Xiaohu Li

Heat analysis of ball bearing under nonuniform preload based on five degrees of freedom quasi-static model

Bearing preload has a great impact on the service performance of high-speed spindle, such as the temperature rise and stiffness. Because of the flatness error of spacer, the axial parallelism error of the spindle, the nonuniform heat distribution of ball bearing and the external loads, the outer ring of the bearing is often subjected to nonuniform distributed loads, which will result in the misalignment between outer ring and spindle. In such conditions, traditional uniform preload method may not meet the requirements for bearing temperature rise and spindle rotation accuracy. In this paper, a nonuniform preload is presented which not only includes the preload magnitude in traditional way, but also involves the preload distribution nonuniformly. Firstly, an equivalent transformation for nonuniform preload is built to simplify the nonuniform preload acting on the outer ring. Then based on the Hertz contact theory and ball bearing geometry theory, a five degrees of freedom quasi-static model of ball bearing under nonuniform preload is established. On the basis of this model, internal load and other contact parameters in bearing are calculated and the heat mechanism of ball bearing is analyzed. Finally, according to the heat generation model under nonuniform preload which include both preload magnitude and distribution, effects of both uniform and nonuniform preload on bearing heat and its distribution are investigated and compared, and the contact forces in bearing are then analyzed. The results show that compared with uniform preload, proper nonuniform preload could effectively improve the contact status between balls and rings, decrease the heat generation rate, and reduce the excessive local heat in ball bearing under practical working conditions.

Investigating effects of non-uniform preload on the thermal characteristics of angular contact ball bearings through simulations

Methods utilising rigid preloading and constant preloading in ball bearing systems may not be adequate to address the optimisation of problems in which preloading occurs. This is because of non-uniform loading on the bearings that is induced by manufacturing error, assembly error and external loads. A non-uniform preload is presented for the analysis of non-uniform bearing loading. A simulation method is developed to determine the effects on non-uniform loading on bearing thermal performance under different preloads. A three-degree-of-freedom model is built to simulate the heat generation rate of angular contact ball bearings under non-uniform preloads. In this model, the non-uniform preload is divided equally into two parts: a uniform preload and an equivalent moment. The bearing heat generation rate can then be employed in finite element analysis software to simulate the temperature field associated with the entire ball bearing. The simulation data shows that non-uniform preloading conditions on ball bearings can decrease heat generation. The results also show that non-uniform preloads can alleviate heating concentrations and reduce peak temperature values under working conditions.

A Multilayer Feed Forward Small-World Neural Network Controller and Its Application on Electrohydraulic Actuation System

Being difficult to attain the precise mathematical models, traditional control methods such as proportional integral (PI) and proportional integral differentiation (PID) cannot meet the demands for real time and robustness when applied in some nonlinear systems. The neural network controller is a good replacement to overcome these shortcomings. However, the performance of neural network controller is directly determined by neural network model. In this paper, a new neural network model is constructed with a structure topology between the regular and random connection modes based on complex network, which simulates the brain neural network as far as possible, to design a better neural network controller. Then, a new controller is designed under small-world neural network model and is investigated in both linear and nonlinear systems control. The simulation results show that the new controller basing on small-world network model can improve the control precision by 30% in the case of system with random disturbance. Besides the good performance of the new controller in tracking square wave signals, which is demonstrated by the experiment results of direct drive electro-hydraulic actuation position control system, it works well on anti-interference performance.

The mental workload judgment in visual cognition under multitask meter scheme

In this study, a multitask dynamic testing measure concerning meters was developed using the virtual meter design software GL Studio in order to measure mental workload under multitasks. We recorded subjects’ electroencephalogram (EEG) and analyzed their brain electrical data using spectrum methods, brain maps, independent component analysis (ICA), and Lempel-Ziv complexity (LZC) calculation. The experimental results showed that the methods appeared to be more motivated on the parietal and occipital lobe of the brain. Besides, in the corresponding channels, theta, alpha and beta brainwave frequencies were found to be significantly motivated. LZC was also considered as a powerful tool in evaluating mental workload, whose value has a close connection with mental workload. This research provided a referable experiment design and analysis for studies on the assessment of mental workload under multitasks.

Investigation of multiple spindle characteristics under non-uniform bearing preload

The non-uniform distribution load during machining and assembly process is crucial for spindle system, especially in complex working conditions. The conception of non-uniform preload adjustment approach was proposed and experimentally investigated in this article. Based on the mechanical equivalent principle, the non-uniform preload was theoretically transformed to the combination of uniform preload and an extra moment. Then, the non-uniform preload of rolling bearing was experimentally measured and analyzed via a spacer with 15-µm wear loss on the end face. The spindle performance factors, such as rotation accuracy, temperature rising, acceleration, and vibration, were all monitored. The rotation center of spindle was deviated in different non-uniform preload conditions. Meanwhile, the temperature and vibration performance of non-uniform preload are superior to those of uniform bearing preload.

