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Objectives The rapid growth of machine learning methods has led to an increase in the demand for data. For bearing fault diagnosis, the data acquisition is time-consuming with complicated processes. Existing datasets are only focused on only one type of bearing, which limits real-world applications. Therefore, the objective of this work is to propose a diverse dataset for ball bearing fault diagnosis based on vibration. Data description In this work, we introduce a practical dataset named HUST bearing , which provides a large set of vibration data on different ball bearings. This dataset contains 99 raw vibration signals of 6 types of defects (inner crack, outer crack, ball crack, and their 2-combinations) on 5 types of bearing (6204, 6205, 6206, 6207, and 6208) at 3 working conditions (0 W, 200 W, and 400 W). Each vibration signal is sampled at a rate of 51,200 samples per second for 10 s. The data acquisition system is elaborately designed with high reliability.

The rotor misalignment fault, which occurs only second to imbalance, easily occurs in the practical rotating machinery system. Rotor misalignment can be further divided into coupling misalignment and bearing misalignment. However, most of the existing references only analyze the effect of coupling misalignment on the dynamic characteristics of the rotor system and ignore the change of bearing excitation caused by misalignment. Based on the above limitations, a five degrees of freedom nonlinear restoring force mathematical model is proposed, considering misalignment of bearing rings and clearance of cage pockets. The finite element model of the rotor is established based on the Timoshenko beam element theory. The coupling misalignment excitation force and rotor imbalance force are introduced. Finally, the dynamic model of the ball bearing-coupling-rotor system is established. The radial and axial vibration responses of the system under misalignment fault are analyzed by simulation. The results show that the bearing misalignment significantly influences the dynamic characteristics of the system in the low-speed range, so bearing misalignment should not be ignored in modeling. With the increase of rotating speed, rotor imbalance and coupling misalignment have a greater impact. Misalignment causes periodic changes in bearing contact angle, radial clearance, and ball rotational speed. It also leads to reciprocating impact and collision between the ball and cage. In addition, misalignment increases the critical speed and the axial vibration of the system. The results can provide a basis for health monitoring and misalignment fault diagnosis of the rolling bearing-rotor system.

Ball bearing monitoring employs time-frequency techniques to facilitate the early detection of faults; however, the presence of non-stationary or noisy signals can limit the effectiveness of these techniques, requiring advanced methods for reliable predictive maintenance. This study proposes a methodology for fault detection in complex systems,utilising Principal Component Analysis (PCA) to identify indicators with a higher probability of fault. Subsequent to this, the signal characteristics are decomposed using the Fast Fourier Transform (FFT). This technique is employed to identify the Hotelling component and the SPE (quadratic prediction error), with the objective of determining the state of health of the rolling bearings. This is achieved by extracting the frequencies and harmonics that characterise the fault. The Hotelling component considers elements in the main space with a higher energy representation for evaluation, while the SPE considers elements in the residual space. The results demonstrate a rapidly appreciable range of detection and dispersion of faulty signals. A comparative analysis of the KPCA-FFT and PCA-FFT results is performed. However, this study demonstrates that the combination of PCA-FFT with the Hotelling index test and SPE is more suitable for evaluating signals with defects.

A silicon nitride ceramic bearing has good self-lubricating characteristics. It still has a good operational status under the condition of a lack of oil. However, the temperature distribution of a silicon nitride ceramic bearing during its operation is unclear. To clarify the thermal distribution of a full-ceramic ball silicon nitride ceramic bearing under self-lubricating conditions, the changing trend of the rolling friction temperature between the rolling elements and channels with different accuracies is analyzed using the friction testing machine. The bearing heat generation model based on the silicon nitride material coefficient is established, and the life test machine measures the temperature of the bearing to verify the accuracy of the simulation model. The results show that the friction temperature between the ceramic ball and channel decreases with the increase in ceramic ball level. With an increase in the ceramic ball pressure and temperature, the friction temperature rises. Under self-lubrication, when the bearing bears a heavy load, the influence of the rotating speed on temperature rise tends to decrease. Under the condition of high speed, with the increase in load, the change range of temperature rise shows an upward trend. The important relationship between the bearing’s heat and bearing’s load and speed is revealed. It provides some theoretical guidance for the thermal analysis of a silicon nitride ceramic ball bearing under the self-lubricating condition to improve the service life and reliability of full-ceramic ball bearings.

As the operating conditions of rolling bearings become increasingly demanding, traditional steel bearings can no longer fully meet the performance requirements of critical equipment. Silicon nitride full ceramic ball bearings, with intrinsic properties such as a low thermal expansion coefficient, low density, corrosion resistance, and wear resistance, offer significant advantages in extreme temperatures, high-speed operation, and harsh corrosive environments. As a result, they have become a key technical solution for the core transmission systems of high-end equipment. However, the dynamic evolution of their service performance under varying operating conditions—such as load and speed—remains insufficiently understood. This study systematically investigates the service performance evolution mechanism of silicon nitride full ceramic ball bearings under self-lubrication conditions. The key findings will provide a theoretical foundation for optimizing and regulating performance under extreme operating conditions.

