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Data-based methods are capable to monitor machine components. Approaches for semi-supervised anomaly detection are trained using sensor data that describe the normal state of machine components. Thus, such approaches are interesting for industrial practice, since sensor data do not have to be labeled in a time-consuming and costly way. In this work, an ensemble approach for semi-supervised anomaly detection is used to detect anomalies. It is shown that the ensemble approach is suitable for condition monitoring of ball screws. For the evaluation of the approach, a data set of a regular test cycle of a ball screw from automotive industry is used.

The positioning precision of a half-closed-loop feed system of machine tools is usually affected by the frictional heat of the system. The axial thermal errors of the working table exceeding the axial allowed tolerance is a type of failure mode of the ball screw system in positioning precision. At present, thermal error prediction and compensation methods have poor accuracy retention because they do not consider the randomness of the parameters. In order to solve the problem, we present a new random moving difference method of studying a tree-like heat transfer with thermally excited moving branches. Furthermore, based on the random moving difference method, a dynamic reliability prediction model (DRPM) of thermally deduced positioning precision is proposed, which was used in the study for predicting the dynamic variation performance of the heat boundaries in the ball screw feed drive system and the dynamic reliability of positioning precision of the system. Finally, the prediction performance of the presented method is verified under a CNC lathe. Our method provides the theoretical and practical foundation for a real-time monitoring positioning precision reliability index while describing the positioning precision accurately because it effectively takes into account the random parameters.

The feed system of machine tool has complex nonlinear dynamic behaviors in the process of machining, which will affect the machining accuracy of parts. The two-degrees-of-freedom dynamical model of the feed system with clearance and friction is established, where the torsion and load disturbance are considered. By using the averaging method, the approximate analytical solution of the feed system of the machine tool is solved. The approximate analytical solutions are verified by the numerical solutions, when the worktable moves at a constant speed or the worktable is at the working point. And the approximate analytical solutions are in good agreement with the numerical solutions. According to the Lyapunov stability analysis, the stability of the steady-state solutions of system is judged by the maximum real part of the eigenvalues. The analysis results show that, the amplitude of the amplitude-frequency response of system decreases when the friction force increases. As the clearance increases, the resonance frequency decreases gradually. When the lead of the ball screw increases, the resonance peak and resonance frequency increase gradually. The numerical simulation analysis of the system shows that when the worktable is at the working point, the angle displacement of the lead screw chatters while it reaches the maximum or minimum value of the vibration angle displacement.

Thermal errors affect the accuracy of computer numerical control machine tools and are produced by the thermal deformation of machine components due to temperature difference between heat source and ambient temperature of the machine tools. At present, most of the literature does not consider the randomness of the influencing factors of thermal error, leading to inaccurate predictions of machine tool thermal error. In this paper, a new inverse random model is proposed through the combination of the stochastic theory, genetic algorithm, and radial basis function neural network (RBFNN), to predict thermal error while considering the randomness of influencing factors. The randomness index of influencing factors can be identified using the inverse random RBFNN (IR-RBFNN). Furthermore, through the combination of the stochastic theory, RBFNN, and the improved exponential moving average method with abnormal data elimination, a new forward random radial basis function neural network (FR-RBFNN) is established according to the identified influencing factor random index. The models are verified through experimental results on a ball screw system. Compared with the traditional methods, the experimental data show that the proposed method provides a more accurate description of thermal errors while incorporating the randomness of factors affecting thermal error.

This paper proposes a novel comprehensive modeling method for deformation errors of different types of rolling joints in machine tools to improving the analysis efficiency. This method comprehensively considers the deformation of three types of rolling joints, i.e., linear guideway, ball screw and bearing, firstly from the perspective of analytical modeling. Two comprehensive models for deformation errors of all rolling joints in two types of motion systems of machine tools are established respectively with the method. The nonlinear interfacial characteristics at rolling joints and the geometric and stiffness coupling characteristics are considered. In order to study characteristics of the synthetical deformation error of rolling joints, a synthetical error model for a five-axis machine tool is developed. Several results and optimizations of the joints are carried out. The proposed method in this paper can effectively avoid the tedious finite element modeling in the traditional analysis process and improve the efficiency.

Thermally induced elongation of a screw is the primary cause of deterioration in the positioning accuracy of half-closed-loop screw systems in machine tools. The failure mode of ball-screw feed-drive systems in relation to the positioning accuracy is defined as the response error of the carriage exceeding the axial tolerance. It is still challenging to accurately predict the thermal errors using conventional methods because the randomness of the influencing factors is not considered. This paper presents an improved random thermal network model subjected to dynamic thermal excitation for calculating real-time transient temperatures of ball-screw systems. Furthermore, a time-varying reliability model is proposed for estimating the gradual reliability of the thermally induced positioning accuracy of ball-screw systems with random thermal boundary parameters using the random thermal network. A ball-screw system of a computerized numerical controlled lathe is used as an example to show the practical application of the proposed model. Repeated experiments demonstrate the accuracy retaining ability and robustness of this method. This work provides the theoretical and practical method for real-time monitoring of the positioning accuracy reliability index for ball-screw systems and it has high accuracy considering the random parameters.

The static stiffness of machine tools plays an important role in ensuring the performance of machine tools and improving the machining accuracy. In the design stage, stiffness matching provides a theoretical basis for determining the stiffness of each component. This study proposed a stiffness matching design method for machine tools. First, the deformation model of machine tools is established on the basis of the state space model. Through force analysis, the relationships between the deformations and stiffness of each part are determined. Second, the stiffness model of the machine tool is established by combining these relationships with the deformation model. Third, the objective function is determined by performing sensitivity analysis after obtaining the stiffness range. The stiffness matching design results are obtained through multi-objective linear programming. Lastly, the stiffness simulations, theoretical model, and experimental results are analyzed. The maximum errors among the experimental, simulation, and theoretical results (18.8 % and 19.9 %) are within the acceptable range. In conclusion, the proposed method is suitable for designing ball screw feed drive systems that requires rigidity.

