Previous studies showed that isoflurane-induced cognitive deficits could be alleviated by dexmedetomidine in young animal subjects. In the current study, we examine whether dexmedetomidine could also alleviate isoflurane-induced cognitive deficits in senile animals. Senile male C57BL/6 mice (20 months) received dexmedetomidine (50 μg/kg, i.p.) or vehicle 30 minutes prior to isoflurane exposure (1.3% for 4 h). Cognitive function was assessed 19 days later using a 5-day testing regimen with Morris water maze. Some subjects also received pretreatment with α₂ adrenoreceptor antagonist atipamezole (250 μg/kg, i.p.), JAK2 inhibitor AG490 (15 mg/kg i.p.) or STAT3 inhibitor WP1066 (40 mg/kg i.p.) 30 minutes prior to dexmedetomidine. Isoflurane exposure increased and reduced the time spent in the quadrant containing the target platform in training sessions. The number of crossings over the original target quadrant was also decreased. Dexmedotomidine attenuated such effects. Effects of dexmedotomidine were reduced by pretreatment with atipamezole, AG490 and WP1066. Increased phosphorylation of JAK2 and STAT3 in the hippocampus induced by isoflurane was augmented by dexmedetomidine. Effects of dexmedetomidine on JAK2/STAT3 phosphorylation were attenuated by atipamezole, AG490 and WP1066. Isoflurane promoted neuronal apoptosis and increased the expression of cleaved caspase-3 and BAD, and reduced Bcl-2 expression. Attenuation of such effects by dexmedotomidine was partially blocked by atipamezole, AG490 and WP1066. Dexmedetomidine could protect against isoflurane-induced spatial learning and memory impairment in senile mice by stimulating the JAK2/STAT3 signaling pathway. Such findings encourage the use of dexmedetomidine in geriatric patients receiving isoflurane anesthesia.

The development trend of high precision of mechanical equipment, the reliability of bearings work increasingly demanded. Therefore, it is crucial for the reliable operation of mechanical equipment to evaluate the health status of bearings. It combines IDBO (Improved Dung beetle optimizer) optimised VMD (Variational mode decomposition) and CNN-BiLSTM (convolutional neural network-Bi-directional Long Short-Term Memory) to achieve rolling bearing conformity fault diagnosis and damage assessment. Chaotic mapping, Golden sine algorithm and cosine iteration strategy are introduced to improve the performance of DBO, and the hyperparameters of VMD are optimised using IDBO to improve the signal pre-processing. Feature extraction and fault classification of signals using CNN-BiLSTM is used to compensate for the poor diagnosis of CNN timing signals by BiLSTM instead of Softmax classifier. The HUST dataset is used to discuss the application of signal processing methods and neural network models in bearing composite fault diagnosis. The advantages of the proposed scheme in bearing composite fault and damage assessment are verified, effectively solving the challenge of rolling bearing composite fault diagnosis.

With the continuous advancement in bearing speed, bearing assembly clearance (pocket, radial, and guide clearances) has a particularly significant impact on dynamic characteristics of bearing. In order to improve its performance, it is necessary to generate an optimized design for assembly clearance based on dynamic analysis. In this paper, a dynamic model of cylindrical roller bearing has been put forth based on the variable step fourth-order Runge–Kutta method, while the simulation results have been verified by a high-speed bearing cage motion testing machine. Considering pocket, radial, and guide clearances as independent variables and maximum impact force, whirl deviation ratio, and minimum power loss as the objectives, a multiobjective optimized model of cylindrical roller bearing has been developed using central composite experimental design (CCD) and response surface method. After optimization, the maximum impact force was reduced by 9.26%, the whirl deviation ratio was reduced by 2.87%, and power loss was reduced by 1.45%.

This paper investigates a method to dynamically model compound faults on the inner and outer rings of an angular contact ball bearing as well as their effects on its dynamic behavior. Gupta’s dynamic modeling method is used to consider changes in the deformation and direction of the contact load when the ball passes through the damaged area and to develop a dynamic model of compound faults in the angular contact ball bearing. The step‐changing fourth‐order Runge–Kutta method is used to solve the dynamic compound fault model. The time‐domain signal of vibration responses in the case of a single fault in the inner and outer rings exhibited a certain periodicity, and the frequency of faults in the envelope spectrum was clear. By comparison, the periodicity of compound faults was not clear. The signals of compound faults were decomposed by the dual‐tree complex wavelet transform to identify their characteristic frequency. Errors occurred between the characteristic frequency of the theoretical fault and its simulated value. They increased with the rotational speed and decreased with an increase in axial load, whereas the influence of radial load on them was minor. For compound faults on the inner and outer rings of an angular contact ball bearing, this study provides a modeling method that can describe changes in the deformation and direction of the contact load when the ball passes through the damaged area of the inner and outer rings. The work here can provide an important foundation for fault identification in angular contact ball bearings.

Faults in cylindrical roller bearings are one of the main contributors to major faults in rotating machinery. The development of bearing fault diagnosis technologies is key to measuring the performance, status, and risk of failure of rolling-element bearings and has attracted extensive attention from industry and academia. When faults arise, they are often not a single fault but a compound fault, such as the simultaneous failure of the inner and outer races. In this paper, a method for evaluating the size of compound faults on the inner and outer races of cylindrical roller bearings is proposed. The dynamic modeling method developed by Gupta is employed to create a dynamic model for compound faults on the inner and outer rings of rolling bearings that allows the time domain signal of the vibration responses of compound faults on the inner and outer races to be obtained. Adopting an improved continuous harmonic wavelet packet decomposition method for the decomposition and reconstruction of the compound fault signal, we arrive at the corresponding single-point fault signal. The relationship between defect size and key metrics of the vibration, such as root mean square acceleration (RMS), peak, crest factor (CF), kurtosis, and level crossing rate (LCR), is investigated. The results show that there is a strong linear correlation between LCR and defect size, which can be used to evaluate the size of the defect. Experimental data for cylindrical roller bearings with compound faults on the inner and outer races are examined to verify the results.

As a key component of the machine tool spindle, bearing has critical influences on the spindle thermal error. In particular, the installation errors of bearing have considerable effects upon the spindle thermal error by altering the bearings’ internal contact angles, contact loads, and friction torques for different ball positions, but have yet to be fully elucidated. In this article, the influence of installation errors on the resulting spindle thermal error was evaluated using both empirical methods and simulation method, with the ultimate aim of reducing installation error. Deviations within the bearing support were used to simulate bearing parallel misalignment; bearing parallel misalignment running model was built, and an analysis and comparison of various conditions were used to determine the influence, showing that the parallel misalignment has significant influence on the spindle Z direction thermal error.