This paper focuses on the primary resonance analysis of a dual-rotor system having two rotor unbalance excitations of different rotating speeds and being connected by an inter-shaft ball bearing. Due to the complex excitation condition and the complicated nonlinear bearing forces of the inter-shaft bearing, the general analytical methods, e.g., the multiple scales method or the harmonic balance method, are failed to give the theoretical solutions. Thus, the harmonic balance–alternating frequency/time domain (HB–AFT) method is formulated to deal with this problem. The basic idea of the method is using the inverse discrete Fourier transform and the discrete Fourier transform, instead of the direct analytical relationship between the supposed solutions of the system and the nonlinear forces, to construct the harmonic expressions of the nonlinear forces, which is the so-called alternating frequency/time domain technique. By using the HB–AFT method, therefore, a Newton– Raphson iteration procedure can be performed to demonstrate the approximate solutions of the system. Accordingly, the frequency responses of the system affected by some critical parameters, such as rotating speed ratio, unbalances of both the inner and outer rotors, and clearance of the inter-shaft bearing, are analyzed, respectively. A variety of phenomena including double resonance peaks, biperiodic and quasi-periodic behaviors, and resonance hysteresis phenomenon are obtained, which are discussed in detail through diagrams for separated frequency responses with different frequency components and rotors’ orbits for different combinations of system parameters. Most prominently, for a relatively small unbalance of rotor as well as a relatively large clearance of the inter-shaft bearing, the resonance hysteresis phenomena are more obvious. The results obtained are also compared with the direct numerical simulation results, and the comparisons show good agreements. In addition, the methodology formulated in this paper is a general approach, which can be applied to other engineering systems with multi-frequency excitations.

As the fundamental supporting structure in rotating machinery, the dynamic behaviors of angular contact ball bearings directly affect the operational performances of high-speed machine tools and aero-engine. In this work, a novel dynamic model considers flexible ring and cage motion whirl so that the deformations of flexible rings can change the contacts between balls and raceways to influence the dynamic behaviors of ball bearings, which is a novel solution for the dynamic performance analysis of angular contact ball bearings under different loads, assemblies and bearing structures. Then, the experimental validation conducted by a high-precision instrument demonstrated the reliability of this original model. On this basis, the effects of the clearances between housing and outer ring, the thickness of flexible ring and radial loads on the sliding of the ball, interaction forces between bearing components, vibration of inner ring, and cage whirl motion were investigated. The results show that the thick flexible ring and the minimal clearance can improve the dynamic stability of cage and mitigate the bearing vibration.

This paper presents the problem of rolling bearing fault diagnosis based on vibration velocity signal. For this purpose, recurrence plots and quantification methods are used for nonlinear signals. First, faults in the form of a small scratch are intentionally introduced by the electron-discharge machining method in the outer and inner rings of a bearing and a rolling ball. Then, the rolling bearings are tested on the special laboratory system, and acceleration signals are measured. Detailed time-dependent recurrence methodology shows some interesting results, and several of the recurrence indicators such as determinism, entropy, laminarity, trapping time and averaged diagonal line can be utilized for fault detection.

The thermal effect has a significant influence on the performance of angular contact ball bearings and thus affects the motion accuracy and stability of spindle-bearing system of computerized numerical control (CNC) lathe. In this paper, a comprehensive coupled CNC lathe spindle-bearing model considering the thermal effect is proposed to predict the dynamic characteristics of system. The spindle is modeled as Timoshenko’s beam by considering the centrifugal force and gyroscopic effects. The bearing is analyzed by a five degrees-of-freedom (DOF) quasi-static model considering the thermal effect in order to obtain the static deformations and thermal deformations of rolling bodies. The dynamic differential equation of system is established by the finite element method. Runge–Kutta integral method is used to solve the system equation numerically to study its nonlinear dynamic behaviors. The correctness of thermal model of CNC lathe spindle-bearing system is verified by testing the housing temperature. The simulation values of system response considering thermal effect or not are compared with the experimental results, which shows that the proposed model is feasible. Moreover, the effects of key parameters such as rotational speed, pulley eccentricity and bearing preload on the nonlinear characteristics of system are investigated. Single-periodic, multi-periodic, quasi-periodic and chaotic motions are observed by time history curve, 3-D frequency spectrum curve, phase diagram, Poincare section and bifurcation diagram under different operating conditions. The analytical model developed here can be also helpful to the design and optimization of CNC lathe spindle-bearing system.

To study the variation rules of nonlinear stiffness of double-row angular contact ball bearings (DR-ACBB), this paper proposed a general mathematic model for DR-ACBB under three different configurations based on the improved quasi-static model of ball bearings, an explicit expression stiffness matrix of DR-ACBB is analytically derived, and a double-layer nested iterative algorithm based on the Newton–Raphson method is designed to realize the efficient solution of the proposed model. Then, the effects of the preload, speeds, and loads on the nonlinear stiffness variations of DR-ACBB under different arrangements are comparatively analyzed. The results show that DR-ACBB under the DB and DF configurations have the same variation rule in axial and radial stiffness; that is, a nonlinear soft-spring stiffness characteristic (i.e., the stiffness decreases with the external load) within the low-speed range and light load condition, and a nonlinear hard spring stiffness characteristic (i.e., the stiffness increases with the external load) within the high-speed range or heavy load condition.