Search Results (27)

With the widespread use of high-speed motorized spindles in precision machining, conventional contact loading methods are no longer adequate for stiffness loading tests under high-speed operating conditions. Non-contact loading technology based on a partial-arc aerostatic radial bearing offers an effective alternative. In this study, a CFD-based hydrodynamic model was developed for the gas-film flow field in a partial-arc aerostatic radial bearing. The effects of bearing geometric parameters, such as chamber configuration, supply-orifice structure, and eccentricity, on loading characteristics were investigated. The influence of hydrodynamic effects under high-speed rotation on the loading force stability and stiffness-testing accuracy was analyzed, and an asymmetric shallow–deep composite chamber design was proposed to mitigate these effects. The results indicate that the partial-arc aerostatic radial bearing, designed based on both static characteristics and rotational performance analysis, can effectively suppress hydrodynamic effects and improve loading force stability and stiffness-testing accuracy. Full article

In high-speed spindle motors operating above 10,000 rpm, vibration analysis is essential for detecting mechanical anomalies. However, data scarcity and imbalance, especially for rare fault conditions, limit the performance of deep learning-based anomaly detection models. In this study, we define sample scarcity as the limited availability of real labeled vibration sequences for model training, i.e., only 5000 normal and 5000 faulty samples collected from three spindle motors (10,000 real samples in total). We propose a Transformer-based Variational Autoencoder (T-VAE) to generate realistic triaxial acceleration sequences for spindle motor health monitoring. The model integrates positional encoding and multi-head self-attention to capture long-range temporal dependencies in multivariate time-series data, and applies a KL annealing strategy to improve training stability. Using 5000 normal and 5000 faulty vibration samples collected from three spindle motors, the model generates 100,000 synthetic samples per class, which are used to augment training for a downstream CNN–LSTM classifier. Without augmentation, the classifier achieved 95.73% pass detection on normal samples and 81.40% fail detection on faulty samples. After augmentation with Transformer-VAE, performance increased to 98.07% pass detection for normal data and 97.99% fail detection for faulty data. For prediction, we evaluate on an independent dataset of 25,000 normal and 25,000 faulty sequences obtained from eleven different spindle motors not used in training (cross-spindle). The results demonstrate that the T-VAE effectively alleviates the data scarcity problem and significantly improves anomaly detection accuracy for high-speed spindle motor vibration signals. This approach can be directly applied to predictive maintenance systems in real-world manufacturing environments. Full article

Thermal elongation in high-speed motorized spindles constitutes a major source of machining error in five-axis machine tools, critically impacting machining precision. This study aims to develop and validate a cumulative thermal error compensation model for predicting spindle thermal elongation, subsequently enabling effective compensation via a dedicated control algorithm. Key thermal error factors, primarily spindle speed and cumulative thermal error, were identified through analysis. An innovative numerical prediction model incorporating these factors was established. Its performance was evaluated through experiments utilizing eddy-current displacement sensors for high-speed, high-precision thermal elongation measurement. The validation results demonstrated the model’s strong predictive capability: During spindle startup, prediction errors exhibited minor transients, stabilizing near zero once the operating speed was reached. Under dynamic speed changes, the maximum prediction error was only 1.28 μm, with the overall maximum residual error recorded at 2.04 μm. These findings confirm the model’s high accuracy. Furthermore, the model exhibits excellent generalization capability, delivering significant compensation effectiveness across diverse variable-speed operating conditions. This work successfully developed a highly accurate numerical model and a practical compensation strategy, significantly enhancing the positioning accuracy of high-speed spindles against thermal disturbances. The proposed approach offers substantial engineering utility for thermal error compensation in precision machining applications. Full article

