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High-speed running bearings generate a large amount of heat, which has a significant impact on the accuracy of machine tool feeding system. In this paper, by applying the bearing proposed statics and local heat source method, considering the combined surface contact thermal resistance and lubricant viscous temperature characteristics of the influence of the thermal network method to determine the main thermal characteristics of the shaft system parameters, the establishment of the transient thermal equilibrium equations, in the iterative process of the shaft system temperature field and deformation of the coupling; through the solution, the bearing temperature field and the transient change of the thermal parameters of the characteristics of the bearing, analyze the working conditions and structural parameters of the bearing transient thermal characteristics curve; using the finite element method coupled field simulation and test bed test, to verify the theoretical model is reasonable. The influence of working conditions and structural parameters on the transient thermal characteristic curve of the bearing is analyzed. The reasonableness of the theoretical model is verified by using the finite element method coupled field simulation and test bench test. After in-depth analysis: no matter the initial clearance or the change of rotational speed and load, it will lead to the change of thermal equilibrium temperature of the bearings, and will produce heat-induced load. Therefore, by choosing the appropriate clearance, improving the viscosity of lubricant, and enhancing the air convection, the heat generation and thermal deformation can be effectively reduced, which provides an important method to support the optimization of the bearing structure and the design of thermal balance.

Abstract In this paper, on one hand, the time-varying characteristics of the heat source and thermal boundary conditions of the high-speed spindle system were analyzed considering the thermal-structural coupling effect. And a transient bearing temperature field prediction method combining the thermal network method and finite element method was proposed. Furthermore, the relationships between time step, calculation efficiency and calculation results were analyzed. On the other hand, a online real-time monitoring system of the transient temperature of the cylindrical roller bearing inner ring for maximum speed of 13,000 r/min was designed and implemented using fibre optic sensing technology. Comparing with the conventional static thermal analysis results, it is verified that the simulation method proposed in this paper has higher accuracy. This paper provides a new approach for analysing and testing the thermal characteristics of high-speed spindle system.

Plate heat exchangers are widely used in the Heating, Ventilation, and Air Conditioning (HVAC) field. Cross-corrugated triangular ducts are commonly employed in plate heat exchangers. Inserting baffles into the cross-corrugated triangular ducts can improve the heat transfer performance of the plate heat exchangers. This study focuses on intricate interdependencies among the flow channel apex angle, the trapezoidal baffle inclination angle, baffle position, and Reynolds number (Re) on heat transfer and pressure drop using response surface methodology (RSM) and computational fluid dynamic (CFD). To identify the factors that maximize the Nusselt number (Nu) and minimize friction factor (f), the RSM is used to design factors, conduct numerical studies, and establish regression equations. The results show that the apex angle, baffle angle, X-direction position, and Re have significantly affected Nu and f. Compared to a non-baffled channel with the same apex angle and Re conditions, the optimized channel enhances heat transfer by 1.54 times and has an almost identical pressure drop. The inclined baffle significantly enhances comprehensive performance at low Re. The synergistic effect of the heat transfer and pressure drop is most optimal when the apex angle of the flow channel is 90°, the trapezoidal baffle inclination angle is 52.5°, and the Re is 1000, with the baffle position at 0.625H in the X-direction.

The NJ2205 cylindrical roller bearing is taken as the analysis object， and roller modeling is carried out through ANSYS software to analyze the "edge effect" problem between roller and raceway under the conditions of flooded oil and stared oil， and the shear stress distribution of roller and raceway is compared and analyzed under the conditions of unmodified， full convex modification and logarithmic modification. The results show that under the condition of radial load is 11.45 kN and speed is 4 000 r/min， the shear stress in the direction of the roller generatrix under flooded oil condition is less than that of stared oil condition， the shear stress in the non-repair mode is the largest， and the logarithmic repair mode. The shear stress is the smallest， and the fully convex repair under oil-rich and spent oil reduces by 17.02% and 10.58% respectively compared to the unrepaired shape， and the logarithmic repair reduces by 32.95% and 17% respectively compared to the unrepaired shape. Therefore， the roller of NJ2205 cylindrical roller bearing adopts log modification curve can effectively reduce the shear stress.

