Error modelling and compensating technology is an effective method to improve the processing precision.The position and orientation deviation of workpiece is caused by the fixing and manufacturing errors of the fixtur...Error modelling and compensating technology is an effective method to improve the processing precision.The position and orientation deviation of workpiece is caused by the fixing and manufacturing errors of the fixture.How to reduce the position and orientation deviation of workpiece has become a technical problem of improving the processing quality of workpiece.In order to increase machining accuracy,an implementation scheme of fixture system comprehensive errors（FSCE） compensation is proposed.A FSCE parameter model is established by analyzing the influence of contact points on the position and orientation of workpiece.Meanwhile,a parameter identification method for FSCE parameter model is presented by using the 3-2-1 deterministic positioning fixture,which determines the model parameters.Moreover,a FSCE compensation model is formulated to study the compensation value of the cutting position.By using RenishawOMP60 Probe and combining vertical machining centre（SKVH850） equipment with SKY2001 Open CNC System,on-machine verification system（OMVS） is built to measure FSCE successfully.The processing error can be reduced by analyzing the cutting position of the tool with the homogeneous transformation of space coordinate system.Finally,the compensation experiment of real time errors is conducted,and the cylindricality and perpendicularity errors of hole surface are reduced by 30.77% and 28.57%,respectively.This paper provides a new way of realizing the compensation of FCSE,which can improve the machining accuracy of workpiece largely.展开更多
Digitization precision analysis is an important tool to ensure the design precision of machine tool currently. The correlative research about precision modeling and analysis mainly focuses on the geometry precision an...Digitization precision analysis is an important tool to ensure the design precision of machine tool currently. The correlative research about precision modeling and analysis mainly focuses on the geometry precision and motion precision of machine tool, and the forming motion precision of workpiece surface. For the machine tool with complex forming motion, there is not accurate corresponding relationship between the existing criterion on precision design and the machining precision of workpiece. Therefore, a design scheme on machine tool precision based on error prediction is proposed, which is divided into two-stage digitization precision analysis crucially. The first stage aims at the technology system to complete the precision distribution and inspection from the workpiece to various component parts of technology system and achieve the total output precision of machine tool under the specified machining precision; the second stage aims at the machine tool system to complete the precision distribution and inspection from the output precision of machine tool to the machine tool components. This article serves YK3610 gear hobber as the example to describe the error model of two systems and basic application method, and the practical cutting precision of this machine tool achieves to 5-4-4 grade. The proposed method can provide reliable guidance to the precision design of machine tool with complex forming motion.展开更多
The accuracy of landslide susceptibility prediction(LSP)mainly depends on the precision of the landslide spatial position.However,the spatial position error of landslide survey is inevitable,resulting in considerable ...The accuracy of landslide susceptibility prediction(LSP)mainly depends on the precision of the landslide spatial position.However,the spatial position error of landslide survey is inevitable,resulting in considerable uncertainties in LSP modeling.To overcome this drawback,this study explores the influence of positional errors of landslide spatial position on LSP uncertainties,and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error.This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example.The 30e110 m error-based multilayer perceptron(MLP)and random forest(RF)models for LSP are established by randomly offsetting the original landslide by 30,50,70,90 and 110 m.The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics.Finally,a semi-supervised model is proposed to relieve the LSP uncertainties.Results show that:(1)The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors,and are lower than those of original data-based models;(2)70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices,thus original landslides with certain position errors are acceptable for LSP;(3)Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.展开更多
Operational disposition of electronic countermeasures(ECM)is a hot topic in modern warfare research.Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme,a supe...Operational disposition of electronic countermeasures(ECM)is a hot topic in modern warfare research.Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme,a super-efficient data envelopment analysis support vector machine(SE-DEA-SVM)method for evaluating the operational configuration scheme of ECM is proposed.Firstly,considering the subjective and objective factors affecting the operational disposition of ECM,the index system of operational disposition scheme is established,and we explain the solution method of terminal indexs.Secondly,the evaluation and algorithm process of SE-DEA-SVM evaluation method are introduced.In this method,the super-efficient data envelopment analysis(SE-DEA)model is used to calculate the weight of index system,and the support vector machine(SVM)method combined with the training samples of evaluation index is used to obtain the input-output model of evaluation value of combat configuration.Finally,by an example(obtaining five schemes),we verify the SE-DEA-SVM evaluation method and analyze the results.The efficiency analysis,comparison analysis,and error analysis of this method are carried out.The results show that this method is more suitable for military evaluation with small samples,and it has high efficiency,applicability,and popularization value.展开更多
基金supported by National Natural Science Foundation of China (Grant No. 50975200)National Key Technologies R & D Programmer of China (Grant No. 2009ZX04014-021)
文摘Error modelling and compensating technology is an effective method to improve the processing precision.The position and orientation deviation of workpiece is caused by the fixing and manufacturing errors of the fixture.How to reduce the position and orientation deviation of workpiece has become a technical problem of improving the processing quality of workpiece.In order to increase machining accuracy,an implementation scheme of fixture system comprehensive errors（FSCE） compensation is proposed.A FSCE parameter model is established by analyzing the influence of contact points on the position and orientation of workpiece.Meanwhile,a parameter identification method for FSCE parameter model is presented by using the 3-2-1 deterministic positioning fixture,which determines the model parameters.Moreover,a FSCE compensation model is formulated to study the compensation value of the cutting position.By using RenishawOMP60 Probe and combining vertical machining centre（SKVH850） equipment with SKY2001 Open CNC System,on-machine verification system（OMVS） is built to measure FSCE successfully.The processing error can be reduced by analyzing the cutting position of the tool with the homogeneous transformation of space coordinate system.Finally,the compensation experiment of real time errors is conducted,and the cylindricality and perpendicularity errors of hole surface are reduced by 30.77% and 28.57%,respectively.This paper provides a new way of realizing the compensation of FCSE,which can improve the machining accuracy of workpiece largely.
