Deformation Error Research Articles

Analysis of space-based large light concentration reflective surfaces with errors

Space-based 100-m light condensing reflectors can undergo considerable structural deformations. The simple and accurate analysis of a concentrator system is important, especially when the system has large deformation errors. Further, slope error measurement of large reflectors is challenging. Gaussian distribution and other calculation models cannot accurately characterize the continuous changes of the actual model. Moreover, the analysis of fully fitted deformed surfaces is complicated. Therefore, this paper proposes a method for approximating surfaces by planers. The side lengths of the planes affect the speed and accuracy of modeling. Therefore, this paper analyzes the influence of the side length of the modeling plane and derives the allowable maximum side length of the plane. The model is also analyzed to ensure that its slope error does not change compared to the actual model during the modeling process. Spherical concentrators have great advantages in spatial concentrating owing to their rotational symmetry. Herein, the error model of a spherical low-ratio concentrator is calculated. Finally, an experiment is designed to verify the correctness of the calculations.

Research on prediction and compensation strategy of milling deformation error of aitanium alloy integral blisk blade

Research on prediction and compensation strategy of milling deformation error of aitanium alloy integral blisk blade

Modelling and simulation of high- and low-speed impact damage of lithium batteries for light and small UAVs

In this study, the high- and low-speed impact damage of lithium batteries for light and small UAVs was investigated through the combination of experimental and simulation methods. A high-precision finite element model of the lithium battery was built, impact compression tests were performed for battery cells and battery modules to investigate the mechanical behavior of the lithium battery under the low-speed impact. In addition, the failure parameters of the lithium battery model were modified through battery cells and battery modules impact compression tests. In this paper, we designed and implemented a battery modules air cannon impact test on aluminum plates. The results achieved using the target impact simulation model of lithium batteries were compared with the results of the lithium battery target impact test. The peak strain error was obtained as 5.1%, the error of the back abrupt deformation of the aluminum plate after the target impact test was found as 5.67%, and the error of the approximate circle diameter of the aluminum plate crater reached 2.23%. The numerical simulation results of the lithium battery target impact were well consistent with the results of the target impact test, thus verifying the accuracy of the lithium battery finite element model built in this study under the high-speed impact. As revealed by the results, when the fall impact speed was higher than the normal flight speed of the UAV, the protective effect of the external battery box on the internal battery cell was found to decrease rapidly; the higher the impact speed, the more serious the damage of the internal single lithium battery would be, thus suggesting that the lithium battery under the high-speed impact would have a high risk of explosion and fire.

An Integrated Structure Analysis Method of Active Surface Antenna by Using the Simplified Actuator

The main surface of a large reflector antenna is composed of thousands of panels, which are inevitably deformed under natural load, leading to a great deterioration of electrical performance of the antenna. The active surface technique is an effective method to compensate antenna deformation error and has been widely used. The actuator is a complex component, it has not been established in the antenna structure analysis model, which limits the theoretical analysis ability of the active surface technology. To solve this problem, an integrated structure analysis method of active surface antenna by using the simplified actuator is proposed. First, according to the supporting characteristics and adjusting function of the actuator, the complex actuator is simplified a simple structure of support beams, support truss and adjustment beam. Second, the finite element model of the active surface antenna including the simplified actuator is established. Then, the relationship between the adjustment value (load) of adjustment beam and the deformation of the antenna structure is deduced, and the integrated analysis method for realizing the active adjustment of panels is established. Finally, the model and adjustment analysis method of the active surface antenna in this paper is applied to an 8 m antenna, and satisfactory structural analysis results are obtained, which shows the effectiveness and universality of the method, and provides a reference for the modeling and adjustment analysis of the active surface antenna.

Study on the method of automatically determining maxillary complex landmarks based on non-rigid registration algorithms