As one of the most important part of the machine tool, thermal behaviors of the ball screw feed drive system has great effect on the positioning accuracy and machining accuracy. Finite element method is widely used for simulating the temperature of the ball screw under various working conditions. In this paper, in order to improve the simulation accuracy, the moving heat loads are considered in the finite element model, and the response surface methodology is proposed to optimize the boundary conditions. The correctness and effectiveness of the method are verified by experimental data. In addition, according to the temperature simulation results of the ball screw feed drive system, thermal equilibrium is defined and the factors which have influenced on it are analyzed.

Ball-screw drives are one of the common wear parts in machine tools. The wear will affect the positioning accuracy of motion axes and can cause a high rejection rate in production. Therefore, it is interesting to develop a method, which can detect the wear condition of ball screws at an early stage. Stiffness loss and backlash in ball-screw drives are often associated with wear. This article proposes a novel method to detect stiffness loss and backlash for ball-screw drives without preload based only on machine internal data. To simulate the wear of a ball screw, a spacer sleeve has been designed, which effectively reduces the axial stiffness of the feed axes. This design allows a quick modification of the wear status of the machine axes and can be utilized to test if the wear status is detectable by analyzing the machine internal data. A multimass model is developed and validated by experimental data, which is used to simulate the dynamic behavior of the machine axis dependent on wear.

Structural health monitoring (SHM) of the ball screw of machine tools relies on the repeated observation of the damage-sensitive features. The natural frequency is a characteristic inherent to the structure that is more robust than other signal features as a SHM index. However, a major problem is that regular changes in the operating conditions, such as the feed speeds, the worktable positions and other uncertain complex boundary conditions, also affect the natural frequencies, and these factors may mask the subtle variations induced by structural damage. Therefore, it is necessary to adopt an effective method to eliminate those effects to avoid false alarms during structural damage monitoring. In this article, Bayesian ridge regression modelling methods are developed to eliminate the effects of the worktable different positions and feed speeds on the natural frequencies. The proposed method can model the natural frequencies that are simultaneously affected by two dimensional operational factors and provide a rigorous quantitative assessment of the uncertainties associated with the complex boundary conditions of the ball screw drive system and the inevitable estimation errors. First, the different worktable positions and feed speeds were tested on the experimental bench to verify the proposed method. Then, two novel criteria were used as damage warning signals, which can reduce false alarm. Finally, this method was applied to monitor the wear of a ball screw of a CNC machining centre in an automobile factory. The validity of the method was provend using actual monitoring results.

This paper presents a novel electromechanical brake (EMB) with automatic wear adjustment function, which has been ignored in most previous studies. With the aim of investigating the parameter characteristics of the EMB system and analyzing the proposed function, the mathematical models of the DC motor, motor friction, worm drive, ball screw and load are established in MATLAB/Simulink. The differences between the simulation and the experiment under step, triangular wave, square wave and sinusoidal input signals are discussed. The parameter characteristics of clamping force-motor current and clamping force-ball screw displacement are obtained, which also verifies that the established model is correct. The results demonstrate that the automatic wear adjustment function of the new EMB could guarantee that the brake stroke and response time remain consistent across each braking manoeuvre.

Ziel der Instandhaltung von Werkzeugmaschinen ist die Verfügbarkeitsabsicherung, um hohe Bauteilqualität und Produktivität zu gewährleisten. Die Kenntnis des Vorschubachsenzustandes, im Besonderen des Kugelgewindetriebs, ist daher von enormer Wichtigkeit. Das „Guard-Plus“-System, eine Entwicklung der August Steinmeyer GmbH und der ifm diagnostics GmbH, ermöglicht dies durch Detektion des Vorspannungsverlustes aufgrund von Verschleiß. Untersuchungen zur Systemfunktion wurden in diesem Beitrag durch das wbk Institut für Produktionstechnik durchgeführt. The aim of machine tool maintenance is to ensure availability in order to guarantee high product quality and productivity. Knowledge of the wear condition of feed axes involved, especially the ball screw, is therefore of enormous importance. The Guard Plus system, a joint development of August Steinmeyer GmbH and ifm diagnostics GmbH, enables this by detecting the preload loss due to wear. Investigation of the system’s function are presented through wbk Institute of Production Science in the following article.

This paper deals with the precision modelling of the ball screw unit’s thermal behaviour in the turning centre and its impact on the tool head positioning error. The error components along controllable axes X and Z are described in detail using an FE model integrating the changes in thermal and force loads and deformations occurring during the motion of the nut as a heat source. The impact of the nut work cycle on the thermal deformations of the ball screw and the displacements of the slideways and the screw points along both the axes and on carriage positioning precision is demonstrated.

