Double-row tapered roller bearings have been widely used in various equipment recently due to their compact structure and ability to withstand large loads. The dynamic stiffness is composed of contact stiffness, oil film stiffness and support stiffness, and the contact stiffness has the most significant influence on the dynamic performance of the bearing. There are few studies on the contact stiffness of double-row tapered roller bearings. Firstly, the contact mechanics calculation model of double-row tapered roller bearing under composite loads has been established. On this basis, the influence of load distribution of double-row tapered roller bearing is analyzed, and the calculation model of contact stiffness of double-row tapered roller bearing is obtained according to the relationship between overall stiffness and local stiffness of bearing. Based on the established stiffness model, the influence of different working conditions on the contact stiffness of the bearing is simulated and analyzed, and the effects of radial load, axial load, bending moment load, speed, preload, and deflection angle on the contact stiffness of double row tapered roller bearings have been revealed. Finally, by comparing the results with Adams simulation results, the error is within 8%, which verifies the validity and accuracy of the proposed model and method. The research content of this paper provides theoretical support for the design of double-row tapered roller bearings and the identification of bearing performance parameters under complex loads.
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http://dx.doi.org/10.3390/s23104967 | DOI Listing |
Data Brief
December 2024
Department of Mechanical and Information Engineering/Smart Cities, University of Seoul, Seoul 02504, Korea.
In modern complex mechanical systems, machine faults typically occur in multiple components simultaneously, and the domain of collected sensor data changes continuously due to variations in operating conditions. Deep learning-based fault diagnosis approaches have recently been enhanced to address these real-world industrial challenges. Comprehensive labeled data covering compound fault scenarios and multi-domain conditions are crucial for exploring these issues.
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December 2024
Beijing Key Laboratory of Micro-nano Energy and Sensor, Center for High-Entropy Energy and Systems, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, P. R. China.
Tribovoltaic nanogenerator (TVNG) is an emerging energy device with the advantages of direct current and high power density. At present, many TVNGs are based on single-crystal materials, which are expensive and fragile during structural processing. Here, a polysilicon-based TVNG for bearing in situ rotational speed sensing is developed, which has the same level of performance and lower cost compared to monocrystalline silicon.
View Article and Find Full Text PDFSci Rep
May 2024
Luoyang Institute of Science and Technology, Luoyang, 471023, China.
Materials (Basel)
December 2023
State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing 100083, China.
A hot-working die steel thick-walled tube Pilger rolling test was carried out using an LG40 Pilger mill, and the morphology and roughness evolution of the inner surface were examined using a white-light interferometer. The experimental results showed that micro-wrinkles formed on the basis of the original inner surface morphology, the altitude difference () between the peaks and valleys of the inner surface profile increased from 3.18 to 3.
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