Objective: To explore an automatic landmarking method for anatomical landmarks in the three-dimensional (3D) data of the maxillary complex and preliminarily evaluate its reproducibility and accuracy. Methods: From June 2021 to December 2022, spiral CT data of 31 patients with relatively normal craniofacial morphology were selected from those who visited the Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology. The sample included 15 males and 16 females, with the age of (33.3±8.3) years. The maxillary complex was reconstructed in 3D using Mimics software, and the resulting 3D data of the maxillary complex was mesh-refined using Geomagic software. Two attending physicians and one associate chief physician manually landmarked the 31 maxillary complex datasets, determining 24 anatomical landmarks. The average values of the three expert landmarking results were used as the expert-defined landmarks. One case that conformed to the average 3D morphological characteristics of healthy individuals' craniofacial bones was selected as the template data, while the remaining 30 cases were used as target data. The open-source MeshMonk program (a non-rigid registration algorithm) was used to perform an initial alignment of the template and target data based on 4 landmarks (nasion, left and right zygomatic arch prominence, and anterior nasal spine). The template data was then deformed to the shape of the target data using a non-rigid registration algorithm, resulting in the deformed template data. Based on the unchanged index property of homonymous landmarks before and after deformation of the template data, the coordinates of each landmark in the deformed template data were automatically retrieved as the automatic landmarking coordinates of the homonymous landmarks in the target data, thus completing the automatic landmarking process. The automatic landmarking process for the 30 target data was repeated three times. The root-mean-square distance (RMSD) of the dense corresponding point pairs (approximately 25 000 pairs) between the deformed template data and the target data was calculated as the deformation error of the non-rigid registration algorithm, and the intra-class correlation efficient (ICC) of the deformation error in the three repetitions was analyzed. The linear distances between the automatic landmarking results and the expert-defined landmarks for the 24 anatomical landmarks were calculated as the automatic landmarking errors, and the ICC values of the 3D coordinates in the three automatic landmarking repetitions were analyzed. Results: The average three-dimensional deviation (RMSD) between the deformed template data and the corresponding target data for the 30 cases was (0.70±0.09) mm, with an ICC value of 1.00 for the deformation error in the three repetitions of the non-rigid registration algorithm. The average automatic landmarking error for the 24 anatomical landmarks was (1.86±0.30) mm, with the smallest error at the anterior nasal spine (0.65±0.24) mm and the largest error at the left oribital (3.27±2.28) mm. The ICC values for the 3D coordinates in the three automatic landmarking repetitions were all 1.00. Conclusions: This study established an automatic landmarking method for three-dimensional data of the maxillary complex based on a non-rigid registration algorithm. The accuracy and repeatability of this method for landmarking normal maxillary complex 3D data were relatively good.

Gaussian optics optimization of an optical particle counter for measurement in high-pressure gas.

An optimization model for the parameters of the pressure-resistant lens of an optical particle counter, based on Gaussian optics theory, was established to increase the measurement accuracy of the counter for high-pressure natural gas. Comparing the experimental and calculated values of the calibrated model, when the pressure-resistant lens is displaced by 2mm under atmospheric pressure, the relative error of the measured body deformation is 0.15%. When the air pressure varies in the range 0.10-5.09MPa, the maximum relative error of optical measurement volume deformation with the change of refractive index is 0.13%, which shows that the model has high reliability and accuracy.

Dynamic prediction of displacement and deformation of any point on mining surface based on B-normal model.

The surface displacement and deformation of goaf caused by coal mining destroy the underground rock structure and surface ecological environment in the mining area and endanger the safety of human life and property. An accurate and efficient dynamic prediction system of mining subsidence is indispensable. Given the limited scope of the application of the probability integral model on the edge of the mobile basin, its poor prediction effect, and its low accuracy, a new mining subsidence prediction model based on the Boltzmann function is proposed. Combined with the transformed normal distribution time function, a B-normal prediction model that can predict the dynamic displacement and deformation of any point on the surface was constructed. The global optimal solution of the parameters of the dynamic prediction model was inversed by introducing particle swarm optimization shuffled frog leaping intelligent algorithm (PSO-SFLA), and then, the model was applied to the 8102 working face of the Guobei coal mine to dynamically predict the subsidence, inclination, curvature, horizontal displacement, and horizontal deformation of the goaf surface. The prediction results showed that on the strike and dip observation lines, the prediction accuracy of the dynamic subsidence and horizontal displacement of the surface could reach the centimeter level, the predicted root mean square error (RMSE) of dynamic tilt and horizontal deformation was less than 0.51 mm/m, and the predicted RMSE of dynamic curvature was within 0.020 mm/m2. The prediction results reflected the dynamic evolution law of surface displacement and deformation and verified the reliability of the B-normal dynamic prediction model, which can fully meet the needs of practical engineering applications.

Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization.

