• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.672-678
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• 2009

Acoustic Emission (AE) technique is a non-destructive testing method and widely used for the early detection of faults in rotating machines in these days, because the sensitivity of AE transducers is higher than normal accelerometers. So it can detect low energy vibration signals. The faults in the rotating machines are generally occurred at bearings and gearboxes which are the principal parts of the machines. It was studied to detect the bearing faults by envelop analysis in several decade years. And the researches showed that AE had a possibility of the application in condition monitoring system(CMS) using the envelope analysis for the rolling bearing. And peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. Noise level is needed to reduce to take exact PR value because the PR is calculated from total root mean square (RMS) and the harmonics peak levels of the defect frequencies of the bearing. Therefore, in this paper, the discrete wavelet transform (DWT) was added in the envelope analysis to reduce the noise level in the AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added the DWT. In the experiment result about inner fault of bearing, defect frequency was difficult to find about only envelop analysis. But it's easy to find defect frequency after wavelet transform. Therefore, Envelop analysis added wavelet transform was useful method for early detection of default in signal process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.2
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• pp.131-143
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• 2013

Vibration condition monitoring of low-speed rotational slewing bearings is essential ever since it became necessary for a proper maintenance schedule that replaces the slewing bearings installed in massive machinery in the steel industry, among other applications. So far, acoustic emission(AE) is still the primary technique used for dealing with low-speed bearing cases. Few studies employed vibration analysis because the signal generated as a result of the impact between the rolling element and the natural defect spots at low rotational speeds is generally weak and sometimes buried in noise and other interference frequencies. In order to increase the impact energy, some researchers generate artificial defects with a predetermined length, width, and depth of crack on the inner or outer race surfaces. Consequently, the fault frequency of a particular fault is easy to identify. This paper presents the applications of empirical mode decomposition(EMD) and ensemble empirical mode decomposition(EEMD) for measuring vibration signals slewing bearings running at a low rotational speed of 15 rpm. The natural vibration damage data used in this paper are obtained from a Korean industrial company. In this study, EEMD is used to support and clarify the results of the fast Fourier transform(FFT) in identifying bearing fault frequencies.

• Smart Structures and Systems
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• v.13 no.3
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• pp.453-471
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• 2014

The fault diagnosis of rolling element bearings has drawn considerable research attention in recent years because these fundamental elements frequently suffer failures that could result in unexpected machine breakdowns. Artificial intelligence algorithms such as artificial neural networks (ANNs) and support vector machines (SVMs) have been widely investigated to identify various faults. However, as the useful life of a bearing deteriorates, identifying early bearing faults and evaluating their sizes of development are necessary for timely maintenance actions to prevent accidents. This study proposes a new two-layer structure consisting of support vector regression machines (SVRMs) to recognize bearing fault patterns and track the fault sizes. The statistical parameters used to track the fault evolutions are first extracted to condense original vibration signals into a few compact features. The extracted features are then used to train the proposed two-layer SVRMs structure. Once these parameters of the proposed two-layer SVRMs structure are determined, the features extracted from other vibration signals can be used to predict the unknown bearing health conditions. The effectiveness of the proposed method is validated by experimental datasets collected from a test rig. The results demonstrate that the proposed method is highly accurate in differentiating between fault patterns and determining their fault severities. Further, comparisons are performed to show that the proposed method is better than some existing methods.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.122-130
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design, this study proposes a design method for determining design variables of an automotive wheel-bearing unit of double-row angular-contact ball bearing type by using a genetic algorithm. The desired performance of the wheel-bearing unit is to maximize system life while satisfying geometrical and operational constraints without enlarging mounting spae. The use of gradient-based optimization methods for the design of the unit is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding and dynamic mutation rate is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. A computer program is developed and applied to the design of a real wheel-bearing unit model to evaluate the proposed design method. Optimum design results demonstrate the effectiveness of the design method suggested in this study by showing that the system life of an optimally designed wheel-bearing unit is enhanced in comparison with that of the current design without any constraint violations.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.61-68
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• 2001

A rotor system is composed of a rotating shaft with supporting bearings. The rotor system is widely used in every rotating machinery such as the turbine generator and the high precision machine tools. A negligible error or malfunction in the rotor, however, can cause a catastrophic failure in the system then result in the environmental and economic disasters. A diagnosis of the rotor system is important in preventing these kinds of failures and disasters. Up to now, many researchers have devoted in the development of diagnosing tools for the system. The basic principles behind the tools are to retrieve the data through the sensors for a specific state of the system and then to identify the specific state through the heuristic methods such as neural network, fuzzy logic, and decision matrix. The proper usage of the heuristic methods will enhance the performance of the diagnostic procedure when together used with the statistical signal processing. In this paper, the methodologies in using the above 3 heuristic methods for the diagnostics of the rotor system are established and also tested and validated for the data retrieved from the rolling element bearing and journal bearing supported system.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.10a
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• pp.261-266
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• 2003

