This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is establishe...This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is established,and the online trajectory correction-regenerating strategy is introduced.Secondly,based on the neighborhood optimal control theory,a neighborhood optimal trajectory online correction algorithm considering the terminal time variation is proposed by adding the consideration of terminal time variation to the traditional neighborhood optimal trajectory correction method.Thirdly,the Monte Carlo simulation method is used to analyze the application range of the algorithm,which provides a basis for the division of application domain of the online correction algorithm and the online regeneration algorithm of midcourse guidance trajectory.Finally,the simulation results show that the algorithm has high real-time performance,and the online correction trajectory can meet the requirements of terminal constraint change.The application range of the algorithm is obtained through Monte Carlo simulation.展开更多
The service cycle and dynamic performance of structural parts are afected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of ...The service cycle and dynamic performance of structural parts are afected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground ofine, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was frst set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were confgured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize realtime communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profle model of the base material in the weld area using a polynomial ftting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verifed the efectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verifed through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction efect and high robustness.展开更多
Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high cost. One inherent difficulty is insufficiency of t...Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high cost. One inherent difficulty is insufficiency of the training samples because the labeled data are limited. Besides, the traditional soft-sensing structure has no online correction mechanism. The forecasting result may be incorrect if the working condition is changed. In this work, a semi-supervised learning(SSL) method is proposed to build the soft-sensing model by use of the unlabeled data. Meanwhile, an online correction mechanism is proposed to establish a soft-sensing approach. The mechanism estimates the input variables at each step by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and generalization ability than other approaches.展开更多
In short-wavelength optics,millimetre spot-sized ion beam figuring(IBF)is an effective method to eliminate form errors with spatial wavelengths ranging from 10 mm to 1 mm.In this case,the full width at half maximum(FW...In short-wavelength optics,millimetre spot-sized ion beam figuring(IBF)is an effective method to eliminate form errors with spatial wavelengths ranging from 10 mm to 1 mm.In this case,the full width at half maximum(FWHM)of the tool influence function(TIF)is typically below 2 mm.In IBF,accurate measurement of a small-sized TIF is critical in determining the removal rate and distribution.In existing research,the online measurement of the TIF has been achieved by scanning the beam current density(BCD)distribution with the Faraday cup(FC).However,due to the convolution effect during scanning,this method is not sufficiently accurate for small-sized TIFs,posing considerable limitations to high-precision applications.This paper presents an in-depth analysis of the convolution effect in TIF measurements.The obtained findings are applied to a corrective TIF measurement method and verified by calculation,simulation,and experiment.The results demonstrate that the proposed method can effectively reduce the measurement error.Specifically,for TIFs with FWHMs ranging from 0.5 to 1 mm,the average measurement error of the peak removal rate(PRR)is reduced from 47.4%to 3.1%,and the average error in the FWHM is reduced from 51.7%to 2.6%.The application of this method to a polishing experiment reduces the rootmean-square(RMS)of the aspherical optical mirror from 1.7 nm to 0.4 nm;moreover,the average convergence rate is 76.4%,which is within the target spatial wavelength range of 15 mm to 3.6 mm.Thus,this paper provides practical guidance for millimetre spot-sized IBF,and is promising for application in high-precision optics.展开更多
基金supported by the National Natural Science Foundation of China(61873278,62173339)。
文摘This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is established,and the online trajectory correction-regenerating strategy is introduced.Secondly,based on the neighborhood optimal control theory,a neighborhood optimal trajectory online correction algorithm considering the terminal time variation is proposed by adding the consideration of terminal time variation to the traditional neighborhood optimal trajectory correction method.Thirdly,the Monte Carlo simulation method is used to analyze the application range of the algorithm,which provides a basis for the division of application domain of the online correction algorithm and the online regeneration algorithm of midcourse guidance trajectory.Finally,the simulation results show that the algorithm has high real-time performance,and the online correction trajectory can meet the requirements of terminal constraint change.The application range of the algorithm is obtained through Monte Carlo simulation.
基金Supported by Hunan Provincial Natural Science Foundation of China(Grant No.2021JJ50116).
文摘The service cycle and dynamic performance of structural parts are afected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground ofine, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was frst set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were confgured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize realtime communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profle model of the base material in the weld area using a polynomial ftting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verifed the efectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verifed through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction efect and high robustness.
基金the National Natural Science Foundation of China(Nos.61374110 and 61074060)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20120073110017)
文摘Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high cost. One inherent difficulty is insufficiency of the training samples because the labeled data are limited. Besides, the traditional soft-sensing structure has no online correction mechanism. The forecasting result may be incorrect if the working condition is changed. In this work, a semi-supervised learning(SSL) method is proposed to build the soft-sensing model by use of the unlabeled data. Meanwhile, an online correction mechanism is proposed to establish a soft-sensing approach. The mechanism estimates the input variables at each step by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and generalization ability than other approaches.
基金supported by National Natural Science Foundation of China(62127901,12103054,62405314,62305333,62375260)National Key Research and Development Program of China(2022YFB3403405)+4 种基金Scientific and Technological Development Program of Jilin(SKL202402021)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2019221,Y2023062)Youth Elite Scientists Sponsorship Program of CAST(2022QNRC001)Young Elite Scientists Sponsorship Program of Jilin Province(QT202222)Scientific and Technological Program of Changchun(2024GZZ19).
文摘In short-wavelength optics,millimetre spot-sized ion beam figuring(IBF)is an effective method to eliminate form errors with spatial wavelengths ranging from 10 mm to 1 mm.In this case,the full width at half maximum(FWHM)of the tool influence function(TIF)is typically below 2 mm.In IBF,accurate measurement of a small-sized TIF is critical in determining the removal rate and distribution.In existing research,the online measurement of the TIF has been achieved by scanning the beam current density(BCD)distribution with the Faraday cup(FC).However,due to the convolution effect during scanning,this method is not sufficiently accurate for small-sized TIFs,posing considerable limitations to high-precision applications.This paper presents an in-depth analysis of the convolution effect in TIF measurements.The obtained findings are applied to a corrective TIF measurement method and verified by calculation,simulation,and experiment.The results demonstrate that the proposed method can effectively reduce the measurement error.Specifically,for TIFs with FWHMs ranging from 0.5 to 1 mm,the average measurement error of the peak removal rate(PRR)is reduced from 47.4%to 3.1%,and the average error in the FWHM is reduced from 51.7%to 2.6%.The application of this method to a polishing experiment reduces the rootmean-square(RMS)of the aspherical optical mirror from 1.7 nm to 0.4 nm;moreover,the average convergence rate is 76.4%,which is within the target spatial wavelength range of 15 mm to 3.6 mm.Thus,this paper provides practical guidance for millimetre spot-sized IBF,and is promising for application in high-precision optics.
