540/1 and Humain Ltd.
文摘Background Deep 3D morphable models(deep 3DMMs)play an essential role in computer vision.They are used in facial synthesis,compression,reconstruction and animation,avatar creation,virtual try-on,facial recognition systems and medical imaging.These applications require high spatial and perceptual quality of synthesised meshes.Despite their significance,these models have not been compared with different mesh representations and evaluated jointly with point-wise distance and perceptual metrics.Methods We compare the influence of different mesh representation features to various deep 3DMMs on spatial and perceptual fidelity of the reconstructed meshes.This paper proves the hypothesis that building deep 3DMMs from meshes represented with global representations leads to lower spatial reconstruction error measured with L_(1) and L_(2) norm metrics and underperforms on perceptual metrics.In contrast,using differential mesh representations which describe differential surface properties yields lower perceptual FMPD and DAME and higher spatial fidelity error.The influence of mesh feature normalisation and standardisation is also compared and analysed from perceptual and spatial fidelity perspectives.Results The results presented in this paper provide guidance in selecting mesh representations to build deep 3DMMs accordingly to spatial and perceptual quality objectives and propose combinations of mesh representations and deep 3DMMs which improve either perceptual or spatial fidelity of existing methods.
基金Item Sponsored by Korea Science and Engineering Foundation(KOSEF)Grant Funded by Korea Government(MEST)(2010-0022521)
文摘It is difficult to obtain the desired strip shape using Sendzimir rolling mills because small diameter work rolls can be easily deformed by the roiling force. To control the strip shape effectively, it is important to understand the relationship between the behavior of the shape actuator and the variation of the strip shape. A numerical model based on the contact element method was proposed for the prediction of strip shape. In this numerical model, the re- lationships between the actuating forces, the roll deflections, the thickness profiles of the entry and exit sides, and the strip shape were considered. The proposed numerical model for strip shape prediction was evaluated by computer simulation and experiment with respect to various AS-U roll and first intermediate roll positions.
文摘Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height （dbh） can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter （h-d） models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods： We develop unconstrained generalized additive models （GAM） and shape constrained generalized additive models （SCAM） for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results： Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand, The definition of constraints leads only to marginal or minor decline in the model statistics like AIC An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting. Conclusions： We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.
基金supported by the Norwegian Institute of Bioeconomy Research(NIBIO)
文摘Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pendula Roth） in Norwa are presented. The Norwegian National Forest Inventory （NFI） is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputatio in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods： Generalized additive mixed models （gamm） are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand ag as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models （scare） were fit tc incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results： Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. / two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatial correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions： In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scare may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.
基金Item Sponsored by National Science and Technology Support Plan of China (2007BAF02B10)Provincial Natural Science Foundation of Hebei of China (E2006001038)
文摘Some unavoidable factors in the process of cold strip shape measurement interfere with the shape meter, so the shape measuring results cannot reflect the true shape of the strip and the measuring precision is low. The influ- ences of the measuring error of the strip edges, the transverse temperature difference of the strip, the deflection of shape detection roller, and the shape of the strip coil on the shape measuring results were analyzed in detail, and the corresponding compensation models were established. The simulation calculation and analysis were carried out on a cold strip mill, and a number of disciplinarian cognitions were obtained.
文摘A shape modeling of spray formed composite roll, which is utilized to predict the shape and dimension of roll during spray forming process, is developed in this paper. The influences of the principal spray forming parameters, such as the spatial distribution of melt mass flux, spray distance, rotating and translating speeds of substrate bar etc. , on the geometry and dimension of spray formed product were investigated.
文摘It is of great significance to model the keyhole shape and dimensions to optimize the plasma arc welding process parameters. In this study, through employing a combined volumetric heat source mode, the weld pool in keyhole plasma arc welding is determined firstly, and then the dynamic force-balance condition on the interface between the plasma jet and the molten metal is dealt with in describing the keyhole formation inside the weld pool. The effects of welding current on the shape and size of keyhole are numerically analyzed. The sharp transformation from a partial keyhole to a full-penetration keyhole is quantitatively demonstrated.