Foil air bearing, which is a noncontact bearing utilizing viscosity of operating fluid and elastic deformation of foil structure, has several advantages over rolling element bearings in terms of oilless environment, long life, high speed operation, and high temperature application over $500^{\circ}C$ . Recently advanced researches are actively being performed for the application to the extreme temperature such as gas turbines, as well as conventional small turbo machinery. In this paper, the principle of foil air bearing is introduced and a feasibility study to adopt a foil bearing as the turbine bearing of 65 HP turbo shaft engine, which is under development for UAV, is presented.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.354-363
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• 2005

Squeeze film dampers (SFDs) have been commonly used to effectively enhance the dynamic behavior of the rotating shaft supported by rolling element bearings. However, due to the recent trends of high operating speed, high load capacity and light weight in rotating machinery, it is becoming increasingly important to change the dynamic characteristics of rotating machines in operation so that the excessive vibrations, which may occurparticularly when passing through critical speeds or unstable regions, can be avoided. Semi-active type SFDs using magneto-rheological fluid (MR fluid), which responds to an applied magnetic field with a change in rheological behavior, are introduced in order to find its applications to rotating machinery as an effective device attenuating unbalance responses. In this paper, a semi-active SFD using MR fluid is designed, tested, and identified to investigate the capability of changing its dynamic properties such as damping and stiffness.In order to apply the MR-SFD to the vibration attenuation of a rotor, a systematic approach for determining the damper's optimal location is investigated, and also, a control algorithm that could improve the unbalance response characteristics of a flexible rotor is proposed and its control performance is validated with a numerical example.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1005-1011
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• 2004

Squeeze film dampers (SFDs) have been commonly used to effectively enhance the dynamic behavior of the rotating shaft supported by rolling element bearings. However, due to the recent trends of high operating speed, high load capacity and light weight in rotating machinery, it is becoming increasingly important to change the dynamic characteristics of rotating machines in operation so that the excessive vibrations, which may occur particularly when passing through critical speeds or unstable regions, can be avoided. Semi-active type SFDs using magneto-rheological fluid (MR fluid), which responds to an applied magnetic field with a change in rheoloaical behavior, are introduced in order to find its applications to rotating machinery as an effective device attenuating unbalance responses. In this paper, a semi-active SFD using MR fluid is designed, tested and identified by means of linear analysis to investigate the capability of changing its dynamic properties such as damping and stiffness. Furthermore, the proposed device is applied to a rotor system to investigate its potential capability for vibration attenuation: an efficient method for selecting the optimal location of the proposed damper is introduced and control algorithm that could improve the unbalance response properties of a flexible rotor is also proposed.

• Tribology and Lubricants
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• v.35 no.1
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• pp.37-43
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• 2019

This paper presents an optimization method to determine the shoulder height of an angular contact ball bearing by 3D contact analysis using nondimensional-shaped variables. The load analysis of the ball bearing is performed to calculate the internal load distributions and contact angles of each rolling element. From the results of bearing load analysis and the contact geometry between the ball and inner/outer raceway, 3D contact analyses using influence function are conducted. The nondimensional shoulder height and nondimensional load are defined to give the generalized results. The relationship between the shoulder height and radius of curvature of the shoulder under various loading conditions is investigated in order to propose a design method for the two design parameters. Using nondimensional parameters, the critical shoulder heights are optimized with loads, contact angles, and conformity ratios. We also develop contour maps of the critical shoulder height as functions of internal loads and contact angles for the different contact angles using nondimensional parameters. The results show that the dimensionless shoulder height increased as the contact angle and dimensionless load increased. Conversely, when the conformity ratio increased, the critical shoulder height decreased. Therefore, if the contact angle is reduced and the conformity ratio is increased within the allowable range, it will be an efficient design to reduce the shoulder height of ball bearings.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.17-24
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• 2014

This paper proposes a fault detection method for low-speed rolling element bearings of an induction motor using acoustic emission signals and histogram modeling. The proposed method performs envelop modeling of the histogram of normalized fault signals. It then extracts and selects significant features of each fault using partial autocorrelation coefficients and distance evaluation technique, respectively. Finally, using the extracted features as inputs, the support vector regression (SVR) classifies bearing's inner, outer, and roller faults. To obtain optimal classification performance, we evaluate the proposed method with varying an adjustable parameter of the Gaussian radial basis function of SVR from 0.01 to 1.0 and the number of features from 2 to 150. Experimental results show that the proposed fault identification method using 0.64-0.65 of the adjustable parameter and 75 features achieves 91% in classification performance and outperforms conventional fault diagnosis methods as well.