The electrocardiogram (ECG) is a highly effective non-invasive tool for monitoring heart activity and diagnosing cardiovascular diseases (CVDs). Automatic detection of arrhythmia based on ECG plays a critical role in the early prevention and diagnosis of CVDs. In recent years, numerous studies have focused on using deep learning methods to address arrhythmia classification problems. However, the transformer-based neural network in current research still has a limited performance in detecting arrhythmias for the multi-lead ECG. In this study, we propose an end-to-end multi-label arrhythmia classification model for the 12-lead ECG with varied-length recordings. Our model, called CNN-DVIT, is based on a combination of convolutional neural networks (CNNs) with depthwise separable convolution, and a vision transformer structure with deformable attention. Specifically, we introduce the spatial pyramid pooling layer to accept varied-length ECG signals. Experimental results show that our model achieved an F1 score of 82.9% in CPSC-2018. Notably, our CNN-DVIT outperforms the latest transformer-based ECG classification algorithms. Furthermore, ablation experiments reveal that the deformable multi-head attention and depthwise separable convolution are both efficient in extracting features from multi-lead ECG signals for diagnosis. The CNN-DVIT achieved good performance for the automatic arrhythmia detection of ECG signals. This indicates that our research can assist doctors in clinical ECG analysis, providing important support for the diagnosis of arrhythmia and contributing to the development of computer-aided diagnosis technology.

Hollow fiber membrane dehumidification is an effective and economical method of air dehumidification. The hollow fiber membrane module is the critical component of the dehumidification system, which is formed by an arrangement of several hollow fiber membranes. The air stream crosses over the fiber bundles when air dehumidification is performed. The fibers vibrate with the airflow. To investigate the characteristics of the fluid-induced vibration of the hollow fiber membrane, the two-way fluid-structure interaction model under the air-induced condition was established and verified by experiments. The effect of length and air velocity on the vibration and modal of a single hollow fiber membrane was studied, as well as the flow characteristics using the numerical simulation method. The results indicated that the hollow fiber membrane was mainly vibrated by fluid impact in the direction of the airflow. When the air velocity was 1.5 m/s~6 m/s and the membrane length was 100~400 mm, the natural frequency of the membrane was negatively correlated with length and positively correlated with air velocity. Natural frequencies were more sensitive to changes in length than changes in air velocity. The maximum equivalent stress and total deformation increased with air velocity and length. The maximum equivalent stress was concentrated at both ends, and the maximum deformation occurred in the middle. The research results provided a basis for the structural design of hollow fiber membranes under flow-induced vibration conditions.

As the most important segment of the spindle unit angular contact ball bearing, the preload significantly influences the bearing characteristics. Thus, the thermal-induced preload derived from the thermal expansion of spindle unit components also affects the increase in bearing temperature, stiffness, fatigue life, and ball skidding significantly. However, such preload is hard to monitor and analyze. Thus, in this article, the authors presented a fiber Bragg gating sensor-based structure for the identification of thermal-induced bearing preload. In addition, a bearing total preload control mechanism was designed with an emphasis on its thermal component. Based on the comparison of the shaft and the outer ring deformation temperature increases measured by embedded fiber Bragg gating sensors, the reasonable bearing preload range was achieved based on Hirano’s theory. Finally, the conclusions provide a reference for improving the performance of angular contact ball bearings and reducing the spindle vibration.

The contact characteristics of angular contact ball bearings are closely related to the thermal failure of high-speed spindle systems. This paper establishes a closed-loop iterative model for analyzing the ball–race contact characteristics of machine tool spindle bearings at different combined loads and oil supply temperatures, based on a five-degree-of-freedom quasi-static analysis model and the finite difference method. Additionally, the accuracy of the proposed model is verified by comparing the measured values of temperature rise with the predicted values. Based on the verification of the accuracy of the model, the contact characteristics of machine tool spindle bearings under strong asymmetric loads and high-temperature lubrication oil are discussed in detail. The results show that at elevated temperatures, the internal loads of angular contact ball bearings operating under combined loads become concentrated, which will lead to reduced fatigue life of the bearings and even thermal seizure.

