Vibration Analysis of Deep Groove Ball Bearing using Finite Element Analysis and Dimension Analysis

Condition monitoring of rotor dynamic is recognized as an advanced preventative maintenance technique for fault-free operation. Faulty bearings in rotating machines may cause severe problems and even untimely breakdowns. This work demonstrates the power of the finite element analysis (FEA) model and dimension analysis technique (DAT) to analyze the effect of the depth and slope angle of surface faults on the bearing contact characteristic. Experimentation is performed to investigate the vibration characteristics of ball bearings. The FEA, DAT, and experimentation show that vibration amplitude is a vital function of surface fault size. The current approach of FEA with DAT reflects their reliability and accuracy for the diagnosis of rotor systems. The present method was found effective in predicting vibration amplitude and defect frequency within acceptable error.

Multi-Objective Optimization of Deep Groove Ball Bearings Using Fatigue-Wear-Thermal Considerations Through Genetic Algorithms

Bearings are the key components in a wide range of machines used in different sectors of industries. Consequently, any improvement in the performance of bearings would be a step forward to extract better performance from those machines. With this motivation in mind, we selected the most common type of bearing, the Deep Groove Ball Bearing (DGBB), for optimizing its performance. Obviously, the first and foremost performance characteristic would be the dynamic load carrying capacity (CD), whose improvement directly leads to the increased service life of the bearing. We have considered two more characteristics of bearings, which we thought would have an impact on the bearings’ performance. They are elasto-hydrodynamic film thickness (hmin) and maximum temperature developed (Tmax) inside the bearing. Maximization of the lubricant thickness decreases the damage to the rolling elements and the raceways due to metal-metal contact. And minimization of temperature is desirable in every machine element. Later, we would also see that the three objective functions chosen are conflicting in nature and hence mutually independent. For the current optimization problem, a genetic algorithm, Elitist Non-dominating Sorting Genetic Algorithm (NSGA-II) is chosen. And the bearing dimensions, which could be controlled during manufacturing are chosen as the design variables. Multiple constraints are chosen based on the design space and strength considerations. The optimization algorithm is used on a set of commercially available bearings. Pareto fronts are drawn to give the designer a multitude of optimal solutions to choose from. However, in this paper, the knee-point solution is presented, which is one of the optimum solutions. When compared with the commercial bearings, the bearings with optimized dimensions have higher dynamic load carrying capacities and hence longer life. Also, the sensitivity analysis is done to check the robustness of the bearings to manufacturing tolerances in the design variables. Finally, for visualization and as a check for physical plausibility, the radial dimensions of one of the optimized bearings have been shown.

Noise calculation method of deep groove ball bearing caused by vibration of rolling elements considering raceway waviness

Raceway waviness error is the main reason to cause rolling elements to vibrate along axial direction and emit noise. In this paper, the mechanical analysis on deep groove ball bearing is carried out. With auto-correlation function, random surface waviness of both inner and outer raceways is simulated. A contact model of rolling elements and raceways considering surface waviness is established. Combining with the theory of acoustic equation, a calculation model is established for the noise caused by vibration of rolling elements and inner ring. The results show that with the decrease of machining accuracy, the noise of rolling elements increases due to axial vibration; with the increase of rotation speed, the noise also increases. Besides, the spectrum of radiation noise of inner raceway with different waviness amplitudes is given. The results indicate that the 3-D waviness on raceway surface has an influence on the vibration and the noise emitted by both rolling elements and inner ring, and provide guidance for sound control in deep groove rolling bearing.

Dynamic Modeling and Vibration Characteristics Analysis of Deep-Groove Ball Bearing, Considering Sliding Effect

To study the vibration characteristics of deep-groove ball bearing, considering the influence of sliding, the dynamic model of the DGB 6205 system is established in this paper. The DGB 6205 system model includes the movement of the bearing inner ring in the X and Y directions, the rotation of the cage, the rotation movement of each ball, the revolution movement of each ball and the movement along the radial direction of each ball. Based on the system model, the differential equations of motion of the system are established, and the correctness of the model is verified by experiment. The slip characteristics of the DGB 6205 system are studied by numerical simulation. At the same time, the influence of time-varying load on the vibration characteristics of the system is studied. Then, the sensitivity of system parameters is analyzed. The results show that the sliding speed between the ball and the inner raceway is greater than that between the ball and the outer raceway. The radial vibration response of DGB 6205 system under time-varying load is less than that under constant load. The increase of radial clearance will increase the vibration response of DGB 6205 system.

Early Weak Fault Diagnosis of Rolling Bearings Based on Fiber Bragg Grating Sensing Monitoring

Aiming at the problems of weak dynamic response and difficulty in diagnosis of early damage of rolling bearings, a diagnosis method for early damage of rolling bearings is proposed. Taking radial rolling bearings as the main research object, the load symmetric structure of deep groove ball bearings is analyzed. Based on the mechanical second-order system theory, the sensor monitoring structure is constructed. The generalized resonance principle is used to identify weak signals, and the fiber Bragg grating is used for signal sensing. The signal is obtained through the fiber Bragg grating high-speed demodulator. When a continuous periodic generalized resonance wave appears in the amplitude–frequency analysis of the signal, and there is a high-frequency resonance frequency, it can be proved that the bearing is faulty. The diagnosis method can effectively avoid the interference of low-frequency signals, the frequency spectrum is pure and there is no electromagnetic interference. It fully shows that the fiber Bragg grating sensor is suitable for the monitoring and diagnosis of the early weak fault of the bearing.