A spindle feed system is continuously subjected to cutting forces, cutting heat and frictional heat during machining processes, which interact to form a complex, nonlinear and thermal-force coupling field. The coupling field causes deformations and vibrations of the mechanism that affect the machining accuracy. Therefore, determining the thermal-force coupling dynamic characteristics of the mechanism is beneficial, as it lays the theoretical foundations for accurate error compensation and the design and optimization of the spindle feed system. The deformation of the spindle feed system in actual working processes is approached by modeling, simulation and verification. Based on the theory of mechanics and heat transfer, the models for the transient milling force and the temperature field are established to obtain the real-time, dynamic cutting force and the associated heat values. A thermo-mechanical coupling model is also deduced, and the deformations generated by the cutting force and heat are simulated using the finite element method. Moreover, the thermo-mechanical coupling deformations of the system are emulated. The above deformation results are tested and confirmed. This paper establishes the deformation rules under the cutting force and cutting heat as well as their associated coupling effects. When studying thermo-mechanical coupling, the initial deformations of the ball screw are dominated by the cutting forces. The effects of heat on the X-direction deformations gradually exceed the effects of the cutting forces. The Y-direction deformations are primarily caused by the forces, with little influence from the heat. The Z-direction deformations are mainly caused by the heat, with negligible influence from the forces.

Being a critical factor affecting the motion accuracy of precision machine tools, structural thermal elongation of precision ball screw unit is generally caused by the comprehensive influence from heat generations of screw-nut pair / bearings and time-varying ambient temperature. To resist 2 thermal disturbances above to guarantee precisely the original length of screw shaft, an active coolant control strategy is proposed in this paper. This strategy is based on an empirical model: For the slender and long tubular structure of screw shaft, the screw shaft temperature is approximately equal to its recirculating coolant temperature. The reason is that the intensive forced coolant convection is capable of eliminating screw shaft temperature rises caused by friction heat generations and ambient air convections. Based on this premise, screw coolant temperature can be consistently controlled by an active strategy, further to correct the thermal elongation of screw shaft. It can be experimentally verified that the thermal variations of machine positioning accuracy caused by the active coolant control strategy are not more than 10µm, which are lower than traditional strategy. Besides, based on detected structural temperatures of precision ball screw unit, the empirical model above is further proved to be reliable by FE simulation method.

In a vertical machining centre (VMC) heat generation occurs due to the movement of the machine tool components. This heat generationand surrounding air temperature create temperature rise in the machine tool. Due tothe temperature rise, the tool centre point (TCP) displaces which leads to inaccuracy and loss of precision in machined components. VMC base is one of the major componentsof a machine tool contributing to TCP displacement. In VMC base, thermal deformation of the guideway is caused by heat generation of linear motion bearing, and thermal deformation of the feed drive system is caused by ball screw movement. Further, the ball bearing also contributes to TCP displacement. Epoxy granite is used as a replacement for conventional cast iron in VMC base due to its better dynamic characteristics. But the lower thermal conductivity of epoxy granite, makes the heat to concentrate in a localised region which creates structural deformation. The present work focuses on determination of heat generation due to the frictionof linear motion bearing and feed drive system, the corresponding temperature rise and deformation of the VMC base. A mathematical model based on transfer function is also developed to predict thermal errors.

In this paper, we propose a method to monitor the preload of an operational ball screw drive system mostly used in CNC machine tools by evaluating the natural frequency of the screw nut in the axial direction and the corresponding working table displacement. First, we derived a discrete dynamic model and used it to study the variation in the ball screw system preload. Second, we proposed a method for monitoring the ball screw preload in operational mode via the motor current signal and the screw nut axial vibration signal. We apply this method by acquiring and analyzing the signals from the system as it undergoes a transition in its motion, then compose the frequency response function (FRF) of the ball screw system. This enables us to detect the axial natural frequency of the ball screw drive system. The ball screw preload is then calculated and monitored as the system is operational. We provide an efficient and intuitive method to monitor the variation in preload level of an operational ball screw system. This method can be used as an indicator of the health status of the drive system in particular, as well as for the entire machine tool in general.

The positioning precision of the ball screw system in machine tools is primarily affected by the thermal deformation of the screw. Hence, the adaptive prediction method must be established to calculate thermal errors of the ball screw system. First, based on heat transfer theory, a new adaptive moving thermal network model of the screw system with moving thermal excitation and varying operating conditions is proposed. The time-serial data of kinematic-pair representative temperatures and the time-serial position data of the moving nut are used as inputs. This adaptive model is used to determine the temperatures of the key elements in the supporting bearings and those of the moving nut and key points of the screw shaft. Further, the heat generation rate of each kinematic pair can be obtained simultaneously. Furthermore, a real-time prediction method of thermal errors of the screw system with moving thermal excitation under various operating conditions is presented. The effectiveness and robustness of the real-time prediction method of thermal errors was verified experimentally. This method is suitable for the rapid prediction of thermal errors of screw systems by monitoring the real-time kinematic-pair representative temperatures and real-time position of the moving nut.

To enable the smart technologies and safe operation of transit and rail transportation, such as hot box detector, track health monitoring and wireless communication on the railroad side, a cost-effective energy source is in need. This paper presents the design, modeling, in-lab experiment and field-test results of a compact ball-screw based electromagnetic energy harvester with a mechanical motion rectifier (MMR) mechanism for smart railway transportation. The MMR mechanism is realized by the embedded one-way clutches in the bevel gears, which converts the bi-directional track vibration into the unidirectional rotation of the generator. Compared to previous designs, the proposed harvester has reduced backlash and thus can harvest energy from a small input of the track deflection induced by the moving train. Two prototypes with different key design parameters were built and tested. A comprehensive model considering the train-rail-harvester interaction was developed to analyze the dynamic characteristics of the coupled system and predict the energy harvesting performance of the harvesters at different train speeds. Both in-lab and field tests were carried out to examine the energy harvesting performance of the harvesters and validate the model. Field test results illustrated that an average power of 1.12 W and 2.24 W were achieved for two prototypes respectively when a Type A rapid transit passed by with a 30 km/h vehicle speed.

