Thermal Deformation Compensation Research Articles

Accuracy improvement of laser tracker registration based on enhanced reference system points weighting self-calibration and thermal compensation.

Improving the accuracy of large measurement systems consisting of multiple laser trackers and Enhanced Reference System (ERS) points is technically challenging. In practice, standard devices with precise distance limits are often used to improve the registration accuracy of laser trackers. However, these standard devices are expensive and need to be calibrated by the Coordinate Measuring Machine (CMM). In addition, the stability of ERS points can significantly affect registration errors. Therefore, this paper proposes a laser tracker registration method based on ERS point-weighted self-calibration and thermal deformation compensation. First, a self-calibration method for simple standard devices based on multilateration measurements is presented, which only utilizes large measurement systems without additional high-precision measurement instruments. Based on this, a weighted registration optimization algorithm for the registration process of a relocation laser tracker is proposed. Then, the position errors of ERS points caused by temperature changes are calculated and compensated based on the thermal deformation coefficient of large structural components. The compensated ERS points are used for the registration of the laser trackers. Finally, the effectiveness of the proposed method is demonstrated by a field measurement experiment on a large spherical shell. Compared with the most widely used benchmark method, the proposed method reduces the average registration error of all ERS points from 0.103 to 0.02mm.

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.

Spatially discretised compensation method for coordinate transformation in large-scale metrology under nonuniform temperature field

Temperature-variation-induced error compensation plays a pivotal role in large-scale metrology, in which the nonuniform temperature field would greatly influence the coordinate transformation process between different systems. This paper proposes a novel analytical thermal deformation compensation method with spatial discretisation modelling among 2D distributed enhanced reference system points to reduce the thermal influence on the coordinate transformation process. First, the analytical thermal deformation model based on the spatial discretisation is established with the plane thermal elastic mechanics and the Finite Difference Method. Then the nonuniform temperature field model is developed based on Ordinary Kriging spatial interpolation. Finally, a compensation method for the coordinate transformation process is proposed based on the actual measurement data and the proposed thermal deformation model. The experimental results illustrate the existence and significance of the nonuniform feature of the temperature field. By the proposed compensation method, the coordinate transformation error is reduced by 47.13% and 76.67% in the x and y directions, respectively. The method is applicable to diminish the influence of thermal deformation under a nonuniform temperature field on the coordinate transformation of large-scale metrology.

Thermal deformation analysis and compensation of the direct-drive five-axis CNC milling head

Thermal deformation analysis and compensation of the direct-drive five-axis CNC milling head

Thermomechanical and isothermal fatigue crack propagation testing method for 316LN austenitic stainless steel

AbstractInvestigating fatigue crack growth behavior of materials is crucial to the life design and safety evaluation of engineering structures. During the practical service condition, the temperature keeps changing, which cannot be studied by the traditional fatigue crack growth test method at constant temperature. In this study, we focus on constructing a new thermomechanical fatigue (TMF) crack propagation testing method, developing a thermal deformation compensation method, and proposing an equivalent compliance method suitable for variable temperature conditions based on ASTM E647 standard to measure the crack length. Furthermore, the load‐ and strain‐controlled TMF tests under different phase angles are carried out to prove the validity of the new method.

Intelligent support system for monitoring machining processes

The intelligent support system for monitoring machining processes was objective of our research. The paper presents process of development of this system which can used in real enterprises. Methodology: to create of the system we use methods of artificial intelligence (neural networks, decision trees and rules, fuzzy logic), using AI methods we created procedures support monitoring machining processes: diagnosis of machining process disturbances using decision rules, control of stability of the machining process based on control card analysis using neural networks, control of surface roughness parameter using neural networks and decision trees and monitoring machine tool through control and compensation of thermal deformations of ball screws of CNC machine tools using neural networks. To optimize of AI models we compared many the models with different structures, chose the best models and used them in intelligent system.

