Search Results (110)

To analyze the wear performance induced by rotor–stator rubbing in an aero-engine sealing structure under authentic operating conditions, a transonic rotor system with double bearing is constructed. This system incorporates the disk, shaft, blades, joint bolts, and auxiliary support structure. The system was evaluated in terms of its critical speed, vibration characteristics, component strength under operational conditions, and response characteristics in abnormal extreme scenarios. A ball screw-type feeding system is employed to achieve precise rotor–stator rubbing during rotation by controlling the coating feed. Additionally, a quartz lamp heating system is used to apply thermal loads to coating specimens, and the appropriate heat insulation and cooling measures are implemented. Furthermore, a high-frequency rubbing force test platform is developed to capture the key characteristics caused by rubbing. The test rig can conduct response tests of the system with rotor–stator rubbing and abrasion tests with tip speeds reaching 425 m/s, feed rates ranging from 2 to 2000 μm/s, and heating temperatures up to 1200 °C. Test debugging has confirmed these specifications and successfully executed rubbing tests, which demonstrate stability throughout the process and provide reliable rubbing force test results. This designed test rig and analysis methodology offers valuable insights for developing high-speed rotating machinery. Full article

In integrated permanent magnet synchronous motors (IPMSMs) coupled with mechanical devices such as ball screws and reducers, complex nonlinear friction characteristics often arise, leading to asymmetrical distortions such as position “flat-top” and speed “ramp-up”. These phenomena significantly degrade the system’s positioning accuracy. To address this issue, this paper introduces a symmetry-inspired nonlinear predictive speed control approach based on the Stribeck piecewise linearized friction compensation and a generalized proportional integral (GPI) observer. The proposed method leverages the inherent symmetry in the Stribeck friction model to describe the nonlinear behavior, employing online piecewise linearization via the least squares method. A GPI observer was designed to estimate the lumped disturbance, including time-varying components in the speed dynamics, friction model deviations, and external loads. By incorporating these estimates, a nonlinear predictive controller was developed, employing a quadratic cost function to derive the optimal control law. The experimental results demonstrate that, compared to traditional integral NPC and PI controllers, the proposed method effectively restores system symmetry by eliminating the “flat-top” and “ramp-up” distortions while maintaining computational efficiency. Full article

The dynamic error is the dominant factor affecting multi-axis CNC machining accuracy. Predicting and compensating for dynamic errors is vital in high-speed machining. This paper proposes a novel prediction-model-based approach to predict and compensate for the ball screw feed system’s dynamic error. Based on the lumped and distributed mass methods, this method constructs a parameterized dynamic model relying on the moving component’s position for electromechanical coupling modeling. Using Latin Hypercube Sampling and numerical simulation, a sample set containing the input and output of one control cycle is obtained, which is used to train a Cascade-Forward Neural Network to predict dynamic errors. Finally, a feedforward compensation strategy based on the prediction model is proposed to improve tracking performance. The proposed method is applied to a ball screw feed system. Tracking error simulations and experiments are conducted and compared with the transfer function feedforward compensation. Typical trajectories are designed to validate the effectiveness of the electromechanical coupling model, the dynamic error prediction model, and the feedforward compensation strategy. The results show that the prediction model exhibits a maximum prediction deviation of 1.8% for the maximum tracking error and 13% for the average tracking error. The proposed compensation method with friction compensation achieves a maximum reduction rate of 76.7% for the maximum tracking error and 63.7% for the average tracking error. Full article

Ball screws play an important role in machine tools by converting rotational motion into precise linear motion. This study evaluates and compares ball screws from two companies (TIC and NSK) through simulations and experimentation to assist in the selection process. Simulation results show that TIC exhibits a lower maximum temperature (32.6 °C) and axial deformation (119.3 μm) compared to NSK (34.05 °C and 174 μm, respectively), indicating superior thermal performance and deformation properties. An accelerated life test conducted over 240 h further demonstrates that TIC maintained more stable temperatures during continuous operation. Additional tests on the TIC ball screw include thermal displacement which is 13.5 μm after 2000 cycles of reciprocating motion. Friction torque fluctuation rate which ranges from 11.6% to 19.9%, and test bench positioning repeatability experiment shows a mean deviation of 4.99 μm from the target position. Overall, the results from this work contribute to process optimization by guiding the selection of ball screws based on their thermal performance and durability, ultimately enhancing machine tool accuracy and reliability. Full article