A common problem in motion control is the onset of vibrations due to the inertial forces when a compliant load is being displaced. It is the case of the vibration of large machine tools, but also the vibration of slender loads in pick&place. The main goal of the present work is to predict and minimise the overshoot that a compliant load moved by a servodrive suffers when it reaches the final position. Instead of modifying the control algorithm or adding dampers, the authors propose an optimal path planning based on the selection of a square sine velocity profile, a standard in machine tools NCs. Thus, a 3 degrees of freedom mechatronic model that integrates the dynamics of the drive-transmission-compliant load system and the control has been developed to predict the overshoot. Analysing the velocity profile, it has been possible to determine several values of the commanded jerk that minimize the overshoot and are related to the natural frequency of the compliant load. The prediction of the overshoot magnitude as well as the optimal jerk values have been experimentally validated in a workbench with a single axis with a ball screw transmission and a compliant load where a laser interferometer has been used to measure the overshoot.

Ball screws used for high-speed feed systems generate friction heat, which affects the preload and supporting system stiffness, and further, the dynamic characteristics of the screw system are modified and negative effects on the positioning accuracy are produced. Therefore, a thermal dynamic model for investigating dynamic performance variation with temperature is needed. First, a new dynamic temperature model of a hollow cylinder with varied heat flow was proposed based on the heat transfer theory. By using the thermocouples to read the real-time surface temperatures of heat sources, this model can be used to obtain the real-time temperature field of the supporting bearings and nut, and by using the FOCAS function to read the real-time position of nut, a finite difference heat transfer model with real-time moving heat sources was established. Based on this model, the dynamic thermally induced preload and stiffness models of the system were obtained. Second, a real-time thermal dynamic model of the ball screw system was achieved. Finally, an inverse identification method of the heat excitation was proposed. Through measuring dynamic characteristics of the feed system in machine tools, the real-time thermal dynamic models of the screw system were validated. It provided the theoretical and practical foundation for real-time monitoring and controlling of dynamic characteristics of preloaded ball screw systems.

The accurate prediction and test of the dynamic characteristics of the ball screw feed system are of great significance to the design, manufacture and improvement of the machine tool. At present, the dynamic modeling of ball screw feed system mostly ignores the influence of assembly on the dynamic characteristics of the system. In order to solve the above-mentioned problems, this paper studies the machine tool with both ends fixed ball screw, considering the influences of the pre-stretching of the lead screw on the joint of the screw and the nut. With the lead screw divided into three sections, the lumped parameter model of the ball screw feed system is established, and the influences of the lead screw pre-stretching on the natural frequency of the system are analyzed. The designed auxiliary clamping device is used to measure the frequency response of the system, which includes the translational motion and the rotational motion. The results of the experiments show that the established dynamic model can predict the dynamic characteristics of the system well. The torque wrench and the designed adaptor are used to adjust the pre-stretching of the lead screw, and the frequency response of the system are tested under different pre-stretching conditions of the lead screw. Both theoretical and experimental results show that the pre-stretching of the lead screw has a significant effect on the contact state of the screw-nut joint, which makes the natural frequency of the system change obviously.

Ball screw mechanism (BSM) plays a key role to transmit motion and power in a machine tool. The accuracy of the machine tool is greatly influenced by the accuracy of the BSM. Since accuracy degradation of BSM is primarily due to wear, the wear behavior of BSM is studied considering the time-varying motion and loading working conditions. A new wear prediction model of BSM is introduced in this research considering complex working conditions. Because BSM is subject to dynamic fluctuations of rotational speed and loading in the operation process, a loading model is established to describe the dynamic contact force between the ball and the raceway, and a motion model is developed to describe the dynamic sliding and rolling behaviors between the ball and the raceway. The degradation of BSM accuracy is analyzed considering time-varying motion and loading working conditions. Experiments have also been designed and conducted to demonstrate the effectiveness of the accuracy degradation analysis for BSM.

Precision locknuts are widely used in rotary machinery especially the machine tools operating in high speed with high precision. The flank-locking locknut studied in this paper is mainly employed in spindle and ball screw assemblies of machine tools to secure the preloading in the bearings required for better structural stiffness. In service the locknuts often suffer corrosion from the harsh machining environment. The possible effects of corrosion on the surface morphology of locknut, such as flatness and roughness, and its performance were investigated. The locknut was submerged in a 5% NaCl solution following ASTM B895 standard for different durations- 1, 2, and 4 h to speed up the possible corrosion. The treated locknut was then undergone assembling test following ISO 2320 standard. The flatness and roughness on the end face and threads were measured along with microscopic examination. It was found that with increasing duration of corrosion, the surface flatness and roughness became worse. However, the tightening constant of the locknut showed a positive correlation with the increased surface roughness raised by the corrosion treatment.

High-speed machining is a key technology for greatly improving productivity and reducing production costs. Angular contact ball bearing is the key component of ball screw feed system. Predictive analysis of bearings thermal behavior is significant to ensure the working accuracy of machine tools. Due to the continuous dynamic changes under actual working conditions, it is difficult to predict and model of the bearings heating characteristics. This paper develops a comprehensive calculation method for predicting the thermodynamic characteristics on high speed feed shaft bearings. Based on quasi-static model and thermal dynamic model, Monte Carlo optimization algorithm is used to inverse the temperature field experimental temperature data. The real heating characteristics of heat source are comprehensively predicted and analyzed, so as to accurately predict the bearing thermal dynamic performances of feed shaft bearings. The research work in this paper lays a strong foundation for the thermal error modeling and thermodynamic analysis of the ball screw feed system of machine tools.