For the machining of aero-engine blades, factors such as machining residual stress, milling force, and heat deformation can result in poor blade profile accuracy. To address this issue, simulations of blade milling were completed using DEFORM11.0 and ABAQUS2020 software to analyze blade deformation under heat-force fields. Process parameters such as spindle speed, feed per tooth, depth of cut, and jet temperature are used to design both a single-factor control and BBD test scheme to study the influence of jet temperature and multiple changes in process parameters on blade deformation. The multiple quadratic regression method was applied to establish a mathematical model correlating blade deformation with process parameters, and a preferred set of process parameters was obtained through the particle swarm algorithm. Results from the single-factor test indicated that blade deformation rates were reduced by more than 31.36% in low-temperature milling (-190 °C to -10 °C) compared with dry milling (10 °C to 20 °C). However, the margin of the blade profile exceeded the permissible range (±50 µm); therefore, the particle swarm optimization algorithm was used to optimize machining process parameters, resulting in a maximum deformation of 0.0396 mm when the blade temperature was -160 °C~-180 °C, meeting the allowable blade profile deformation error.

Offline Feed-Rate Scheduling Method for Ti–Al Alloy Blade Finishing Based on a Local Stiffness Estimation Model

In the aerospace field, Ti–Al alloy thin-walled parts, such as blades, generally undergo a large amount of material removal and have a low processing efficiency. Scheduling the feed rate during machining can significantly improve machining efficiency. However, existing feed-rate scheduling methods rarely consider the influence of machining deformation factors and cannot be applied in the finishing stages of thin-walled parts. This study proposes an offline feed-rate scheduling method based on a local stiffness estimation model that can be used to reduce machining errors and improve efficiency in the finishing stage of thin-walled parts. In the proposed method, a predictive model that can rapidly calculate the local stiffness at each cutter location point and a cutting-force prediction model that considers the effect of cutting angle are established. Based on the above model, an offline feed-rate scheduling method that considers machining deformation error constraints is introduced. Finally, an experiment is performed by taking the finishing of actual blade parts as an example. The experimental results demonstrate that the proposed feed-rate scheduling method can improve the machining efficiency of parts while ensuring machining accuracy. The proposed method can also be conveniently applied to feed-rate scheduling in the finishing stage of other thin-walled parts without being limited by machine tools.

The Importance of Embedding a General forward Kinematic Model for Industrial Robots with Serial Architecture in Order to Compensate for Positioning Errors

This paper proposes a methodology for creating simplified structural schemes and forward geometric models for industrial robots with serial architecture, with the goal of reducing thermal deformation errors that negatively impact positioning accuracy during operation. Unlike classical approaches, the proposed methodology introduces modifications to the order of matrix multiplication and incorporates new parameters to create a forward geometric model that better corresponds to the deformation characteristics of these robots. Details are presented on how to build and employ this extended model and integrate it into a thermal error compensation algorithm. The implementation of the algorithm in a software application is presented along with experimental results that demonstrate its effectiveness. This work addresses a real phenomenon that occurs in industrial robot operation and has implications for improving the performance of robots in manufacturing applications.

Deformation error compensation in 5-Axis milling operations of turbine blades

The precision and performance of machined flexible parts are under influence of deformation errors during end milling operations. Thus, prediction and compensation of deformation errors during milling operations of flexible parts can provide a key tool in accuracy enhancement of part production. In this study, an improved virtual machining system is proposed in order to assess and compensate deformation errors caused by cutting temperature and forces in 5-axis milling operations of flexible parts. The improved Johnson–Cook model is utilized to investigate the cumulative impact of strain rate and deformation temperatures on flow stress during milling operations of turbine blade. To estimate deformation errors caused by cutting forces and temperature on the workpiece and cutting tool, the finite element analysis is then applied. As a result, volumetric vectors of deformation error at each cutting location along the machining pathways are then generated in order to be compensated within new compensated machining tool paths. Thus, the deformation error created by cutting forces and temperature on the workpiece and cutting tool are compensated in order to enhance accuracy during 5-axis milling operation of flexible turbine blades. Experiments are carried out using a 5-axis CNC machine tool and errors are quantified using a CMM to verify the developed strategy in the study. As a consequence, precision of machining operations on flexible turbine blades can be enhanced by employing the developed virtual machining system in the study.

