• Journal of the Korean Society for Precision Engineering
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• v.32 no.4
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• pp.329-337
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• 2015

In this paper, a simulation based estimation method of energy consumption of the spindle and feed drives for the NC machine tool during the cutting process is proposed. To predict energy consumption of the feed drive system, position, velocity, acceleration and jerk of the table are analyzed based on NC data and then the power and energy are calculated considering friction force and mass of the stages. Energy consumption of the spindle is estimated based on models from acceleration motion of rotating parts, friction torque and power loss of motors. Moreover, simulation models of cutting power and energy for the material removal along the NC tool paths are proposed.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.111-118
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• 2011

In recent years, various types of partial discharge (PD) methods such as capacitive, inductive, electromagnetic, and acoustic coupling techniques have been developed for diagnosing rotating machines. An electromagnetic (EM) probe, which is an inductively coupled type of sensor, is required for detecting corona and internal discharges during off-line tests. In this study, a new technique for enhancing the measurement sensitivities for corona and internal discharge based on an EM inductive position sensor is proposed. An EM probe that winds wires around horseshoe-shaped and cylindershaped ferrites as helices is designed and optimized for the implementation of off-line PD monitoring of the stator winding of a rotating machine. The measurement system based on this design is implemented, and it is verified from the results of the experiment performed in this study that the probe provides similar performance as existing commercial products.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.1020-1028
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• 2011

As rotating machines play an important role in industrial applications such as aeronautical, naval and automotive industries, many researchers have developed various condition monitoring system and fault diagnosis system by applying artificial neural network. Since using obtained signals without preprocessing as inputs of neural network can decrease performance of fault classification, it is very important to extract significant features of captured signals and to apply suitable features into diagnosis system according to the kinds of obtained signals. Therefore, this paper proposes a neural-network-based fault diagnosis system using AR coefficients as feature vectors by LPC(linear predictive coding) and EIV(errors-in variables) analysis. We extracted feature vectors from sound, vibration and current faulty signals and evaluated the suitability of feature vectors depending on the classification results and training error rates by changing AR order and adding noise. From experimental results, we conclude that classification results using feature vectors by EIV analysis indicate more than 90 % stably for less than 10 orders and noise effect comparing to LPC.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1257-1274
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• 2023

Rotating machines heavily rely on an intricate network of interconnected sub-components, with bearing failures accounting for a substantial proportion (40% to 90%) of all such failures. To address this issue, intelligent algorithms have been developed to evaluate vibrational signals and accurately detect faults, thereby reducing the reliance on expert knowledge and lowering maintenance costs. Within the field of machine learning, Artificial Immune Systems (AIS) have exhibited notable potential, with applications ranging from malware detection in computer systems to fault detection in bearings, which is the primary focus of this study. In pursuit of this objective, we propose a novel procedure for detecting novel instances of anomalies in varying operating conditions, utilizing only the signals derived from the healthy state of the analyzed machine. Our approach incorporates AIS augmented by Dynamic Time Warping (DTW). The experimental outcomes demonstrate that the AIS-DTW method yields a considerable improvement in anomaly detection rates (up to 53.83%) compared to the conventional AIS. In summary, our findings indicate that our method represents a significant advancement in enhancing the resilience of AIS-based novelty detection, thereby bolstering the reliability of rotating machines and reducing the need for expertise in bearing fault detection.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.324-333
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• 2009

This paper presents a numerical simulation study of the transient behavior of a $2{\times}340MW$ pump-turbine power plant, where the results show an unstable behavior at runaway. First, the modeling of hydraulic components based on equivalent schemes is presented. Then, the 2 pump-turbine test case is presented. The transient behavior of the power plant is simulated for a case of emergency shutdown with servomotor failure on Unit 1. Unstable operation at runaway with a period of 15 seconds is properly simulated using a 1-dimensional approach. The simulation results points out a switch after 200 seconds of the unstable behavior between a period of oscillations initially of 15 seconds to a period of oscillation of 2.16 seconds corresponding to the hydraulic circuit first natural period. The pressure fluctuations related to both the rigid and elastic water column mode are presented for oscillation mode characterization. This phenomenon is described as a switch between a rigid and an elastic water column oscillation mode. The influence of the rotating inertia on the switch phenomenon is investigated through a parametric study.

• 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 of Mechanical Engineers A
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• v.34 no.11
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• pp.1681-1689
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• 2010

Several studies on the use of Support Vector Machines (SVMs) for diagnosing rotating machinery have been successfully carried out, but the fault classification depends on the input features as well as a multi-classification scheme, binary optimizer, kernel function, and the parameter to be used in the kernel function. Most of the published papers on multiclass SVM applications report the use of the same features to classify the faults. In this study, simple statistical features are determined on the basis of time domain vibration signals for various fault conditions, and the optimal features for each fault condition are selected. Then, the optimal features are used in the SVM training and in the classification of each fault condition. Simulation results using experimental data show that the results of the proposed stepwise classification approach with a relatively short training time are comparable to those for a single multi-class SVM.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1769-1776
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• 2016

For on-line partial discharge (PD) monitoring of rotating machines, a novel sensor is proposed, which can be installed on the power lead inside the terminal box of the machine. The sensor has been designed to have high capacitance, and minimal reflection of measured pulses. As a sensitivity of the sensor, transfer impedance $Z_t$ has been measured and compared to conventional coupler-type sensors. A simple method is presented for measuring $Z_t$ of coupler sensors, using a vector network analyzer and a practical lead-cable of rotating machine. Through this method, it became possible to measure the $Z_t$ of coupler sensors including the installation environment of them. The $Z_t$ of the proposed sensor is higher than that of same sized other conventional couplers at frequencies between 30 and 92 MHz. Another sensitivity test has been performed using a PD calibrator as a test pulse source. The proposed sensor has higher measured peak voltage than the conventional coupler type sensors when the same charges were input.

• 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.

• Coupled systems mechanics
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• v.7 no.4
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• pp.373-393
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• 2018

This paper is concerned with the wave propagation behavior of rotating functionally graded temperature-dependent nanoscale beams subjected to thermal loading based on nonlocal strain gradient stress field. Uniform, linear and nonlinear temperature distributions across the thickness are investigated. Thermo-elastic properties of FG beam change gradually according to the Mori-Tanaka distribution model in the spatial coordinate. The nanobeam is modeled via a higher-order shear deformable refined beam theory which has a trigonometric shear stress function. The governing equations are derived by Hamilton's principle as a function of axial force due to centrifugal stiffening and displacement. By applying an analytical solution and solving an eigenvalue problem, the dispersion relations of rotating FG nanobeam are obtained. Numerical results illustrate that various parameters including temperature change, angular velocity, nonlocality parameter, wave number and gradient index have significant effect on the wave dispersion characteristics of the understudy nanobeam. The outcome of this study can provide beneficial information for the next generation researches and exact design of nano-machines including nanoscale molecular bearings and nanogears, etc.