An improved thermal performance modeling for high-speed spindle of machine tool based on thermal contact resistance analysis

The temperature field distribution has a significant influence on structural performance, thermal deformation, and thermal error compensation. To improve the prediction accuracy of the temperature distribution of the spindle system, a comprehensive model considering the contact thermal resistance (TCR) of the interfaces was established to analyze the thermal performance of the high-speed spindle system in the present work. An elastoplastic contact model was used to calculate the contacting areas and loads of interfaces, which were employed to establish the contact thermal resistance model of the primary interfaces of the spindle, such as bearing rings and tool holders. Based on the TCR parameters, a finite element analysis (FEA) model was proposed to analyze the temperature distribution of the spindle system. And a temperature test experiment was set up to verify the accuracy of the FEA model. The results show that the relative errors of representative test points were all less than 5%, which means the established model can appropriately reflect the temperature field distribution of the spindle.

Research Status of Hydrostatic Bearing Technology in Machine Tool

Background: As the basis of mechanical manufacturing, large-scale machine tools are being developed for improving processing accuracy, load-bearing capacity and rigidity. Hydrostatic thrust bearing, hydrostatic guide and hydrostatic ram are important components of large machine tools; with the continuous improvement of product accuracy requirements, the research on the hydrostatic thrust bearing, hydrostatic guide and hydrostatic ram has become more important. Objective: This paper presents the current research on hydrostatic thrust bearing, hydrostatic guide and hydrostatic ram to highlight the importance of hydrostatic ram in improving the machining accuracy of machine tools. The study aims to lay a foundation for research and development of hydrostatic ram in the future. Methods: Firstly, the hydrostatic bearing technology is introduced. Secondly, the research status of hydrostatic thrust bearing, hydrostatic guide and hydrostatic ram is presented to provide theoretical basis for improving the processing performance of rest ram. Result: Deformation compensation and thermal deformation compensation of hydrostatic ram have been studied more. Most of the research study focuses on the accuracy of hydrostatic ram, but less on the bearing performance of hydrostatic ram. Conclusion: Breakthroughs have been made in the research on precision control and structural form of the hydrostatic bearing at home and abroad. Most scholars take the ram of Computer Numerically Control (CNC) boring and milling machines as the research object, but there is less research on the ram of vertical lathes. Therefore, the academic circle should pay more attention to the bearing performance of the hydrostatic ram of vertical lathes.

Algorithm for automatic compensation of thermal deformations of thermally loaded load-bearing structures

The paper considers a possible algorithm for the automatic control system of the thermal modes of load-bearing structures of the information-measuring system of autonomous objects. Thermo-deformation component of information-measuring error, which is the cause of distortion of operating and service information of an autonomous object, is reduced due to compensation of thermogradient by automatic control system of operation modes of distributed controlled heat sources. The system provides a significant reduction in the level of thermal deformation error of measurements, the cause of which is the deformation of supporting structures due to unstable and uneven heat release of information-measuring instruments placed on the structure. To compensate for thermal deformations, the system includes controlled heat sources that compensate for the thermal gradients of the supporting structure arising under the influence of the information-measuring system instruments and external thermal radiation on the structure. An effective rational control algorithm, providing compensation of the thermal gradient of the load-bearing structure to an acceptable level, is proposed. The control algorithm and the system structure are designed to be implemented by special software of the onboard computer.

Automatic control system of the mechatronic module

The paper discusses a new approach to improving the accuracy of reproducing the task signal by a precision circular transfer table based on the implementation in the form of a mechatronic module. This design eliminates the disadvantages of the traditional design, such as backlash, failure when fixing the face-plate. The mechatronic module is a gearless connection between the face-plate and the electric motor. The new design required a new approach to the operation of the automatic tracking and stage positioning control system. In the process of stage positioning, thermal deformations occur, and therefore, a feature is the inclusion of an additional automatic control system for the cooling of an executive synchronous electric motor with permanent magnets in the rotor. The paper deals with the issue of the interrelationship between the positioning and tracking systems with the thermal deformation compensation system. Simulation of the operation of two systems has been carried out.