Deformation Error Compensation in 5-Axis Milling Operations of Turbine Blades

Deformation Error Compensation in 5-Axis Milling Operations of Turbine Blades

THEORETICAL RESEARCHES OF THE EMBEDDED FIBER-OPTIC SYSTEM OF TESTING DEFORMATION AND TEMPERATURE OF POLYMER COMPOSITES

This article describes the results of theoretical researches of the system of optical testing of polymer composites by the method of two optical fibers with different sensitivity to deformation and temperature, using integrated arrays of fiber Bragg gratings. The features of the primary data processing from the optical testing system embedded into the composite are considered by the methods of weighted arithmetic mean and approximation by the Gaussian function. The basic relations for calculating the error in determining the temperature and strain with the help of fiber-optic embedded testing systems are obtained. A numerical model of the interrogator has been constructed, which makes it possible to estimate the systematic error of deformation and temperature measurements, including taking into account the noise of a real interrogator. It is shown that, taking into account a number of assumptions for the problem of simultaneous embedded testing of composites with fiber Bragg gratings, it is advisable to apply he method of primary processing of testing data using the approximation of the real spectra of fiber Bragg gratings by the Gaussian function, while in order to increase the reliability of testing, it is necessary to take into account the temperature correction characteristic of a particular interrogating device.

Optimal deformation error compensation process in flank milling of thin-walled workpieces

Optimal deformation error compensation process in flank milling of thin-walled workpieces

Error compensation method of industrial robots considering non-kinematic and weak rigid base errors

Industrial robots are receiving increasing attention owing to their numerous advantages, such as flexibility, maneuverability, and low cost. In robotic machining systems, improving the absolute positioning accuracy of the robot is essential for improving workpiece quality. This study proposes a robot error compensation method that considers nonkinematic and weak rigid base errors. A mapping model between the theoretical position of the robot and the actual error was established based on an incremental support vector machine (ISVM), and the nonkinematic error compensation of the robot was realized. The robot error before and after axis 1 rotation is compensated for by modeling the rotational error of axis 1 and the deformation error of the robot base and is verified on the milling robot KUKA KR 160. The experimental results show that the maximum absolute position error of the robot end-effector is reduced by 85.27% (from 1.3277 to 0.1956 mm) after compensation. Milling experiments have shown that the position error of the empty running trajectory before compensation is reduced from −1.3231 to −0.1297 mm, and the z-direction error of the workpiece is reduced from −0.8771 to 0.3267 mm, which meets the machining accuracy requirements of the milling robot system in this paper.

Parametric stiffness modeling of a variable cross-section link for a collaborative robot

This paper describes how a parametric stiffness model of the variable cross-section link of a collaborative robot is obtained. The variable cross-section link module is divided into three parts: the front connection part, the rear connection part, and the main part. The static condensation method is used to model the stiffness of the connecting parts. The parametric stiffness modeling of the main part is carried out using the structural mechanics method. The stiffness models of the three parts are integrated into the parametric stiffness model of the entire link. The parametric stiffness model of the variable cross-section link is related to the structural dimensions of the link. The elastic deformation errors in all directions obtained from the stiffness model are within 5%. The method establishes the mapping relationship between the link’s structural dimensions and its stiffness model. Based on this, the structural optimization of a collaborative robot based on parametric stiffness model is made possible.

Investigating the Manufacturing Process of Heat-Treated Nb3Sn-CICC Conductor for CFETR CSMC Modules

The center solenoid model coil (CSMC) of the China fusion engineering test reactor (CFETR) requires a high heat treatment temperature of 650 °C, which would destroy the insulation layer by carbonization and cause coil failure. To avoid this, using the manufacturing technology and routine process of the ITER center solenoid coil as a reference, in this article, a solution is introduced that is applied for manufacturing the CFETR CSMC module. The coil is heat treated before insulation and after winding. A single turn of the heat-treated coil is separated and the wrapping turn insulation is applied, and then the separated layers are reversed back into the integrated coil. To manufacture the integrated coils, the heat-treated coils are molded. After heat treatment, the interlayer separation distance of the Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn cable-in-conduit conductor in the coil should satisfy the allowable strain range of the superconductor, which is crucial for designing the rotational support structure of the interlayer separation. In addition, to achieve the accurate final shape of the coil and meet the design requirements, as well as to ensure coil contour accuracy after layer by layer separation, the antideformation ability of the coil mold is a key research topic. Herein, mechanical properties of the key components were optimized and numerical calculations and ANSYS simulations were used for statistical analyses. Results from the analyses indicated that the equivalent stress on the device is less than the maximum permissible stress of the raw material. The device was manufactured and compared with a design mold. The overall deformation error was <5%, movement error of the electric frame was <2%, rotation error of rotating was less than ±1° per 360°, levelness between the upper and lower platform was <1 mm, and motion error was less than ±1 mm per 100 mm. These results demonstrated the optimized structure design of the device. In the as-obtained device, the coil could separate a single turn and wrapping turn insulation could be applied. Parameters of the manufactured coil satisfied all the CSMC design requirements; these results indicate that the proposed device is suitable for manufacturing the CFETR CSMC module coil.