The surface texture technology has been applied to ball screws. However, the rough grinding surface of ball screws is not considered, and the elastohydrodynamic lubrication (EHL) characteristics and anti-friction and anti-wear mechanisms are not comprehensive and in-depth. Theoretical simulation and experimental measurement of the ground surface topography of the screw raceways are conducted to take into account the impact of the grinding surface on the EHL interaction between the ball and the raceway. The EHL model and friction torque model of ball screws have been established simultaneously, considering the ground surface topography of the raceway and the geometric features of the textures manufactured on the raceway surface. The friction reduction mechanism of the textured raceway of ball screws is elucidated in detail from the microscopic point of view, and the influence of the geometric features of the textures on the anti-friction characteristics of ball screws under different axial loads and rotation speeds is further analyzed and discussed. The proof-of-principle experiments of the friction-reducing performances of the textured raceways of the ball screws are conducted. The textured raceway of the ball screws provides an effective anti-friction effect that reduces the friction coefficient of the contact system of the ball screws by 15.2% at a normal contact force of 60.23 N, an entrainment speed of 167.5 m/s, a texture diameter of 40 μm, a texture depth of 10 μm and a texture areal density of 10%. Full article

Commercial X-EPS steering gears are characterized by high torque output, torque—with increasing capabilities, high reliability, and excellent handling precision. Among them, the screw–nut pair in the steering gear is subjected to complex working loads, and its raceways are prone to fatigue failure. To more accurately and effectively predict the fatigue life of the screw–nut pair in the steering gear, a method for dynamic simulation and fatigue life prediction of commercial X-EPS steering gears is proposed based on virtual prototyping technology and finite element theory. That is, a rigid–flexible coupling dynamic model of the X-EPS steering gear is established to obtain the load spectra of the screw and nut, and a finite-element static model is also established. Then, combined with the material S-N curve, the fatigue life is predicted through the NOCDE fatigue “five-block diagram”. The research results show that the screw and nut raceways are the key components prone to fatigue failure in the steering gear. The minimum numbers of fatigue life cycles are 1.028 × 10⁵ times and 2.9695 × 10⁵ times, respectively. Subsequently, a fatigue life bench test was conducted for verification. The results show that the error between the fatigue life analysis model of the XEPS recirculating ball steering gear and the test is less than 5%, meeting the requirements of the fatigue life test standard and design standard. Full article

This paper proposes a variable mechanism structure based on a ball screw design for precise displacement control in axial piston pumps, with the objective of improving actuator position and velocity control within the displacement-controlled (DC) systems. Traditional valve-controlled cylinder variable mechanisms (VCCVM) often suffer from limited control precision over the swash plate due to numerous uncertain parameters within the hydraulic system. To address this issue, a ball screw is utilized to replace the original valve-controlled cylinder for swash plate control, enhancing accuracy and responsiveness. In addition, an in-depth analysis of the Ball Screw Variable Mechanism (BSVM) is conducted, leading to the development of a coupled mechanical–hydraulic dynamic model. Based on this model, a controller is designed to improve system performance. Finally, the effectiveness and high performance of the proposed new structure and control strategy were validated through comparative experiments and simulations. The experimental results confirm the advantages of the proposed design, demonstrating satisfactory improvements in control precision. Full article