The ball screw is one of the essential components of a machine tool and identifying its degradation level is therefore critical for the health management of the entire machine tool. This paper proposes a new method to automatically and reliably discriminate the defect level of the ball screw. In this method the multiple classifier system (MCS), rather than the single classifier system, is used for severity differentiation in order to enhance the classification accuracy. We adopt the dynamic classifier selection (DCS) strategy for the MCS and design a novel local class accuracy technique (N-LCA) to replace the conventional local class accuracy technique (LCA) for DCS, so that the performance of the DCS strategy can be significantly improved. Since the LCA selects the most suited classifier for a testing object by estimating each classifier’s competence in the sample’s neighborhood, how to define such a neighborhood has a direct influence on the performance of the LCA. In the N-LCA, the neighborhood components analysis algorithm is introduced to adaptively and accurately determine the neighborhood for better tackling the difficulty in a reliable local accuracy evaluation. Eventually, a new MCS is constructed with the N-LCA to better discriminate the ball screw degradation severity, and its effectiveness is verified by our experimental results.

This paper presents a new mechanical design of an anthropomorphic robot hand. The hand is designed such that it is adaptive, backdrivable, modularized to provide both dexterity and robustness. The hand has 18 joints, 14 degrees of freedom, and a new joint mechanism called an active DIP–PIP joint for the robot finger. The mechanism includes a pair of movable pulleys and springs for generating both linked and adjustable motions. Although the set of DIP (distal interphalangeal) and PIP (proximal interphalangeal) joints exhibits a coupled movement in free space, it moves adaptively when it contacts an object. To ensure a 1:1 ratio movement when a finger is moving freely and to produce additional joint torque when gripping an object, torsion springs are attached to each joint. The backdrivability of each joint is realized using an actuation module with a miniature BLDC motor and a ball screw. In addition, the relatively unknown intermetacarpal joints, which provide additional dexterity to the hand for grasping small objects, are used in the robot hand model. A modularized design simplifies the assembly of the hand and increases the economic feasibility. Experimental results are included in this paper for validating the design of the robot hand.

To establish the dynamic model of machine tool structure is an important means to assess the performance of the machine tool structure during the cutting process. It’s necessary to study the dynamics of the machine tools in different configurations for the sake of analyzing the dynamic behavior of the machine tools in the entire workspace. In this paper, a robust approach is presented to build an efficient and reliable dynamic model to evaluate the position-dependent dynamics of the twin ball screw (TBS) feed system. First, the TBS feed system is divided into several components and a finite element (FE) model is built for each component. Second, the Craig-Bampton method is proposed to reduce the order of the substructures. Third, a multipoint constraints (MPCs) method was introduced to model the mechanical joints substructures of the TBS system, and the spring-damper element (SDE) is employed to connect the condensation nodes. Finally, a series experimental tests and full order FE analysis are conducted on the self-designed TBS worktable in the four positions to validate the effectiveness of the proposed dynamic model. The results show that the proposed approach evaluates accurately the position-dependent behavior of the TBS system.

The CNC machine tool feed axesdrives includecomplex transmission mechanisms having mechanical and thermal errors, which adversely affect the geometrical accuracy. Proper axes drive configurations haveto be designed along with advanced control systems to compensate for various errors. For achieving a precise axis control, accurate measuring systems are required along with advanced position sensors (scales and encoders)and laser interferometers A complete check on a machine tool is made for kinematic errors which include linear positional errors, repeatability, reverse errors, pitch. The Renishaw laser diagnostic equipment, model ML10 is used for dynamic measurements of slides that reveal drive errors and stick-slip motion. The laser calibration is carried as per JIS B-6330 in effecting immediate mechanical adjustments on the machine and software compensation in the control system. For the feed sub-assemblies to have a high degree of positional accuracy and repeatability at high-speed machining, thermal error compensation has to be done. Heat generation takes place at ball screw, bearings, and guideways, causing non-uniformtemperature distribution and causes thermal deformation. The sub-assembly involves the feed motor, recirculating ball-screw, bearing assembly, and coupling mounted to slides (x and z) of the lathe machines. The ambient temperature variation, the impact of viscous friction, and the influence of cutting load affect the positional and machining accuracy. In the present work, the thermal deformations in the feed motor assembly are calculated theoretically usinga heat transfer approach and are validated experimentally using laser-interferometer calibration. Also, a statistical analysis is presented for the Z-axis feed drive, and the results are in agreement with the laser-interferometry experiments.

For a slender ball-screw feed system, the position of the screw–nut joints will change greatly when the moving worktable moves along its whole stroke. Therefore, the compression/tension and torsion stiffness of the screw-shaft on both sides of the screw–nut joints will change. Thus, the system transmission stiffness will also vary and affect its dynamics. In this article, considering the changes of the worktable position and using hybrid element method, a dynamic model was established for the slender ball-screw feed system, and a calculation method of the system stiffness and mass matrix was provided. The experiments on the slender ball-screw feed system with different positions were also performed to verify the proposed dynamic model. Finally, the influences of length, screw-tension force, pitch, nominal diameter of screw and rated dynamic load of screw-nut joints on the slender ball-screw feed system’s natural frequency along its whole stroke were studied. The results showed that the slender ball-screw feed system possesses obvious position-dependent variable dynamics along its whole stroke; the ratio of length to diameter of the screw ( Lf/ d0) would be better designed smaller than 50 in order to obtain the relative uniformity of the system dynamics when manufacturing large machine tools.