Straightening of the rollers of planetary roller screw — Design of straightening die and experimental validation

The roller of a Planetary Roller Screw (PRS) is prone to bending deformation and runout error after carburizing, which results in the uneven transmission performance, increased transmission friction, and decreased service life. Traditional grinding methods used to rectify these errors have high costs and low efficiency and furthermore reduce the thickness of the carbon layer of the roller. This paper proposed a new radial feed-in straightening method to correct the geometric errors of carburized PRS rollers. Trial tests are first performed to explore the feasibility of different straightening techniques, as well as to discover key factors for the rational design of a straightening die. Based on the trial tests, a new tooth profile model of the straightening die for the PRS roller is proposed. Finite element models are developed to analyze the material flow feature of the straightening process, as well as to verify the effectiveness of the proposed tooth profile model of the straightening die. For mass production needs, experimental tests are performed to further examine the performance of the proposed straightening method. It is found that reducing the tooth contact interference between the roller and die can effectively increase the quality of the straightened workpiece. Results show that the bending deformation and runout error of the carburized PRS roller are effectively corrected by the proposed straightening process. Furthermore, the smoothness of the tooth surface of the roller is significantly increased, and all the tested samples meet production quality standards after straightening. A comparison of transmission performance under 0.3 million cycles shows that the maximum friction torque (1.82 N·mm) of the PRS product with straightened rollers is much better than without straightening (105.70 N·mm).

Process-based deep learning model: 3D prediction method for shot peen forming of an aircraft panel

Shot peen-forming is a more precise method of forming aircraft panels than conventional methods. The traditional method of acquiring the process parameters relies mainly on prior theoretical knowledge and trial-and-error. Despite the finite element method's ability to replace some experimentation, it still cannot realize the design of shot peen forming processes parameters of an aircraft panel based on a known contour. This study uses an innovative model-based deep learning approach to predict aircraft panel deformation and active design the shot peening parameters. The prediction time is less than 1 second, resulting in a significant reduction in computational time. The shot peen forming process parameters and the geometric structure characteristics of the aircraft panel are divided into independent channels to establish a high-dimensional feature map, which are used to train the deep learning model. The forming contours of the 2024-T351 high-strength aluminum alloy panel are predicted under different shot peening processes. In addition, the process parameters are designed according to the known contour of the forming process. To verify the precision of the proposed method, the designed shot peen forming process is used to manufacture a single curvature aircraft panel with a curvature radius of 3500 mm. There is good agreement between the forming contour and the theoretical design contour. The maximum deformation error is less than 1 mm and its mean error is 7.8%. The mean curvature radius error is 5.668%. The proposed method provides a new and practical reference to the precise design of the shot peen-forming process.

Prediction of Thermal Deformation and Real-Time Error Compensation of a CNC Milling Machine in Cutting Processes

This study constructs a prediction model of thermal deformation with an artificial neural network and implements the real-time error compensation for a three-axis vertical CNC milling machine in cutting processes to improve the thermal error of the workpiece. There are 32 PT-100 thermal sensors installed in key parts of the machine in order to measure the temperature of key machine parts in actual cutting conditions. Pearson’s correlation coefficients are used to select crucial temperature sensors for building the prediction model of thermal deformation. The reduced number of crucial temperature sensors in model construction can simplify the model complexity and speed up the response time of prediction. This study constructs a long short-term memory (LSTM) neural network model to predict the thermal error of the machine in cutting processes. This prediction model of thermal deformation can be further used in real-time error compensation of the workpiece in cutting processes. In an 8 h cutting experiment, the dimensions of the workpiece show that, with real-time error compensation, the thermal error in X-axis decreases from 7 µm to 3 µm, the thermal error in Y-axis decreases from 74 µm to 21 µm, and the thermal error in Z-axis decreases from −64 µm to −20 µm. The results indicate that the prediction model of thermal deformation and the real-time error compensation can significantly reduce the thermal error and improve the dimensional accuracy of the workpiece.