Investigation of non-uniform preload effect on stiffness behavior of angular contact ball bearings:

Preloading is an effective way to maintain good performance of angular contact ball bearings. Traditionally, the rigid and constant preload are applied by uniform approaches on the bearing system. However, non-uniform loads occur while the surfaces of spacer are obliquitous at rigid preload or the stiffnesses of springs are inconsistent at constant preload. In this article, a new approach is proposed to incorporate the non-uniformity effect. Using this approach, the bearing performance under practical operating conditions could be improved. At first, the critical relationship between the stiffness behavior and the non-uniform preload of the ball bearing system is studied. Then, based on Jones’ model, the stiffness function of angular contact ball bearings with non-uniform preload is established analytically. Based on the functions, boundary conditions are determined and used to calculate the local contact deformation and predict the bearing stiffness when the preload is non-uniform. Finally, the stiffness of both ceramic and steel ball bearings under non-uniform preload and various operating conditions is simulated. Comparing with traditional methods, the new method has better performance in stiffness prediction under non-uniform preload. It will give a designer a deep insight on the dynamic analysis and optimization of the rotor-bearing system.

Study on the influence of machine tool spindle radial error motion resulted from bearing outer ring tilting assembly

To reveal the spindle radial error motion characteristics in condition of bearing outer ring tilting assembly, mathematical method on spindle radial error motion were analyzed. Then, in real operation condition the natural frequency of the test rig was investigated. Experimental system and methods were designed to test axial thermal displacement, radial error motion and modal characteristic of spindle in condition of bearing outer ring tilting assembly. Results show that axial thermal extension and radial vertical rising of spindle front-end occurs during thermal displacement test. With the same outer spacer nonparallelism, the synchronous error motion and total error motion generally increase with spindle rotation speed, and reach a peak at certain rotation speed.

Binary-state bacterial foraging optimization based on network topology and its application

AbstractBacterial foraging optimization (BFO) inspired by the foraging behavior of E.coli has been used to solve optimization problems. This paper presents a novel binary-state bacterial foraging optimization based on network topology (BBFO-NT). In the proposed BBFO-NT, a binary-state bacterial foraging strategy, which makes the bacteria to have mutual learning mechanism, is introduced. The two behavioral states include an explorative state based on Von Neumann topology and an exploitative state based on small-world networks. The bacteria co-evolve during the optimization process under the two states. Experiments on a set of benchmark functions validate the effectiveness of the improved algorithm. BFO and some other intelligent optimization algorithms are employed for comparison. The simulations show that the proposed BBFO-NT offers significant improvements than BFO. On this basis, the new algorithm has been successfully applied to the docking control. The experiments indicate that the improved algorithm ...

Experiment analysis of spindle performance with rolling bearing under non-uniform preload

As a result of the manufacturing errors in the main parts of spindle, and the errors in assembly process of spindle, as well as the non-uniform heat distribution during spindle operation, the non-uniformly distributed preload in rolling bearing is inevitable. The non-uniform preload has not only axial force on the rolling bearing, but also the bending moment around the rolling bearing center. The effect of preload in bearing being non-uniform on the spindle performance is still unclear. In order to analyze the spindle performance with rolling bearing under non-uniform preload, a spindle test system with adjustable non-uniform distribution preload is built. By changing the magnitude of preload force on each action point, it can make the preload force distribute non-uniformly. In the static state of spindle, upon the change of non-uniformly distributed preload, the radial displacement of spindle shaft end is also changed, while in the dynamic state of spindle, it will lead to the change of the rotation center of spindle as a result of bending moment accompanying the non-uniform preload. Furthermore, the dynamic and static results show that when the preload is under non-uniform distribution, the spindle performance is significantly different from that under uniform preload. So this study would have certain reference value to check the spindle performance and explore novel preload method for rolling bearing.

A new dynamic bacterial foraging optimization and its application on model reduction

Inspired by the foraging behavior of E. coli bacteria, bacterial foraging optimization (BFO) has emerged as a powerful technique for solving optimization problems. However, BFO shows poor performance on complex and high-dimensional optimization problems. In order to improve the performance of BFO, a new dynamic bacterial foraging optimization based on clonal selection (DBFO-CS) is proposed. Instead of fixed step size in the chemotaxis operator, a new piecewise strategy adjusts the step size dynamically by regulatory factor in order to balance between exploration and exploitation during optimization process, which can improve convergence speed. Furthermore, reproduction operator based on clonal selection can add excellent genes to bacterial populations in order to improve bacterial natural selection and help good individuals to be protected, which can enhance convergence precision. Then, a set of benchmark functions have been used to test the proposed algorithm. The results show that DBFO-CS offers significant improvements than BFO on convergence, accuracy and robustness. A complex optimization problem of model reduction on stable and unstable linear systems based on DBFO-CS is presented. Results show that the proposed algorithm can efficiently approximate the systems.