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Aiming at the problem that the reliability of the hub drive system under the actual load could not be accurately evaluated at the design stage, a method for evaluating reliability which applied in the design stage was proposed. The dynamic fatigue reliability of each gear pair of the hub drive system was calculated by replacing the actual random load with the static load of the rated design load in the method. The fatigue damage and reliability of each gear pair of the wheel hub drive system under the actual load were simulated through Romax Design software, and the feasibility of the method d was verified, which could provide theoretical basis and practical test guidance for the reliability design of wheel drive system.

Aiming at the problems of cumbersome operation and strong subjectivity of the traditional detection method for the transmission accuracy of spiral bevel gears, an acoustic signal-assisted detection method for judging the transmission accuracy of spiral bevel gears is proposed. Combining the gear rolling inspection machine with the developed acoustic signal acquisition system, a real-time acoustic signal acquisition experiment is designed for detecting the quality of the contact marks on the tooth surface of the spiral bevel gear. Combined with the particle swarm optimization(PSO) algorithm and the maximum correlated kurtosis deconvolution(MCKD) based signal processing methods, the effect of different axial deviations on the gear mesh acoustic signals is investigated. It is found that the increase of the axial deviation leads to the increase of the amplitude corresponding to the mesh frequency and its octave frequency, which seriously affects the transmission accuracy of the gear. Meanwhile, the feasibility of the proposed method is verified by using practical examples, which provides an effective auxiliary mean for the detection of the meshing performance of spiral bevel gears.

The grinding of spiral bevel gears is a nonlinear and dynamic complex process. It is significant to explore the complex grinding mechanism of spiral bevel gears by simulating the grinding process based on finite element method. A finite element model of composite abrasive grinding was established based on material constitutive equation of Johnson-Cook force-thermal coupling. And the changes in the tooth surface temperature field, grinding force and abrasive wear were compared and analyzed under different grinding speeds, grinding depths and abrasive spacing condition. The simulation results were also verified by the experimental results.The results show that the grinding depth is the most important factor to affect the grinding surface performance. The influence of the compound abrasive grain interference on the tooth surface temperature field and the resulting grinding vibration cannot be ignored. It could provide theoretical guidance for the research and practical processing of grinding surface performance of spiral bevel gears.

The service life of the planetary reducer in a hub drive system largely depends on the system reliability design. Aimed at the problems of lower credibility and inadequate depth in the reliability allocation, based on improved FMECA formulas and order statistics theory, an advanced reliability allocation method of the planetary reducer is proposed. The basic characteristics of the planetary reducer are analyzed, and FMECA formulas with the positive failure correlation modifying operator are presented, which indicate that the subsystem complexity and the failure occurrence change in the same direction as the failure correlation degree, respectively. Simultaneously, based on the Gumbel Copula function and order statistics theory, the reliability allocation model is established to assign reliability design indices to parts of the planetary reducer. By comparing the subsystem reliability allocation weights obtained by different methods, results show that the allocation result of the proposed method is more credible. It will be helpful to accomplish the deeper reliability allocation and improve the service life of the planetary reducer.

Rolling bearing plays an important role in carrying and transmitting power in rotating machinery, and the bearing fault is easy to lead to mechanical accidents, resulting in huge losses and casualties. Therefore, the condition monitoring and diagnosis of rolling bearings are very important to improve the safety of equipment. Compound fault is a common fault evolved from the initial defect, which is characterized by randomness, coupling, concealment, and secondary. The existence of these characteristics brings great challenges to the accurate diagnosis of compound faults. In the diagnosis of compound faults, the traditional methods that select the single optimal demodulation frequency band for analysis and identification sometimes cannot completely extract multiple fault components, which are prone to miss diagnosis and misdiagnosis. In order to solve this problem, the SEACKgram method is proposed by constructing a Square Envelope Unbiased Autocorrelation Correlation Kurtosis (SEACK) index. The frequency band of the original signal is divided by the Maximal Overlap Discrete Wavelet Packet Transform, and the SEACK index is used to quantitatively describe the fault signals of different frequency bands. According to the different fault periods, the resonant frequency bands of the maximum SEACK value are selected, then the resonance band signal is analyzed by square envelope spectrum, and the fault type is identified according to the fault characteristic frequency. The simulated and experimental vibration signals of rolling bearings with compound faults are used to verify the feasibility of the proposed method. The results show that the proposed SEACKgram can improve the accuracy of compound faults identification and would be applied in engineering practice to a certain extent. [ABSTRACT FROM AUTHOR]