Real‐time temperature estimation method for electromagnetic performance improvement of a large axisymmetric radio telescope under solar radiation

The temperature field caused by solar radiation can seriously affect the electromagnetic (EM) performances of large-aperture and high-frequency radio telescopes, and achieving the EM performance improvements under solar radiation is of great importance. In this study, combining temperature simulation and measurement, a fast estimation method of the temperature field is presented. First, a temperature database based on transient temperature field simulation is constructed in advance, and by utilising the telescope's axisymmetric structure, the dimension of the database can be greatly reduced. Then, a small number of temperature sensors are installed and the real-time measured data are applied to correct the simulation temperature field extracted from the above temperature database by the table look-up method, which can ensure the temperature field estimation speed. Thus, based on the real-time estimated temperature field and the telescope's finite element model, thermal deformations can be calculated in real-time and used for deformation compensation. A 7.3 m reflector antenna with 21 temperature sensors is adopted to verify the proposed strategy, and the results show the effectiveness and feasibility of the strategy. This study can provide helpful guidance for the real-time compensation of thermal deformations derived from large axisymmetric telescopes.

A Linear Regression Thermal Displacement Lathe Spindle Model

Thermal error is one of the main reasons for the loss of accuracy in lathe machining. In this study, a thermal deformation compensation model is presented that can reduce the influence of spindle thermal error on machining accuracy. The method used involves the collection of temperature data from the front and rear spindle bearings by means of embedded sensors in the bearing housings. Room temperature data were also collected as well as the thermal elongation of the main shaft. The data were used in a linear regression model to establish a robust model with strong predictive capability. Three methods were used: (1) Comsol was used for finite element analysis and the results were compared with actual measured temperatures. (2) This method involved the adjustment of the parameters of the linear regression model using the indicators of the coefficient of determination, root mean square error, mean square error, and mean absolute error, to find the best parameters for a spindle thermal displacement model. (3) The third method used system recognition to determine similarity to actual data by dividing the model into rise time and stable time. The rise time was controlled to explore the accuracy of prediction of the model at different intervals. The experimental results show that the actual measured temperatures were very close to those obtained in the Comsol analysis. The traditional model calculates prediction error values within single intervals, and so the model was divided to give rise time and stable time. The experimental results showed two error intervals, 19µm in the rise time and 15µm in the stable time, and these findings allowed the machining accuracy to be enhanced.

Thermal Deformation Compensation of Laser Tracker Relocating in Aircraft Assembly

During aircraft assembly, measurements from either a single or multiple laser tracker with different positions are transformed to an assembly coordinate system by measuring the enhanced reference system (ERS) points via a rigid-body registration method. The location deviations of the ERS points resulting from thermal deformations have become the major error source in registration. To improve the accuracy of measurement, a thermal deformation compensation method, based on precise thermal deformation theory, is proposed in this study. Thermal deformation coefficients of ERS points in X-, Y-, and Z-axes are calculated separately, and an iterative algorithm is developed to correct the actual locations of the ERS points and estimate the optimal coordinate transformation parameters. A case study indicated that, with our proposed novel thermal deformation compensation method, the average registration error is decreased by 9.2–38.7%, and the maximum registration error is deceased by 12.3–38.6%.

Real-time thermal deformation compensation method for active phased array antenna panels

The electromagnetic (EM) performance of active phased array antennas (APAAs) is significantly influenced by thermal deformation of the antenna panels caused by thermal power consumption and ambient temperature change. This paper proposes a method to reduce the influence of thermal deformation on the EM performance of small APAAs via real-time compensation. In the proposed method, a thermal deformation prediction model is first constructed based on analysis of experimental data. The model is then used to accurately predict thermal deformation based on the measured values of several key temperature sensors in real time, and the EM performance is compensated by adjusting the array phase difference controlled by a phased shifter according to the predicted results. The results of experiments conducted indicate that the thermal deformation model has high prediction accuracy, and the decrease in EM performance caused by antenna panel thermal deformation is effectively reduced by the proposed method. Thus, the proposed method has positive implications for improving the overall performance of APAAs.