The capacity of modern computer numeric control (CNC) machine tool builds on the machine design (structural rigidity, drive system, control looping, etc.), machining process (cutting speed, feed rate and cutting forces) and environment (temperature and vibrations).The linear drive system of CNC machines consists of ball screw and its associated components. The servomotor drives the feed drive system in control conditions at required speed, and providing feedback to controller of the machine. Feed drive system is responsible for the performance of linear axis of machine. The performance indicators include positioning accuracy, repeatability and backlash. The required accuracy on workpiece relies on the torque/power of axis motors. The objective of this article is to derive an equation for the computation of torque for the feed drive system of CNC machines. We have proposed two simple and easiest method of computing torque. Firstly, we computed the torque required for the running of linear axis of machine under load conditions by the first method. Secondly, the verification of computed torque has been done by the second method. Thirdly, we have analyzed three major factors like rapid rate, weight over the system and lead of ball screw to study the behavior of torque. Finally, analytical estimations have been carried out for the validation of the deployed method.

The convective heat transfer coefficient (CHTC) is a key parameter for thermal analysis. The calculation method of empirical equations cannot accurately reflect the real situation of an object, especially when the fluid temperature is a variable, making the CHTC calculation more difficult. Based on finite element (FE) thermal analysis, an iterative algorithm of FE thermal analysis combined with experimental data was proposed. Furthermore, in the thermal analysis process, the temperature of the object itself changes and the heat is not uniform. The adopted CHTCs dynamically varied with the uneven wall temperature and ambient temperature. A CHTC gradual change “dynamic boundary condition” application mode was used. The interactive iterative calculation was completed by the FE software ABAQUS 6.14 and MATLAB 2016b, and a program was written to improve the calculation accuracy of the CHTC using multiple iterations. Taking the machine tool ball screw feed system as an example, a large number of experiments were conducted over 1 year under different ambient temperatures to verify that the method described in this paper was accurate and feasible. In addition, the relationship between the CHTC and ambient temperature change was found determined, and an explanation was provided.

In order to compensate the measurement errors of the on-machine measurement system caused by the XY worktable error accurately under the influence of multiple factors, the structural characteristics of the XY worktable are analyzed in detail. The dynamic positioning error model of the XY worktable motion components such as the grating measurement systems, the ball screw assemblies, the guide rail system manufacturing errors and the friction forces under the influence of the above factors are established, and the theoretical model of the dynamic positioning error of the XY worktable is derived. It can be seen from the analysis process that the main factors affecting the dynamic positioning error are the movement speed of the worktable, the weight of the workpiece to be measured, the installation position of the workpiece and the friction force. The actual model parameters are substituted into the theoretical model to calculate the dynamic positioning error of the worktable under different influencing factors by using the technical indicators of the experimental platform. From the analysis of calculation results, it can be seen that the dynamic positioning error is the smallest when the moving speed of the worktable is 12 mm/s, and this velocity is defined as the best measuring speed，which lays a good theoretical foundation for improving the dynamic machining accuracy of machine tools and the measurement accuracy of on-line measurement system.

In precision machining, the machining conditions play an important role in part surface quality, because the characteristic of the exciting source in machine tools has a close relationship with the machining conditions. Therefore, this paper investigates the spectral characteristic of displacement fluctuation and its effect on the part surface quality for ball screw feed systems. The spectral characteristic is deduced by an equivalent disturbance model that considers the error sources of permanent magnet synchronous motor drives. In the spectrum of displacement fluctuation, the amplitudes of some spectral components increase with the load force; the corresponding frequencies are even multiples of the fundamental frequency of phase current and of the fundamental frequency of phase current plus or minus the rotor frequency. The resonance due to the variation of spectrum seriously deteriorates the part surface quality, leading to visible and characteristic patterns on the surface of machined parts. In the paper, two solutions to improve the surface quality are proposed and validated, i.e., the control method based on an adaptive filter and the method with constraint of feed rate.

The ball screw system is one of the crucial components of machine tools and predicting its remaining useful life (RUL) can enhance the reliability and safety of the entire machine tool and reduce maintenance costs. Although quite a few techniques have been developed for the fault diagnosis of the ball screw system, forecasting the RUL of the ball screw system is a remaining challenge. To make up for this deficiency, we present a model-based method to predict the RUL of the ball screw system, which consists of two parts: health indicator (HI) construction and RUL prediction. First, we develop a novel HI, weighted Mahalanobis distance (WDMD). Unlike the Mahalanobis distance (MD), which is constructed by fusing original features directly, the WDMD is formed with some selected features only, and the features are weighted before integration. Second, an exponential model is developed to describe the degradation path of the ball screw system. Then, the particle filtering algorithm is employed to combine the WDMD and the degradation model for state estimation and RUL prediction. The proposed approach is verified by a dataset obtained from an experimental system designed for accelerated life tests of the ball screw system. The results show that the WDMD has a more apparent deterioration trend than the MD and the proposed exponential model performs better than both the linear model and the nonlinear model in RUL prediction.

This work aims at the establishment of methodology to model and analyze the thermal errors of a five-axis CNC machining center, from an estimated temperature field, to finally model an artificial neural network (ANN) algorithm to accurately predict with robustness the thermal error. The thermoelastic behavior of the machining center was modeled through two different approaches: experimental (or data-driven) model and numerical (or physical) model. The thermal behavior of the machine was first modeled using finite element method (FEM) techniques based on theory of friction heat and convection heat and validated with the various experimentally raised temperature fields using temperature sensors and thermal imaging. The main machine subsystems were initially validated, such as ball screw system, linear guides, and spindle, which allowed for validating of the thermal behavior of the entire machine for five different duty cycles obtaining a maximum error of less than 8% when comparing the numerical results with the experimental results. The components of the thermal errors in X, Y, and Z directions were obtained through FEM by measuring the displacement of the spindle tip in relation to the reference bushing located on the worktable. The same procedure was experimentally performed using a touch probe system clamped in the spindle, and the results were compared obtaining a maximum deviation of 17 μm. The validation of the finite element model allowed for the use of the results obtained by the simulation to train and validate an ANN for predicting the thermal errors of the machining center. The relative errors between the thermal errors predicted by the ANN and the FEM simulation results were less than 1% indicating that the methodology developed in this work that combines the use of physical models with data-driven models is an accurate and robust tool to predict the thermal errors of the machine for various working conditions, even with the machine moving at different speeds or alternating the movement of the axles.

