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SKF Group is one of the largest bearing manufacturers in the world, well known for its innovations and high quality bearings. One of its innovations is the CARB bearing, which functions particularly well under severe working conditions where traditional bearings break down easily. Compared to traditional bearings, CARB saves costs and creates value because it requires less maintenance, has a longer life, and simplifies machine structure. SKF launched CARB in 1995 and acquired a patent for a period of ten years. CARB bearings, which are manufactured in Sweden, have been widely used in Western markets and become almost standard parts. SKF started to export the new bearings to China in 1997. CARB bearing markets, in China, could be classified into two parts, the new installation (OEM) market and maintenance market, which mainly consisted of the replacement of the CARB bearing for the Chinese‐made conventional bearings on numerous machines. The SKF Shanghai Office was in charge of devising a marketing strategy to sell the CARB bearings to the maintenance markets, the majority of which were large‐scale state‐run companies. But the China market is huge, culture and influences from the West vary across regions, styles of doing business are also different. The first task of the SKF Shanghai Office was to segment the maintenance market and select the segment which was least difficult to enter.

The purpose of this paper is to examine the effect of application of a heat pipe in an aspect of hydrostatic thrust bearings on thermal balance and deformation and the role of this application in increasing the rotating speed of a workbench.

Numerical simulations of oil film temperature field, the temperature field and thermal deformation of the bearing’s workbench and base were performed by finite element analysis (FEA) software for both the traditional hydrostatic thrust bearings and the heat pipe ones.

Oil pad and workbench of the hydrostatic thrust bearings are fabricated with a heat pipe cooling structure, which can take away most of the heat generated by shearing of the oil film, control the temperature rise and thermal deformation of the hydrostatic thrust bearing effectively, avoid the dry friction phenomenon and finally improve the processing quality of equipment.

The heat pipe hydrostatic thrust bearings could control the temperature rise and thermal deformation of the hydrostatic thrust bearing effectively, avoid the dry friction phenomenon and improve the processing quality of equipment.

The purpose is using generative adversarial network (GAN) to solve the problem of sample augmentation in the case of imbalanced bearing fault data sets and improving residual network is used to improve the diagnostic accuracy of the bearing fault intelligent diagnosis model in the environment of high signal noise.

A bearing vibration data generation model based on conditional GAN (CGAN) framework is proposed. The method generates data based on the adversarial mechanism of GANs and uses a small number of real samples to generate data, thereby effectively expanding imbalanced data sets. Combined with the data augmentation method based on CGAN, a fault diagnosis model of rolling bearing under the condition of data imbalance based on CGAN and improved residual network with attention mechanism is proposed.

The method proposed in this paper is verified by the western reserve data set and the truck bearing test bench data set, proving that the CGAN-based data generation method can form a high-quality augmented data set, while the CGAN-based and improved residual with attention mechanism. The diagnostic model of the network has better diagnostic accuracy under low signal-to-noise ratio samples.

A bearing vibration data generation model based on CGAN framework is proposed. The method generates data based on the adversarial mechanism of GAN and uses a small number of real samples to generate data, thereby effectively expanding imbalanced data sets. Combined with the data augmentation method based on CGAN, a fault diagnosis model of rolling bearing under the condition of data imbalance based on CGAN and improved residual network with attention mechanism is proposed.

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

This study aims to investigate the effects of graphite-MoS₂ composite solid lubricant on the tribological properties of copper-based bearing materials under dry conditions.

The mixture of Graphite-MoS₂ was inlaid in ZQSn6-6–3 tin bronze and ZQAl9-4 aluminum bronze matrix. These copper-embedded self-lubricating bearing materials were considered in friction pairs with 2Cr13 stainless steel, and their tribological properties were studied by using an MM200 wear test machine.

The results show that the friction coefficients and wear rates of copper-embedded self-lubricating bearing materials are lower than those of the ordinary copper-based bearing materials. The wear performance of the tin bronze inlaid self-lubricating bearing material is better than that of the aluminum bronze inlaid self-lubricating bearing material. The wear mechanism of the tin bronze bearing material is mainly adhesive wear, and that of the aluminum bronze bearing material is mainly grinding wear, oxidation wear and adhesive wear. The copper-embedded self-lubricating bearing materials had no obvious abrasion, whereas the aluminum bronze inlaid self-lubricating bearing material exhibited deep furrows and obvious abrasion under high loads.