This study focuses on an experimental device for the adaptive adjustment of the preload of high-speed motorized spindles. Firstly, based on Hirano’s criterion, the optimal preload for bearings at different rotational speeds was determined, and an adaptive preload adjustment mechanism was developed, with its accuracy experimentally validated. Secondly, the optimal lubrication conditions were obtained by a single-factor experiment. Then, the vibration characteristics under different preload conditions were explored, and the axial displacement variations were analyzed across a range of rotational speeds. Finally, the temperature rise in the bearings with the speed at the constant preload force and the optimal preload force were compared. The results demonstrated that the adaptive preload adjustment device outperformed the constant preload application. In teaching practice, this study enhanced students’ systematic understanding of the adaptive preload adjustment process in motorized spindles, promoted the integration of theoretical knowledge with practical application, and strengthened their learning interest. In addition, this device can provide experimental equipment for studying the performance of high-speed motorized spindles and bearings in scientific research. Full article

The electric spindle serves as a critical component in enabling a highly dynamic response, stable torque output, and precise motion control for the main cutting operations of CNC machine tools. The design precision and control performance of its drive motor directly influence the geometric accuracy, surface quality, and overall machining efficiency of the workpiece, thereby determining the comprehensive performance of advanced CNC systems. This paper begins with a systematic review of the global industrial layout of CNC machine tool and electric spindle manufacturers, highlighting regional clustering patterns and technological development trends across key manufacturing regions. Subsequently, it classifies and elaborates on the differentiated technical requirements for the electric spindle motor in terms of wide-speed-range servo capability, high-efficiency operation, adaptability to high-speed and high-power cutting loads, and precision maintenance under high-speed conditions, based on the process characteristics of different types of CNC machine tools. A comprehensive overview of the current state of research is provided with respect to electric spindle motor design and control technologies. Finally, forward-looking perspectives are presented on future development directions, particularly in the areas of multi-physics coupling co-design and the integration of intelligent control algorithms, aiming to offer a solid theoretical foundation and strategic guidance for the advancement and engineering application of high-performance electric spindles. Full article

In the application of an aerostatic motorized spindle, given the different requirements for the optimal gas film thickness of gas bearing under various processing conditions, this paper puts forward the tapered aerostatic bearing as the radial support element of the spindle and realizes the adjustability of gas film gap in a particular range through the axial fine-tuning mechanism. A 5-DOF dynamic model of the bearing rotor system is established, and the transient Reynolds equation is solved using the finite difference method to obtain the pressure distribution characteristics of the gas film. Based on this, the spindle’s translation and angular displacement responses are determined by solving the spindle’s motion equation. The simulation results show that the tilting motion of the spindle significantly affects the pressure distribution of the gas film, and the nonlinear gas film force will lead to nonlinear severe vibration of the spindle. The study also reveals that reducing the gas film thickness under low-speed and heavy-load conditions effectively decreases the amplitude and offset of the spindle. However, increasing the gas film thickness enhances the system’s speed and stability under high-speed and light-load conditions. Full article

Grease lubrication is cost-effective and low-maintenance for motorized spindles, but standard steel bearings can fail at high speeds. This study focuses on high-speed full ceramic ball bearings lubricated with grease. The coefficient of friction torque in the empirical formula is corrected by establishing the heat generation model of full ceramic ball bearing and combining it with experiments. A simulation model of grease flow is established to study the influence of grease filling amount on grease distribution. The simulation model of the temperature field of a full ceramic ball bearing is established to analyze the influence of rotating speed on bearing heat generation, and experiments verify the calculation results of the theoretical model. The results show that an optimal grease filling amount of 15~25% ensures even distribution without accumulation. Additionally, when the amount of grease is constant, the outer ring temperature increases with higher rotating speeds. The test results show that when the grease filling is 0.9~1.2 g, it accounts for about 9~12% of the volume of the bearing cavity, and the temperature of the outer ring is the lowest. At a rotation speed of 24,000 rpm, the outer ring temperature of the grease-lubricated bearing is 50.1 °C, indicating a reasonable range for use in motorized spindles. It provides a theoretical basis for the optimization design of macro-structural parameters of full ceramic ball bearings in the future, which can minimize heat generation and maximize bearing capacity. Full article