Compensation of Thermal Deformations of Heat Supply Net¬work with Radial Expansion Bends

Compensation of Thermal Deformations of Heat Supply Net¬work with Radial Expansion Bends

Hybrid modelling for thermal deformation prediction of high speed motorized spindle

Thermal-induced deformation accounts for 40-70% of the total dimensional and shape errors that arise from various sources of machine tools. This paper suggests a hybrid model based on regression-based analysis and computation-based simulation to predict the thermal deformation of high speed motorized spindle. COMSOL Multiphysics was used to obtain the numerical solutions of the thermal deformation, and the PLS algorithm was used to modify the error between the simulation model and the experimental data collected from the spindle test system. The experimental results showed that the proposed hybrid model could predict thermal deformation effectively and accurately, and it can be used for real-time thermal deformation compensation to improve the machining accuracy of NC machine tool.

Thermal error control method based on thermal deformation balance principle for the precision parts of machine tools

A new thermal error control method based on the thermal deformation balance principle is suggested to control the thermal error of a precision machine tool’s functional parts, which negatively affects processing precision. The compensation of the thermal expansion of metal by the thermal contraction of carbon fiber reinforced plastics (CFRPs), which has a negative linear expansion coefficient, lies behind this method. The metal structure is bonded with CFRP bandage and thermoelectric modules to achieve the temperature difference between the metal and the CFRP, thereby realizing the same thermal deformation. The heat transfer channel in the compensation system for thermal deformation is designed by the structural topology design method to distribute the heat evenly. Experimental and numerical simulation results show that the suggested approach reduces thermal displacement by 93% compared with the metal structure without the CFRP bandage. The suggested method can be applied to thermal deformation compensation for various high-precision equipment, including coordinate measuring machines, aerospace equipment, and optics and optical instruments.

Modelling and compensation of thermal deformation for machine tool based on the real-time data of the CNC system

As one of the main issue affecting the precision and stability of the machine tool, thermal deformation is determined by the environmental temperature as well as the heat generated in the working process of machine tool. Currently, research work on the modelling of thermal deformation mostly rely on the data retrieved from temperature sensors embedded or amount on the machine tool, where the thermal deformation is modelled as function of temperature field in the machine tool. Thermal deformation thus modelled is normally impractical in the thermal compensation process because of the high cost and low stability it may incur when a set of temperature sensors are utilized. In this paper, a novel approach for modelling and predicting the thermal deformation of ball screw is proposed. Instead of relying on the data from temperature sensors, the real-time data of the CNC system, e.g., current and velocity of driving motor, and displacement of axis, is utilized directly to derive the thermal deformation model. With such data, a model is firstly built with considering the heat generated from friction motion as well as the heat dissipation with the machining environment; the parameters of the proposed model were then identified by a multiple linear regression method. Based on the proposed model, the thermal deformation of ball screw can be precisely estimated in both the warming up and cooling down state of the machine tool, as validated by experiments on a ball screw of a small size machine tool.

Predictive compensation of thermal deformations of ball screws in CNC machines using neural networks

Predictive compensation of thermal deformations of ball screws in CNC machines using neural networks

Sensorless compensation system for thermal deformations of ball screws in machine tools drives

Abstract The article presents constructional, technological and operational issues associated with the compensation of thermal deformations of ball screw drives. Further, it demonstrates the analysis of a new sensorless compensation method relying on coordinated computation of data fed directly from the drive and the control system in combination with the information pertaining to the operational history of the servo drive, retrieved with the use of an artificial neural networks (ANN)-based learning system. Preliminary ANN-based models, developed to simulate energy dissipation resulting from the friction in the screw-cap assembly and convection of heat are expounded upon, as are the processes of data selection and ANN learning. In conclusion, the article presents the results of simulation studies and preliminary experimental evidence confirming the applicability of the proposed method, efficiently compensating for the thermal elongation of the ball screw in machine tool drives.