As the critical performance index of ball screws, the contact characteristics have a significant influence on the lubricant properties, tribological properties, and wear properties of ball screws, which further directly affect the service life of ball screws. The non-uniform load distribution induced by geometric errors results in imbalances among balls along the nut, negatively impacting the service life of ball screws. This study focuses on the load distribution of single-nut ball screws under low-speed working conditions. This paper proposes a self-adjustable model of load distribution that considers the flexibility of the screw and nut with respect to the determination of the non-bearing ball. A refined model for axial stiffness is proposed to systematically analyze the influence of geometric errors on stiffness variations under various loading conditions. The results confirm the ability of the proposed model to reveal the static load distribution in view of geometric errors. The greatest discrepancy observed between the theoretical predictions and the experimental data was 9.22%. The numerical simulations demonstrate variation trends in the normal contact load, the loaded-ball number, and the axial deformation of a nut with geometric errors. Furthermore, the relationship between the axial stiffness of a single-nut ball screw and the geometric error is obtained. The self-adjustable model of load distribution is helpful for studying the carrying capacity of a single-nut ball screw. The findings of the study provide a definite reference for optimization of structural design and wear life prediction. Full article

Swash plate axial piston pumps play an important role in hydraulic systems due to their superior performance and compact design. As the controlled object of the valve-controlled hydraulic cylinder, the swash plate is affected by the complex fluid dynamics effect and the mechanical structure, which is prone to vibration, during the working process, thereby adversely affecting the dynamic performance of the system. In this paper, an electronically controlled ball screw type variable displacement mechanism with stiffness compensation is proposed. By introducing piezoelectric ceramic materials into the nut assembly, dynamic stiffness compensation of the system is achieved, which effectively changes the vibration characteristics of the swash plate and thus significantly improves the working stability of the system. Based on this, the stiffness model of a double nut ball screw is established to obtain the relationship between piezoelectric ceramics and the double nut. An asymmetric Bouc–Wen piezoelectric actuator model with nonlinear hysteresis characteristics is also established, and a particle swarm algorithm with improved inertia weights is utilized to identify the parameters of the asymmetric Bouc–Wen model. Finally, a piezoelectric actuator model based on the feedforward inverse model and a PID composite control algorithm is applied to the variable displacement mechanism system for stiffness compensation. Full article

Studying the interactions between biological organisms and their environment provides engineers with valuable insights for developing complex mechanical systems and fostering the creation of novel technological innovations. In this study, we introduce a novel bio-inspired three degrees of freedom (DOF) spherical robotic manipulator (SRM), designed to emulate the biomechanical properties observed in nature. The design utilizes the transformation of spherical Complex Spatial Kinematic Pairs (CSKPs) to synthesize bio-inspired robotic manipulators. Additionally, the use of screw theory and the Levenberg–Marquardt algorithm for kinematic parameter computation supports further advancements in human–robot interactions and simplifies control processes. The platform directly transmits motion from the motors to replicate the ball-and-socket mobility of biological joints, minimizing mechanical losses, and optimizing energy efficiency for superior spatial mobility. The proposed 3DOF SRM provides advantages including an expanded workspace, enhanced dexterity, and a lightweight, compact design. Experimental validation, conducted through SolidWorks, MATLAB, Python, and Arduino, demonstrates the versatility and broad application potential of the novel bio-inspired 3DOF SRM, positioning it as a robust solution for a wide range of robotic applications. Full article

Many applications in manufacturing, physical therapy, and machining require linear motion stages to move back and forth at specified rates without exceeding the capabilities of the stages. Growing interest has also been in using integrated servo motors for these applications, which would benefit from the integrated nature of the motor, feedback device, and drive electronics in a single package. This paper introduces a methodology for trajectory planning for the reciprocating motion for a linear motion device. The methodology can be implemented on any device, and a simplified version can be applied to the control software for integrated servo motors. The approach develops motion trajectories, such as triangular or trapezoidal, using a dynamic model of the device and the motor’s torque–speed profile characteristics. The simplified version of the methodology was implemented using an integrated servo motor driving a ball screw stage. Tests were conducted at various motion rates and loads. The experimental results show high accuracy between the predicted and measured motion rates, particularly for rates below three cycles per second. These results suggest that the developed methodology can be a valuable tool for predicting the performance of systems that use integrated servo motors for reciprocating motion applications. Full article