基金supported by National Natural Science Foundation of China (Grant No. 51075419)Chongqing Municipal Natural Science Foundation of China (Grant No. CSTC,2009BB3234)
文摘Digitization precision analysis is an important tool to ensure the design precision of machine tool currently. The correlative research about precision modeling and analysis mainly focuses on the geometry precision and motion precision of machine tool, and the forming motion precision of workpiece surface. For the machine tool with complex forming motion, there is not accurate corresponding relationship between the existing criterion on precision design and the machining precision of workpiece. Therefore, a design scheme on machine tool precision based on error prediction is proposed, which is divided into two-stage digitization precision analysis crucially. The first stage aims at the technology system to complete the precision distribution and inspection from the workpiece to various component parts of technology system and achieve the total output precision of machine tool under the specified machining precision; the second stage aims at the machine tool system to complete the precision distribution and inspection from the output precision of machine tool to the machine tool components. This article serves YK3610 gear hobber as the example to describe the error model of two systems and basic application method, and the practical cutting precision of this machine tool achieves to 5-4-4 grade. The proposed method can provide reliable guidance to the precision design of machine tool with complex forming motion.
基金the National Natural Science Foundation of China(Grant Nos.42377164 and 52079062)the Interdisciplinary Innovation Fund of Natural Science,Nanchang University(Grant No.9167-28220007-YB2107).
文摘The accuracy of landslide susceptibility prediction(LSP)mainly depends on the precision of the landslide spatial position.However,the spatial position error of landslide survey is inevitable,resulting in considerable uncertainties in LSP modeling.To overcome this drawback,this study explores the influence of positional errors of landslide spatial position on LSP uncertainties,and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error.This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example.The 30e110 m error-based multilayer perceptron(MLP)and random forest(RF)models for LSP are established by randomly offsetting the original landslide by 30,50,70,90 and 110 m.The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics.Finally,a semi-supervised model is proposed to relieve the LSP uncertainties.Results show that:(1)The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors,and are lower than those of original data-based models;(2)70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices,thus original landslides with certain position errors are acceptable for LSP;(3)Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.
基金This work was supported by the Military Postgraduate Funding Project(JY2019C055)Hunan Province Postgraduate Scientific Research Innovation Project(CX20200029).
文摘Operational disposition of electronic countermeasures(ECM)is a hot topic in modern warfare research.Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme,a super-efficient data envelopment analysis support vector machine(SE-DEA-SVM)method for evaluating the operational configuration scheme of ECM is proposed.Firstly,considering the subjective and objective factors affecting the operational disposition of ECM,the index system of operational disposition scheme is established,and we explain the solution method of terminal indexs.Secondly,the evaluation and algorithm process of SE-DEA-SVM evaluation method are introduced.In this method,the super-efficient data envelopment analysis(SE-DEA)model is used to calculate the weight of index system,and the support vector machine(SVM)method combined with the training samples of evaluation index is used to obtain the input-output model of evaluation value of combat configuration.Finally,by an example(obtaining five schemes),we verify the SE-DEA-SVM evaluation method and analyze the results.The efficiency analysis,comparison analysis,and error analysis of this method are carried out.The results show that this method is more suitable for military evaluation with small samples,and it has high efficiency,applicability,and popularization value.