Rolling bearings play a crucial role as components in rotating machinery across various industrial fields. Bearing faults can potentially lead to severe accidents in operating machines. Therefore, condition monitoring and fault diagnosis of rolling bearings are essential for preventing equipment failures. Multiple faults are a common occurrence resulting from the prolonged operation of rolling bearings, and numerous research efforts have been made to study multiple faults in different components of the bearing. However, diagnosing multiple faults in a single component of the rolling bearing still remains a highly challenging task. In this paper, a multiple faults separation and identification method based on time-frequency (TF) spectrogram (TFS) is proposed for vibration signals of rolling bearings. Firstly, the fast path optimization method is improved to match the TFS of original vibration signals in bearing faults generated by short-time Fourier transform. Then multiple TF curves are extracted from the TFS by the proposed multiple transient component curves extraction method based on the improved fast path optimization method. With the fault characteristic period, a classification criterion is introduced to separate TF curves. Secondly, a TF masking method is constructed to retain the TF information closely related to fault components of vibration signals. Finally, the novel TF representation can be obtained to develop signal reconstruction, and multiple faults can be detected based on envelope analysis separately. The experiments from rolling bearings with multiple faults on raceways are used to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Dynamic modelling of rolling element bearing (REB) is a significant method to explore the vibration mechanism generated by fault, and it is the theoretical basis of fault diagnosis of REBs. Aiming at the complexity of defect-rolling-element interaction under radial load, the whole contact process of rolling element (RE) passing over defective area of outer or inner ring is analysed in detail. The impact force excitation function is derived by rotation and revolution velocity of RE. A four degree-of-freedom (DOF) dynamic model of REB with compound fault of both inner and outer raceway surface is developed by considering the time-varying displacement, impact force excitative and elastohydrodynamic lubrication (EHL) condition, and the novelty of the model is that the improved impact force excitation function is used. The experimental validation is carried out on test tig of Machinery Fault Simulator. The change of impact force with shaft speed and defect size is analysed. It is shown that the simulation results of the proposed model are closer to experimental results. A mapping method from defect-rolling-element-defect (DRED) behaviour to time is proposed to study the vibration characteristics of DRED behaviour, the results show that the amplitude of vibration will decrease when the same RE collides with inner and outer raceway defects simultaneously. When the same RE collides with inner and outer raceway defect successively, the amplitude of vibration will reach the maximum during the inner raceway defect rolling over each RE once. The proposed model can be used in practical application to study the influence of compound defects on vibration response of REB. [ABSTRACT FROM AUTHOR]

The vibration characteristics and skidding behaviour of deep groove ball bearings (DGBBs) are significantly influenced by the evolution of local defects and thermal effects. In previous studies, the influences of skidding and thermal effects were not considered in order to simplify the model of defective bearings. But the presence of skidding and thermal should not be ignored to accurately simulate the operation of bearing. To gain a comprehensive understanding of the operational mechanism of defective bearings, it is crucial to examine the skidding and thermal characteristics of various defect types using dynamic modelling approaches. In this study, the DGBB dynamic model for seven types of defects is established, which considers the self-rotation, rotation, and radial motion of ball, the contact force, ball/cage and ball/raceway skidding, and the effects of thermal elastohydrodynamic lubrication (TEHL). Experimental data from a machine fault simulator test rig is utilized to validate the accuracy of the proposed modelling methods. The results indicate that compound defects (CDs) result in higher vibration amplitudes and more severe skidding phenomena compared to single defects (SDs). Furthermore, compound defects exhibit a greater thermal effect on the oil film in the contact area than SDs, significantly impacting the operational performance of the bearing. [ABSTRACT FROM AUTHOR]