Applying deep learning to unsupervised bearing fault diagnosis in complex industrial environments is challenging. Traditional fault detection methods rely on labeled data, which is costly and labor-intensive to obtain. This paper proposes a novel unsupervised approach, WDCAE-LKA, combining a wide kernel convolutional autoencoder (WDCAE) with a large kernel attention (LKA) mechanism to improve fault detection under unlabeled conditions, and the adaptive threshold module based on a multi-layer perceptron (MLP) dynamically adjusts thresholds, boosting model robustness in imbalanced scenarios. Experimental validation on two datasets (CWRU and a customized ball screw dataset) demonstrates that the proposed model outperforms both traditional and state-of-the-art methods. Notably, WDCAE-LKA achieved an average diagnostic accuracy of 90.29% in varying fault scenarios on the CWRU dataset and 72.89% in the customized ball screw dataset and showed remarkable robustness under imbalanced conditions; compared with advanced models, it shortens training time by 10–26% and improves average fault diagnosis accuracy by 5–10%. The results underscore the potential of the WDCAE-LKA model as a robust and effective solution for intelligent fault diagnosis in industrial applications. Full article

This paper addresses the issue of the high-precision control of substrate tension in an accumulator during the roll-to-roll coating process. First, a coupling model for tension errors in the substrate within the accumulator is established, along with dynamic models for the input–output rollers, carriage, and the thrust model of the ball screw. Based on these models, a simulation model is built in MATLAB/Simulink to analyze the main causes of substrate tension errors in the accumulator under uncontrolled conditions. Next, to tackle the tension errors caused by carriage displacement, a nonlinear proportional–integral–derivative (PID) controller is proposed, and a control strategy for substrate tension in the accumulator is designed. Finally, based on the established simulation model, experiments are conducted using the proposed nonlinear PID controller and the designed tension control strategy, and their performance is compared with that of a classical PID controller. The simulation results show that both the nonlinear PID controller and the classical PID controller, when combined with the proposed tension error control strategy, can reduce tension errors in the accumulator substrate. However, the nonlinear PID controller is more suitable for controlling substrate tension errors in the accumulator. On the one hand, the nonlinear PID controller has better anti-disturbance capability. In the anti-disturbance experiment, under PID control, the substrate tension error remains stable at around −1.6 N, with tension disturbances of ±0.2 N occurring at approximately 185 s and 135 s. On the other hand, the nonlinear PID controller demonstrates better robustness. In the robustness experiment, under the nonlinear PID controller, the substrate tension error fluctuates within the range of 0 to 0.02 N, showing excellent robustness. Full article

In order to realise the efficient maintenance of industrial machines, Small and Medium-sized Enterprises (SMEs) need a system that utilises digital technology to handle everything from data collection to the visualisation of the collected data in an integrated manner. In this paper, an integrated monitoring platform using external sensor devices is proposed and implemented for the purpose of preventive maintenance of industrial machines. The proposed system performs edge processing to calculate features effective for monitoring on the sensor device, collects only the obtained features, and visualises them on a web server. In order to determine the features required by edge processing, a cycle waveform cut-out algorithm was proposed. As an evaluation experiment, the proposed system was used to detect the loosening of bolts on the support side of a ball screw. The results of the analysis showed that the dispersion value immediately after the start of uniform motion from the right end to the left end was valid, so the system was implemented as edge processing in the sensor device. In wireless transmission experiments on a testbed, an average of 20 consecutive cycles were used to achieve a 99.9% correct response rate and high detection accuracy, demonstrating the usefulness of the proposed system. Full article

With the continuous development of intelligent manufacturing technology, the application of intelligent feed systems in modern machine tools is becoming increasingly widespread. Digital twin technology achieves the monitoring and optimization of the entire life cycle of a physical system by constructing a virtual image of the system, while neural network controllers, with their powerful nonlinear fitting ability, can accurately capture and simulate the dynamic behavior of complex systems, providing strong support for the optimization control of intelligent feed systems. This article discusses the design and implementation of an intelligent feed system based on digital twins and neural network controllers. Firstly, this article establishes a mathematical model based on the traditional ball screw structure and analyzes the dynamic characteristics and operating mechanism of the system. Subsequently, the mathematical model is fitted using a neural network controller to improve control accuracy and system response speed. The experimental results demonstrate that the neural network controller shows good consistency in fitting traditional mathematical models, not only effectively capturing the nonlinear characteristics of the system but also maintaining stable control performance under complex operating conditions. Full article