In order to investigate the turbulent lubrication performance of a textured hydrodynamic journal bearing (THJB), a model of turbulent lubrication was established in this paper. The variations in the Reynolds number, oil film thickness, oil film pressure, bearing capacity, attitude angle, and side leakage flow with structural and working parameters were studied, and the axis whirl orbit was further analyzed. The results show that turbulent lubrication is suitable for the actual operating conditions of THJBs. The Reynolds number decreases with the eccentricity ratio in the pressure-bearing zone but increases with rotational speeds, whereas the variation in the maximum oil film pressure increases and the minimum oil film thickness decreases with the eccentricity ratio under various Reynolds numbers. The bearing capacity decreases with the dimple diameter, depth, oil film thickness, and clearance ratio but increases with the length/diameter ratio and dimple spacing. As the eccentricity ratio increases, the attitude angle decreases, but the side leakage flow increases. In addition, the system tends to be unstable as the rotational speed and length/diameter ratio increase, and the friction and wear on the surface are three-body friction. This work not only helps in analyzing the characteristics of a THJB under actual operating conditions but also provides support for research on the simulation of THJB’s lubrication mechanism of THJB via computational fluid dynamics.

Future field work tasks will require mountain tractors to pass through rough terrain with limited human supervision. The wheel–soil interaction plays a critical role in rugged terrain mobility. In this paper, an algorithm for the estimation of soil characteristic parameters based on the Simpson numerical integration method and Gauss–Newton iteration method is presented. These parameters can be used for passability prediction or in a traction control algorithm to improve tractor mobility and to plan safe operation paths for autonomous navigation systems. To verify the effectiveness of the solving algorithm, different initial values and soils were selected for simulation calculations of soil characteristic parameters such as internal friction angle, settlement index, and the joint parameter of soil cohesion modulus and friction modulus. The results show that the error was kept within 2%, and the calculation time did not exceed 0.84 s, demonstrating high robustness and real-time performance. To test the applicability of the algorithm model, further research was conducted using different wheel parameters of electric mountain tractors under wet clay conditions. The results show that these parameters also have high accuracy and stability with only a few iterations. Thus, the estimation algorithm can meet the requirements of quickly and accurately identifying soil characteristic parameters during tractor operation. A criterion for the passability of wheeled tractors through unknown terrain is proposed, utilizing identified soil parameters.

Pitch bearings are the key components of wind turbines (WTs). The reliability of pitch bearings affects the electric energy output efficiency of WTs. Due to its large loading ability, constant contact angle and high stiffness, the three-row roller slewing bearing (TRSB) is becoming a more attractive choice as a pitch bearing, especially in large-scale WTs. The contact force and pressure distributions significantly affect the fatigue life of a three-row roller pitch bearing (TRPB). Therefore, it is essential to propose a precise calculation method for the contact force and pressure. The present work establishes a quasi-static five degree-of-freedom (DOF) mathematical model for TRPBs, in which the bearing under general loading conditions is considered. The influences of combined external forces, overturning moments and inner ring misalignment angle on the contact force and pressure distributions of TRPBs are comprehensively investigated. According to the analysis results, the overturning moment and axial force can significantly affect the number of load-carrying rollers in each row. Furthermore, a slight variation of the inner ring angular misalignment has a significant effect on the contact force and pressure of TRPBs. Finally, it is more prone to pressure concentration in the non-crowned roller than that in the crowned roller, especially in the case of the inner ring with a misalignment angle. Since the high calculation efficiency and accuracy, the proposed method has remarkable potential applications in the fatigue life prediction and design of TRPBs.

Bearing fault detection is important for the reliable and safe operation of rotating machinery. The operating speed of the bearing is usually variable, which makes fault detection more challenging. Existing works have not explored a structural framework that links angle resampling with Markov models, leaving room for improvement in fault detection under variable speed conditions. This article proposes a Markov probability model-based fault detection method for bearing operating under variable speed conditions. First, angle resampling is used to resample the data obtained under different rotational speeds to demodulate frequency modulation. Then, the resampled vibration signal is modeled using the explicit-duration hidden Markov model (EDHMM). Finally, the fault is detected through the likelihood ratio test. The fault detection results are visualized through the receiver operating characteristic (ROC) curve, its quantification metric area under the ROC curve (AUC) value, and the corresponding sequence plot. The performance is compared with the angle resampling-free Markov model likelihood ratio detection method. The results indicate that the AUC of the proposed method is 0.9110, much higher than that of the angle resampling-free Markov model, 0.6439.

Double-row tapered roller bearings (DTRBs) offer significant advantages, including high load-carrying capacity, long service life, and the ability to withstand combined radial and axial loads as well as bending moments. DTRBs are widely used in mechanical equipment and machinery, such as precision machine tools, automobiles, rail transit, and wind turbines. While previous studies have primarily focused on the static analysis of DTRBs, few have investigated their vibration mechanisms. To explore the dynamic characteristics of DTRBs, a comprehensive dynamic model was developed, incorporating local defects. This model reveals the vibration behavior of DTRBs with local defects and analyzes the impact of bearing defects on vibration characteristics. The findings provide a theoretical foundation for DTRB defect diagnosis and serve as a basis for future studies on the dynamics of various roller bearings.