In high-speed motors, there is a huge amount of heat generation from core and winding losses, which may result in thermal failures or motor performance deterioration. In the prevention of heat accumulation, efficient cooling technology is critical for smooth and reliable motor movement. This paper summarizes the diverse application of high-speed motor and thermal requirements, such as in electrical devices, turbo-machinery, and high-precision machine tools. Three paths of case convection—cooling, internal ventilation cooling and spindle core cooling—are analyzed. Methods for configuring thermal resistance and improving cooling efficiency are summarized. Among them, coolant flow characteristics and flow channel shapes, gas supply ventilation systems, and methods to reduce air resistance, as well as axial cooling and integrated heat pipe structures, are extensively investigated. Finally, the development prospects of high-speed motor cooling are also forecasted. At present, the primary research directions are to reduce the heat generated by the heat source, utilize the latent heat of the coolant, optimize the cooling flow path of the shell, design an axial air-cooling circulation system, and enhance the heat dissipation of the spindle. Full article

Understanding the temperature–working condition relationship is crucial for optimizing machining processes to ensure dimensional accuracy, surface finish quality, and overall spindle longevity. Monitoring and controlling spindle temperature through appropriate cooling systems and operational parameters are essential for efficient and reliable machining operations. This paper presents an in-depth analysis of the thermal equilibrium and deformation characteristics of a high-speed motorized spindle unit utilized in grinding machine tools. Through a series of thermal equilibrium experiments and meticulous data acquisition, the study investigates the nuanced influence of various working conditions, including spindle speeds, coolant types, and coolant flow rates, on spindle temperatures and thermal deformations. Leveraging the power of Artificial Neural Networks (ANNs), predictive models are meticulously developed to accurately forecast spindle behavior. Subsequently, the models are seamlessly transitioned to a cloud computing infrastructure to ensure remote accessibility and scalability, facilitating real-time monitoring and forecasting of spindle performance. The validity and reliability of the predictive models are rigorously assessed through comparison with experimental data, demonstrating excellent agreement and high accuracy in forecasting spindle thermal behavior. Furthermore, the study underscores the critical role of key working condition variables as precise predictors of spindle temperature and thermal deformation, emphasizing their significance in optimizing overall spindle efficiency and performance. This comprehensive analysis offers valuable insights and practical implications for enhancing spindle operation and advancing the field of grinding machine tools. Full article

Given motorized spindles’ extensive periods of prolonged high-velocity operation, they are prone to temperature changes, which leads to the problem of thermal error, leading to diminished precision in machining operations. To address the thermal error issue in motorized spindles of computer numerical control (CNC) machine tools, this study proposes a pelican optimization algorithm (POA)-optimized convolutional neural network (CNN)–long short-term memory (LSTM) hybrid neural network model (POA-CNN-LSTMNN). Initially, the identification of temperature-sensitive locations in the spindle system is performed using a combination of hierarchical clustering, the K-medoids algorithm, and Pearson’s coefficient calculation. Subsequently, the temperature data from these identified points, along with real-time collected spindle thermal error data, are employed to construct the model. The Pelican optimization algorithm is used to enhance the model parameters to achieve the best performance. Finally, the proposed model is subjected to a comparative analysis with other thermal error prediction models. Drawing from the experimental findings, it is evident that the POA-CNN-LSTMNN model exhibits superior prediction performance. Full article