The positioning error of ball screw feed systems is mainly caused by thermal elongation of the screw shaft in machine tools. In this article, an adaptive on-line compensation method of positioning error for the ball screw shaft is established. In order to explore the thermal–solid mechanism of ball screw feed drive systems, the experiments were carried out. An exponential fitting equation is presented to obtain the temperature relationship between the temperature sensitive point and its center of each heat source based on the finite element method of the feed drive system. Consequently, based on time and position exponential distribution functions, a variable separation model of heat transfer is established. Furthermore, based on the heat transfer model of multiple varying and moving heat sources, an adaptive on-line analytical compensation model of positioning error is presented. Finally, the effect of the adaptive on-line analytical compensation model of positioning error is verified through the experiments. And, this model has self-adaptive ability and robustness. Therefore, this adaptive on-line analytical compensation model based on the heat transfer theory can be applied in real-time compensation of positioning error.

Due to their high efficiency and positioning accuracy, ball screw drives are the most frequently used feed drives in modern machine tools. Important properties, such as the ball screw drives stiffness and friction, depend on the load distribution and the characteristics of each rolling element contact. Detailed knowledge of the system and the contact characteristics is the basis for advanced durability and thermal modelling of ball screw drives. In this paper, a methodology to calculate ball screw drives load distribution and rolling element contact characteristics is introduced. The model is used to analyze the influence of the elastic deformation of nut and spindle on each rolling element contact with regard to the occurring forces, pressures and load angles. Experimentally measured load-displacement characteristics validate the calculation methodology.

Most feed drives in machine tools are designed using ball screw drives. The bandwidth of such drives with conventional PPI control principle is limited by the first natural frequency of mechanical transmission elements. A novel feedback control principle is presented to improve feed drive dynamics. It is cascade structured and consists of a weakly set motor speed controller, a disturbance observer with the feedback velocity of machine table and a PD position controller. This principle increases the bandwidth of the position loop over 200% without any extra sensor or actuator. Experimental results validate the effectiveness and robustness of this principle.

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.

The aim of this paper is to present a reliable methodology for condition monitoring of components of high performance centerless grinding machines. This enables the detection and localization of the defects on the ball screw. The fault detection is realized using a self-implemented classification algorithm and other pattern recognition algorithms. The diagnosis is based on acceleration and AE measurement data performed on an axis test rig using various damaged ball screws at different operating parameters. Moreover, the structure of the pattern recognition process will be introduced, this includes the signal pre-processing, the selection of the most suitable features for this specific application using MATLAB®. Finally, the evaluation of the developed solution will be showed. The actions allowing improving the accuracy of measurement data and the effectiveness of the processing algorithms, based on MATLAB® applications, are described throughout the paper. Satisfactory classification results will be obtained and discussed.

Precision double-nut ball screws are key functional parts in machine tools. The positioning accuracy of a ball screw can directly affect the machining accuracy of a machine tools. During actual use, the preload degradation and the large axial clearance of the double-nut ball screw are caused by the contact wear, which directly affects the transmission positioning accuracy. The contact wear is focused on the ball and the rough raceway surface of the ball screw. Therefore, a novel method is proposed in this paper to characterize the rough spherical morphology of raceways for ball screws based on fractal theory, and the fractal parameters of the screw and nut raceways are identified. A fractal contact model of the asperity on the raceway surface is established. By introducing contact parameters to modify the contact area, an area distribution function suitable for the coordinated contact is obtained. A mathematical model for calculating the normal contact load of the ball screw in three states is established by considering the friction factor. A precision loss model of the ball screw is established based on the full ball load distribution model and the multiscale contact load model, and the proposed model is verified by experiments. The surface contact coefficient of the inner and outer raceways is discussed. The influence of raceway fractal parameters on the wear rate is analyzed, and coupling research on precision loss and preload degradation for the ball screw is carried out. The initial wear rate under different axial load is discussed, and the change trend of wear rate with time is analyzed. The precision loss model of the preload double-nut ball screw based on fractal theory provides a new theoretical basis for accurately predicting the precision degradation and provides method support for establishing the wear life prediction of a ball screw.

The precision of machine tools is essentially determined by the feed drive control. To improve the dynamic behavior of elastic feed drives, this paper presents a novel position control concept, substituting the conventional P position controller of the industrial cascade control with a continuous sliding mode controller (SMC) together with a Kalman Filter for state estimation. The novelty of this approach lies in the focus on practical applicability: The underlying PI-cascade structure leads to low commissioning effort and the SMC controller’s parameterization is simplified to a single tuning parameter. A general compliant feed drive model is used as plant, whose parameters usually are already known from commissioning of the velocity controller. The SMC position controller is derived analytically and its stability and damping properties are investigated for the dominating mechanical mode for uncertainties of the model parameters and a wide range of controller gains. The effectiveness of the SMC-PI controller is validated for an industrial ball screw feed drive. Extensive experimental results show a considerable decrease of tracking errors in command tracking, disturbance rejection and for a high speed cutting (HSC) milling experiment compared to P-PI cascade control, while stability margins remain almost independent of the controller gains. The parameterization is discussed on the basis of a theoretical analysis and measuring results. Furthermore, excellent robustness properties regarding model errors are demonstrated.