This paper explores the cage whirl state under different operating conditions based on the cylindrical roller bearing dynamics model. The stability and whirl characteristics of the cage whirl are evaluated by considering the rotation and force of the cage and roller. The results demonstrate that the cage whirl state is divided into three types according to the cage whirl orbit: disordered whirl, local periodic whirl and regular circular whirl. With disordered whirl, the whirl speed and whirl radius of the cage are unpredictable, and the force of the cage changes frequently. With local periodic whirl, the rotation speed, whirl speed and the force on the cage change periodically or stay constant. In the case of a regular circular whirl, the force on the cage should be considered to evaluate the stability of the cage whirl. In addition, the collision force between the roller and cage determines whether the cage whirl speed is stable or not, and the bearing slipping has no obvious effect on cage whirl stability.

This paper investigates a method to dynamically model compound faults on the inner and outer rings of an angular contact ball bearing as well as their effects on its dynamic behavior. Gupta’s dynamic modeling method is used to consider changes in the deformation and direction of the contact load when the ball passes through the damaged area and to develop a dynamic model of compound faults in the angular contact ball bearing. The step-changing fourth-order Runge–Kutta method is used to solve the dynamic compound fault model. The time-domain signal of vibration responses in the case of a single fault in the inner and outer rings exhibited a certain periodicity, and the frequency of faults in the envelope spectrum was clear. By comparison, the periodicity of compound faults was not clear. The signals of compound faults were decomposed by the dual-tree complex wavelet transform to identify their characteristic frequency. Errors occurred between the characteristic frequency of the theoretical fault and its simulated value. They increased with the rotational speed and decreased with an increase in axial load, whereas the influence of radial load on them was minor. For compound faults on the inner and outer rings of an angular contact ball bearing, this study provides a modeling method that can describe changes in the deformation and direction of the contact load when the ball passes through the damaged area of the inner and outer rings. The work here can provide an important foundation for fault identification in angular contact ball bearings.

As a key component of the machine tool spindle, bearing has critical influences on the spindle thermal error. In particular, the installation errors of bearing have considerable effects upon the spindle thermal error by altering the bearings’ internal contact angles, contact loads, and friction torques for different ball positions, but have yet to be fully elucidated. In this article, the influence of installation errors on the resulting spindle thermal error was evaluated using both empirical methods and simulation method, with the ultimate aim of reducing installation error. Deviations within the bearing support were used to simulate bearing parallel misalignment; bearing parallel misalignment running model was built, and an analysis and comparison of various conditions were used to determine the influence, showing that the parallel misalignment has significant influence on the spindle Z direction thermal error.

The bearing preload plays an important role on the bearing performance, particularly the important characteristics of the bearing include bearing temperature increases, the bearing fatigue life, and ball skidding. Generally, the bearing preload contains the initial bearing preload and the thermal-induced bearing preload. Moreover, the bearing performance is closely related to machine tool accuracy. Obtaining an optimal bearing preload can improve the spindle work accuracy of machine tools. A method for determining optimal bearing preload over a wide range of speeds is given in this article. The method is based on the aforementioned factors that affect bearing performance, synthetically considering the initial preload and thermal-induced bearing preload, and it is verified both experimentally and with simulations. The results show that there is a minimum bearing preload value for avoiding the bearing ball skidding; the bearing temperature rise more than 30°C can be hardly achieved in the normal speed range, the fatigue life decides the biggest bearing preload; and the method is applicable to machine tool spindle usage.

As the core component of machine tool, the thermal characteristics of the spindle have a significant influence on machine tool running status. Lack of an accurate model of the spindle system, particularly the model of load–deformation coefficient between the bearing rolling elements and rings, severely limits the thermal error analytic precision of the spindle. In this article, bearing internal loads, especially the function relationships between the principal curvature difference F ( ρ ) and auxiliary parameter n δ , semi-major axis a , and semi-minor axis b , have been determined; furthermore, high-precision heat generation combining the heat sinks in the spindle system is calculated; finally, an accurate thermal model of the spindle was established. Moreover, a conventional spindle with embedded fiber Bragg grating temperature sensors has been developed. By comparing the experiment results with simulation, it indicates that the model has good accuracy, which verifies the reliability of the modeling process.

