Yong-Han Kim

Optimum shape design of rotating shaft by ESO method

Evolutionary structural optimization (ESO) method is based on a simple idea that the optimal structure can be produced by gradually removing the ineffectively used material from the design domain. ESO seems to have some attractive features in engineering aspects: simple and fast. In this paper, ESO is applied to optimize shaft shape for the rotating machinery by introducing variable size of finite elements in optimization procedure. The goal of this optimization is to reduce total shaft weight and resonance magnification factor (Q factor), and to yield the critical speeds as far from the operating speed as possible. The constraints include restrictions on critical speed, unbalance response and bending stresses. Sensitivity analysis of the system parameters is also investigated. The results show that new ESO method can be efficiently used to optimize the shape of rotor shaft system with frequency and dynamic constraints.

Optimal design of nonlinear squeeze film damper using hybrid global optimization technique

The optimal design of the squeeze film damper (SFD) for rotor system has been studied in previous researches. However, these researches have not been considering jumping or nonlinear phenomena of a rotor system with SFD. This paper represents an optimization technique for linear and nonlinear response of a simple rotor system with SFDs by using a hybrid GA-SA algorithm which combined enhanced genetic algorithm (GA) with simulated annealing algorithm (SA). The damper design parameters are the radius, length and radial clearance of the damper. The objective function is to minimize the transmitted load between SFD and foundation at the operating and critical speeds of the rotor system with SFD which has linear and nonlinear unbalance responses. The numerical results show that the transmitted load of the SFD is greatly reduced in linear and nonlinear responses for the rotor system.

Noise Source Identification of Small Fan-BLDC Motor System for Refrigerators

Noise levels in household appliances are increasingly attracting attention from manufacturers and customers. Legislation is becoming more severe on acceptable noise levels and low noise is a major marketing point for many products. The latest trend in the refrigerator manufacturing industry is to use brushless DC (BLDC) motors instead of induction motors in order to reduce energy consumption and noise radiation. However, cogging torque from BLDC motor is an undesirable effect that prevents the smooth rotation of the rotor and results in noise. This paper presents a practical approach for identifying the source of excessive noise in the small fan-motor system for household refrigerators. The source is presumed to a mechanical resonance excited by torque ripple of the BLDC motor. By using finite element analysis, natural frequencies and mode shapes of the rotating part of the system are obtained and they are compared with experimental mode shapes obtained by electronic torsional excitation test which uses BLDC motor itself as an exciter. Two experimental validations are carried out to confirm the reduction of excessive noise.

Parameter Comparison of Acoustic Emission Signals for Condition Monitoring of Low-speed Bearings

Abstract The moving components of low-speed machines which require condition monitoring are mainly gears and bearings. Among them, bearings are the most critical component to be monitored. Besides providing rotating motion, they are required to carry heavy load. This study investigates the application of Acoustic Emission (AE) technique for condition monitoring of low-speed bearings. Experimental tests involving a new and an inner race damaged bearing were performed using a fault simulator operating at speeds ranging from 1200 rpm to 30 rpm. Typical hit-based AE analysis, time-domain statistical parameters and frequency-domain with modified peak ratio were calculated and compared to gauge the capability of the technique for use in condition monitoring of low-speed bearings.

Condition Monitoring of Low-speed Bearings - a Review

Abstract Machines with operating speeds less than 600 rpm are classified as low-speed machinery. These machines are usually the most critical items in the production line, generally large and have high rotating inertias. Until recently, there has not been much interest in condition monitoring of these machines as they do not fail easily. However, if an expected failure does occur, the downtime and replacement costs can be enormous, which can lead to massive production loss. Unlike those medium- to high-speed machines, condition monitoring of low-speed machinery presents a challenge as traditional velocity and acceleration sensors are only sensitive to responses with high impact rates. The moving components of these machines that require condition monitoring are mainly bearings and gears. Due to the lack of interest until recently, there is limited literature on condition monitoring of low-speed machinery. In this review, the authors have attempted to gather together the innovative and advanced approaches on condition monitoring of low-speed machinery, with the main focus on rolling element bearing condition monitoring.

Investigation of Dynamic Property of Squeeze Film Damper Using Magnetic Fluid

The paper presents the identification of dynamic property of a rotor system with a squeeze film damper (SFD) using magnetic fluid. An electromagnet Is installed in the inner damper of the SFD. The magnetic fluid is well known as a functional fluid. Its rheological property can be changed by controlling the applied current to the fluid and the fluid can be used as lubricant. Basically, the proposed SFD has the characteristics of a conventional SFD without an applied current, while the damping and stiffness Properties change according to the variation of the applied electric current. Therefore, when the applied current is changed, the whirling vibration of the rotor system can be effectively reduced. The clustering-based hybrid evolutionary algorithm (CHEA) is used to identify linear stiffness and damping coefficients of the SFD based on measured unbalance responses.