The high demand in tracking performance is crucial in machine tools application.Therefore,the purpose of this paper is to design a Nonlinear PID (NPID) controller for improvement of tracking performance via cutting force.The method was then compared with another method which was conventional PID controller.The configuration included different cutting force disturbances of 1500rpm,2500rpm and 3500rpm.The parameters were set to 0.4Hz and 0.7Hz frequency for every 10mm and 20mm of amplitude, respectively.The investigation was centred on a comparative study of these two techniques which focused on x-axis of Googol Tech XY ball screw drive system. Results between the designed controllers were validated based on two types of errors;the maximum tracking error and root mean square error.Results showed that the NPID controller recorded better tracking performance compared to PID controller with an error reduction of about 33%. In addition,the results proved that NPID controller is highly practical and suitable to be used for ball screw drive.The controller can be further improved with the implementation of observer such as disturbance observer to compensate the cutting forces.

The positioning error of ball screw feed drive systems is mostly caused by thermal deformation of the ball screw shaft in machine tool feed systems. This paper presents an adaptive real-time model (ARTM) for predicting the temperature transient distribution and thermal error distribution of the ball screw shaft. FEM integrated with the Monte Carlo method is applied to determining the heat generation rates of two bearings, moving nut and two guides in the ball screw feed system. Then based on the data of the FEM calculations, an exponential function of the feed velocity and time is used to describe variation of the temperature difference between the measured surface point and the center of the kinematical pair with time. Finally, a numerical forecasting algorithm is developed to predict the thermal characteristics of the screw shaft and its effectiveness is verified by the experiments.

Purpose The alignment precision of existing methods is limited by the precision of detecting element and worker’s experience, which the parallelism between ball screw and guide way is not guaranteed effectively. Thus, this paper aims to propose a method of detecting ball screw’s alignment error (BSAE) via monitoring the average vibration magnitude induced by rotational frequency of ball screw (VMRFBS). Design/methodology/approach In this study, the ball screw is simplified as a freely supported beam. A mathematical model of the effect of BSAE on the contact angle of the ball and screw is established. The change of contact angle has effect on the deformation and contact stiffness according to the Hertz contact theory. To improve the accuracy of the experimental results, the VMRFBS are analyzed by using average method, and the average values of the VMRFBS at different BSAEs are calculated by using the least squares method. Findings The experimental results show that the average VMRFBS increases with the increasing of BSAE under the BSAE from 0 to 0.2 mm, while the other conditions are unchanged. Originality/value This method provides an approach to monitor the BSAE and improve the alignment accuracy of machine tools and automation equipment, which has a certain guide for improving the alignment accuracy of ball screw.

To improve the simulation accuracy of the thermal characteristic of ball screw feed drive systems, a dynamic thermal-structure coupling model, which considered the effect of the thermal contact conductance (TCC) of the solid joint on the accuracy of simulation results, was proposed to conduct thermal characteristic analysis of ball screw feed drive systems. The predictive model for TCC was proposed based on the micro morphology description of rough surfaces and the contact load distribution of solid joints. Then, the dynamic thermal-structure model of the ball screw feed drive system was established. To validate the effectiveness of the dynamic thermal-structure coupling model, thermal characteristic experiments of the ball screw feed drive system were conducted under different feed rates. The results showed that the simulation accuracy of temperature field and axial thermal elongation can be improved from 65% to 87% and from 70% to 85%, respectively.

Conventional methods of building CNC machine tools involve using linear motors and ball screw drives to obtain table motion. The double opposite sync motion design is an improvement over traditional CNC machines. In this work, an enhanced CNC gantry machine design is proposed, which exhibits a double motion mechanism. The new design is based on a rack and pinion system such that both the gantry tool and worktable are movable. The gantry’s natural frequency was designed at 202 Hz in the first vibration mode, enabling it to work at higher speeds of up to 11,530 rpm, which makes the gantry suitable for both rough cutting and fine finishing. A prototype of the multi-mode motion CNC gantry milling machine was developed to investigate the machining performance and efficiency of the double opposite sync system. Performance analysis was done using ball bar precision tests on the different modes of CNC gantry operation. Validation tests were carried out to determine the effects of the motion of the machine parts on the dimensional accuracy and surface finish of the machined parts. The results indicated that the straightness of the developed machine was reduced from 176.3 to 114.6 μm, which occurred due to the reduced total distance travelled by the tool and worktable. Moreover, the circularity increased from 338.7 to 667.0 μm. This increase could be attributed to the combination of errors arising from both the gantry and table.

Due to the requirement of the development of the precision manufacturing industry, the accuracy of machine tools has become a key issue in this field. A critical factor that affects the accuracy of machine tools is the feed system, which is generally driven by a ball screw. Basically, to improve the performance of the feed drive system, which will be thermally extended lengthwise by continuous usage, a thermal error compensation system that is highly dependent on the feedback temperature or positioning data is employed in the machine tool system. Due to the overdependence on measuring technology, the cost of the compensation system and low productivity level are inevitable problems in the machine tool industry. This paper presents a novel feed drive thermal error compensation system method that could compensate for thermal error without positioning or temperature feedback. Regarding this thermal error compensation system, the heat generation of components, principal of compensation, thermal model, mathematic model, and calculation method are discussed. As a result, the test data confirm the correctness of the developed feed drive thermal error compensation system very well.