These results are helpful for the application of copper-embedded self-lubricating bearing materials.

This paper aims to describe a theoretical and experimental research concerning influence of recess shape on comprehensive lubrication performance of high speed and heavy load hydrostatic thrust bearing with a constant flow.

The lubrication performance of a hydrostatic thrust bearing with different recess shape under the working conditions of high speed and heavy load has been simulated by using computational fluid dynamics and finite volume method.

It is found that the comprehensive lubrication performance of a hydrostatic thrust bearing with circular recess is optimal. The results demonstrate that recess shape has a great influence on the lubrication performance of the hydrostatic thrust bearing.

The simulation results indicate that to get an improved performance from a hydrostatic thrust bearing with constant flow, a proper selection of the recess shape is essential.

The purpose of this study with the rapid development of the heavy/large mechanical equipment, the heavy computer numerical control (CNC) vertical lathe has become the ideal processing equipment for the parts of those mechanical equipments. The main factor which affects the machining quality and efficiency of heavy CNC vertical lathe is the mechanical properties of the hydrostatic thrust bearing.

This paper did the research based on the large size sector oil pad’s lubrication performance of the hydrostatic thrust bearing in the heavy/large equipments, establishing the lubrication performance distribution mathematical model of the velocity field, flow field, pressure field and so on, analyzing the bearing behavior of the large size sector oil pad.

The results show that the oil flow generated by the plate relative motion will be greater than that generated by the pressure difference in area B, with the rotational speed’s increasing of the hydrostatic thrust bearing, and the direction is opposite. The oil flow generated by the centrifugal force will be greater than that generated by the pressure difference in area C, with the rotational speed’s increasing of the hydrostatic thrust bearing, and the direction is opposite. When the rotational speed of the hydrostatic thrust bearing is too high, the friction heat will be not easy to be sent out. The bearing rotating speed should be lower than the comparatively smaller one of ω1 and ω2, which can help avoid the rise of too high temperature.

The research provides powerful theoretical foundation for practical application of the large size sector oil pad hydrostatic thrust bearing, its structure design and operating reliability, realizing the lubrication performance prediction of the large size hydrostatic thrust bearing.

The optimal control on reassembly (remanufacturing assembly) error is one of the key technologies to guarantee the assembly precision of remanufactured product. However, because of the uncertainty existing in remanufactured parts, it is difficult to control assembly error during reassembly process. Based on the state space model, this paper aims to propose the optimal control method on reassembly precision to solve this problem.

Initially, to ensure the assembly precision of a remanufactured car engine, this paper puts forward an optimal control method on assembly precision for a remanufactured car engine based on the state space model. This method takes assembly workstation operation and remanufactured part attribute as the input vector reassembly status as the state vector and assembly precision as the output vector. Then, the compensation function of reassembly workstation operation input vector is calculated to direct the optimization of the reassembly process. Finally, a case study of a certain remanufactured car engine crankshaft is constructed to verify the feasibility and effectiveness of the method proposed.

The optimal control method on reassembly precision is an effective technology in improving the quality of the remanufactured crankshaft. The average qualified rate of the remanufactured crankshaft increased from 83.05 to 90.97 per cent as shown in the case study.

The optimal control method on the reassembly precision based on the state space model is available to control the assembly precision, thus enhancing the core competitiveness of the remanufacturing enterprises.

The purpose of this paper is to study the tribological effect of zinc borate ultrafine powder (ZBUP) oil additive on the running-in quality.

The running-in quality was assessed by friction coefficient and surface topography. Fractal parameters including fractal dimension, the width of multifractal, the multifractal difference, multifractal parameters, phase trajectory and correlation dimension were used to extract the nonlinear characteristics of surface topography and friction coefficient.

When the ZBUP additive was added, the convergence degree of the phase trajectory and the stability of the running in were higher than that of base oil. It indicates that the ZBUP additive can improve the running-in quality of sliding bearing. Besides, the ZBUP additive can shorten the running-in time. A boundary protective film, which has good friction-reducing and anti-wear effects, was generated on the surface when the ZBUP additive was added.

The results have a great significance to improve the running-in quality and prolong the service life of the sliding bearing.