The high-speed motorized spindle has been wildly used in the field of aerospace processing, due to its advantages such as high speed, high precision, and high efficiency. CNC machine tools used for processing aerospace products require high machining accuracy, and once the spindle fails, it will seriously affect the quality of product processing. Thus, it is important to study the faults of the spindle, especially the faults caused by subtle errors. In this work, a dynamic model of a spindle with unbalanced mass fault and spindle inclination fault is established, and the natural frequencies and mode shapes of the motorized spindle are calculated by using the whole transfer matrix method (WTMM). The deflections of the spindle initial end in the different situations are discussed when the two faults happen independently. The results show that the spindle end deflection of the same fault has different sensitivity at different speeds. At the third order of natural frequencies, the deflection of a motorized spindle is greatest regardless of the fault that occurs. Although the motorized spindle rotates at the same speed, different faults could cause different mode shapes. At the lower speed, when the unbalanced mass fault happens, the mode shape is in an arched shape, and while the spindle inclination fault happens, the mode shape is in a concave shape. Full article

This comprehensive study investigates the micro-milling of a Mg13Sn alloy, a material of considerable interest in various high-precision applications, such as biomedical implants. The main objective of the study was to explore the optimizations of variable feed per tooth (fz), cutting speed (Vc), and depth of cut (ap) parameters on the key outcomes of the micro-milling process. A unique experimental setup was employed, employing a spindle capable of achieving up to 60,000 revolutions per minute. Additionally, the study leveraged linear slides backed by micro-step motors to facilitate precise axis movements, thereby maintaining a resolution accuracy of 0.1 μm. Cutting forces were accurately captured by a mini dynamometer and subsequently evaluated based on the peak to valley values for Fx (tangential force) and Fy (feed force). The study results revealed a clear and complex interplay between the varied cutting parameters and their subsequent impacts on the cutting forces and surface roughness. An increase in feed rate and depth of cut significantly increased the cutting forces. However, the cutting forces were found to decrease noticeably with the elevation of cutting speed. Intriguingly, the tangential force (Fx) was consistently higher than the feed force (Fy). Simultaneously, the study determined that the surface roughness, denoted by Sa values, increased in direct proportion to the feed rate. It was also found that the Sa surface roughness values decreased with the increase in cutting speed. This study recommends a parameter combination of fz = 5 µm/tooth feed rate, Vc = 62.8 m/min cutting speed, and ap = 400 µm depth of cut to maintain a Sa surface roughness value of less than 1 µm while ensuring an optimal material removal rate and machining time. The results derived from this study offer vital insights into the micro-milling of Mg13Sn alloys and contribute to the current body of knowledge on the topic. Full article

The cooling performance of motorized spindles plays an important role in accuracy in high-speed machining. Aiming at improving the cooling performance of traditional motorized spindles, convex columns were built in the cooling channel. Based on field synergy, the effects of quadrilateral, circular and triangular convex columns on the heat transfer performance of the cooling channel were analyzed numerically. We also compared the pressure drop between the inlet and outlet under the same conditions. The results show that the cooling channels with triangular convex columns provide the best cooling effect with the smallest increase in area compared to quadrilateral convex columns and circular convex columns. The pressure drop in the cooling channels with a circular convex column is minimized. By optimizing the spacing of the convex column, the best effect was found at a spacing of 7 mm. By optimizing the angle of the top angle of the triangular column, it is found that the enhanced heat transfer effect is best at 120° when the heat transfer area is the same. In addition, when considering the addition of convex columns, it is important to ensure sufficient pressure drop to achieve a good cooling effect. Full article

The surface accuracy of a multistep rotary shaft is very important in manufacturing and the assembly process of the high-speed motorized spindle of CNC machine tools, which is closely related to the machined dimensional variation induced by the turning process. This paper attempts to enhance a comprehensive understanding of the impact of different locating-error sources and machine toolpaths on the machined dimensional variation for multistep rotary parts of the high-speed motorized spindle in the turning process. A modeling method and a compensation strategy of dimensional variation are introduced in this paper and based on the relationship definition between the error sources and the machined surface using the differential motion vector and stream-of-variation methods. Validation experiments were conducted to verify the proposed model. Additionally, the relationship between locating errors and dimensional variation was investigated with varied case studies, providing a theoretical methodology for the prediction and characterization of the expected dimensional variations of the surface machined with the given conditions. Full article