Rhododendron spp. is an important ornamental species that is widely cultivated for landscape worldwide. Heat stress is a major obstacle for its cultivation in south China. Previous studies on rhododendron principally focused on its physiological and biochemical processes, which are involved in a series of stress tolerance. However, molecular or genetic properties of rhododendron's response to heat stress are still poorly understood. The phenotype and chlorophyll fluorescence kinetics parameters of four rhododendron cultivars were compared under normal or heat stress conditions, and a cultivar with highest heat tolerance, "Yanzhimi" (R. obtusum) was selected for transcriptome sequencing. A total of 325,429,240 high quality reads were obtained and assembled into 395,561 transcripts and 92,463 unigenes. Functional annotation showed that 38,724 unigenes had sequence similarity to known genes in at least one of the proteins or nucleotide databases used in this study. These 38,724 unigenes were categorized into 51 functional groups based on Gene Ontology classification and were blasted to 24 known cluster of orthologous groups. A total of 973 identified unigenes belonged to 57 transcription factor families, including the stress-related HSF, DREB, ZNF, and NAC genes. Photosynthesis was significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway, and the changed expression pattern was illustrated. The key pathways and signaling components that contribute to heat tolerance in rhododendron were revealed. These results provide a potentially valuable resource that can be used for heat-tolerance breeding.

Bearing temperature rise amplitude is related to the running state of bearing and spindle thermal error, so the measurement of bearing temperature field is helpful to ascertain the bearing running characteristic and analysis of the spindle thermal error. On the basis of thoroughly understood several reasons of bearing heat generation, this article analyzes bearing temperature field simulation based on ANSYS and bearing temperature field measurement based on fiber Bragg grating sensors. The results showed that using fiber Bragg grating is able to complete the bearing temperature field distribution measurement perfectly.

Seismogenic fault geometry, especially for a blind fault, is usually difficult to derive, based only on the distribution of aftershocks and interference fringes of Interferometric Synthetic Aperture Radar (InSAR). To better constrain the fault geometry of the 2017 Jiuzhaigou Mw 6.5 earthquake, we first carried out a nonlinear inversion for a single fault source using multi-peak particle swarm optimization (MPSO), Monte Carlo (MC), and Markov Chain Monte Carlo (MCMC) algorithms, respectively, with constraints of InSAR data in multiple SAR viewing geometries. The fault geometry models retrieved with different methods were highly consistent and mutually verifiable, showing that a blind faulting with a strike of ~154° and a dip angle of ~77° was responsible for the Jiuzhaigou earthquake. Based on the optimal fault geometry model, the fault slip distribution jointly inverted from the InSAR and Global Positioning System (GPS) data by the steepest descent method (SDM) and the MC method showed that the slip was mainly concentrated at the depth of 1–15 km, and only one slip center appeared at the depth of 5–9 km with a maximum slip of about 1.06 m, some different from previous studies. Taking the shear modulus of μ = 32 GPa, the seismic moment derived from the distributed slip model was about 7.85 × 1018 Nm, equivalent to Mw 6.54, which was slightly larger than that from the focal mechanism solutions. The fault spatial geometry and slip distribution could be further validated with the spatial patterns of the immediate aftershocks. Most of the off-fault aftershocks with the magnitude > M2 within one year after the mainshock occurred in the stress positive stress change area, which coincided with the stress triggering theory. The static Coulomb stress, triggered by the mainshock, significantly increased at the Tazang fault (northwest to the epicenter), and at the hidden North Huya fault, and partial segments of the Minjiang fault (west of the epicenter).

Afterslip could help to reveal seismogenic fault structure. The 2020 Mw 6.3 Nima earthquake happened in a pull-apart basin within the Qiangtang block, central Tibetan plateau. Previous studies have explained the coseismic and early (<6 mo) postseismic deformation by rupture and afterslip on a normal fault bounding the western side of the basin. Here, we resolved the 19-month Interferometric Synthetic Aperture Radar-measured sequences of postseismic displacements that revealed a second postseismic displacement center ~12 km to the east of the main fault. Fitting the postseismic displacement requires afterslip on both the main fault and an antithetic fault that probably forms a y-shaped pair of conjugate faults in a negative flower structure. Stress-driven afterslip models suggest that the required afterslip on the antithetic fault could be triggered by coseismic rupture of the main fault or by a simultaneous rupture on the antithetic fault. The afterslip on both faults occurred mainly up-dip to the coseismic slip and has released moment ~15%-19% of that by the coseismic rupture. These results provide insights into active extension in the central Tibetan plateau and highlight the complex nature of fault rupture and afterslip. [ABSTRACT FROM AUTHOR]