• 한국정밀공학회지
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• 제31권8호
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• pp.749-755
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• 2014

The aim of this study was to assess the effects of artificial unloading induced by hindlimb suspension on the trabecular bone in tibiae. Twenty four 12-week-old Sprague-Dawley rats were assigned to 3 groups, namely, the control group (CON, n = 8), the hindlimb-suspended group (HLS, n = 8) and HLS with partial vibration group (HLSPV, n = 8). After 4 weeks, compared with CON group, HLS group had significantly greater decreases on BMD, BV/TV, Tb.N, Conn.Dn and increase on Tb.Sp (p < 0.05). However, there were no significant differences in BMD and the other micro structural parameters of tibial trabecular bones between CON and HLSPV (p > 0.05). These results implied that partial vibration might inhibit the bone loss induced by hindlimb suspension. Furthermore, we could expect to apply partial vibration system in space environment, to prevent bone loss in astronauts.

• 한국소음진동공학회논문집
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• 제12권10호
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• pp.799-807
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• 2002

The vibration signal can give an indication of the condition of rotating machinery, highlighting potential faults such as unbalance, misalignment and bearing defects. The features in the vibration signal provide an important source of information for the faults diagnosis of rotating machinery. When additional training data become available after the initial training is completed, the conventional neural networks (NNs) must be retrained by applying total data including additional training data. This paper proposes the fault diagnostics algorithm using the ART-Kohonen network which does not destroy the initial training and can adapt additional training data that is suitable for the classification of machine condition. The results of the experiments confirm that the proposed algorithm performs better than other NNs as the self-organizing feature maps (SOFM) , learning vector quantization (LYQ) and radial basis function (RBF) NNs with respect to classification quality. The classification success rate for the ART-Kohonen network was 94 o/o and for the SOFM, LYQ and RBF network were 93 %, 93 % and 89 % respectively.

• 한국소음진동공학회논문집
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• 제12권5호
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• pp.365-373
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• 2002

This paper concerns the design and application of an electro-rheological (ER) fluid damper to semiactive vibration control of rotor systems. In particular, the system under present study is constructed structurally flexible in order to explore multiple critical speeds within operation range. To this end, the dynamic models of the proposed ER damper and its associated amplifier are derived in the first place. Subsequently entire rotor system model is assembled along with the dynamics of the end effector based on a finite element method enabling prediction as to its free and forced vibration characteristics. Next, an artificial intelligent (AI) feedback controller is synthesized taking into account the peculiarity of Coulomb damping effect in rotor applications. Finally, computational and experimental results are presented including model validation and control performances. In practice, such an AI control proved effective whether the spin speed was either before or after critical speeds.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.388-393
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• 2012

Vibration condition monitoring at low rotational speeds is still a challenge. Acoustic emission (AE) is the most used technique when dealing with low speed bearings. At low rotational speeds, the energy induced from surface contact between raceway and rolling elements is very weak and sometimes buried by interference frequencies. This kind of issue is difficult to solve using vibration monitoring. Therefore some researchers utilize artificial damage on inner race or outer race to simplify the case. This paper presents vibration signal analysis of low speed slewing bearings running at a low rotational speed of 15 rpm. The natural damage data from industrial practice is used. The fault frequencies of bearings are difficult to identify using a power spectrum. Therefore the relatively improved method of empirical mode decomposition (EMD), ensemble EMD (EEMD) is employed. The result is can detect the fault frequencies when the FFT fail to do it.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1162-1165
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• 2001

Operational Modal Analysis also known as Output Only Modal Analysis has in the recent years been used for extracting modal parameters of civil engineering structures and is now becoming popular for mechanical structures. The advantage of the method is that no artificial excitation need to be applied to the structure or force signals to be measured. All the parameter estimation is based upon the response signals, thereby minimising the work of preparation for the test. This test case is a controlled lab set-up enabling different parameter estimation methods techniques to be used and compared to the Operational Modal Analysis. For Operational Modal Analysis two different estimation techniques are used： a non-parametric technique based on Frequency Domain Decomposition (FDD), and a parametric technique working on the raw data in time domain, a data driven Stochastic Subspace Identification (SS!) algorithm. These are compared to other methods such as traditional Modal Analysis.

• Advances in concrete construction
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• 제8권2호
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• pp.77-90
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• 2019

This paper aims to investigate vibration frequency decrease (vibration period elongation) of reinforced concrete (RC) structure with unreinforced infill wall and reinforced infill wall exposed to progressively increased artificial earthquake load on shaking table. For this purpose, two shaking table experiments were selected as a case study. Shaking table experiments were carried on 1:1 scaled prototype one bay one storey RC structure with infill walls. The purpose of this shaking table experiment sequence is to assess local behavior and progressive collapse mechanism. Frequency decrease and eigen-vector evolution are directly related to in-plane and out-of-plane bearing capacities of infill wall enclosure with reinforced concrete frame. Firstly, frequency decrease-damage relationship was evaluated on the base of experiment results. Then, frequency decrease and stiffness degradation were evaluated with applied Peak Ground Acceleration (PGA) by considering strength deterioration. Lastly, eigenvector evolution-local damage and eigenvector evolution-frequency decrease relationship was investigated. Five modes were considered while evaluating damage and frequency decrease of the tested specimens. The relationship between frequency decrease, stiffness degradation and damage level were presented while comparing with Unreinforced Brick Infill (URB) and Reinforced Infill wall with Bed Joint Reinforcement (BJR) on the base of natural vibration frequency.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.411-416
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• 2006

Fault detection and diagnosis is the most important technology in condition-based maintenance(CBM) system that usually begins from collecting signatures of running machines using multiple sensors for subsequent accurate analysis. With the quick development in industry, there is an increasing requirement of selecting special sensors that are cheap, robust, and easy-installation. This paper experimentally investigated performances of four types of sensors used in induction motors faults diagnosis, which are vibration, current, voltage and flux. In addition, diagnostic effects of five popular classifiers also were evaluated. First, the raw signals from the four types of sensors are collected at the same time. Then the features are calculated from collected signals. Next, these features are classified through five classifiers using artificial intelligence techniques. Finally, conclusions are given based on the experiment results.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.559-564
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• 2001

In order to apply into a compact and reliable centrifugal blood pump, this paper introduces a self-bearing motor in which a rotor is rotated without contact. The rotor is actively controlled in only radial directions, while the axial and tilting motions are passively stable owing to the disk-shape structure of the rotor. A prototype was made in outer-rotor type that is far better in the compactness than inner-rotor type. The prototype could be driven up to 8000 rpm with the rotor vibration under 0.12mm. The maximum cardiac output and pressure head were 9 L/min and over 200 mmHg, respectively. These experimental results show that the proposed self-bearing motor has sufficient performance for application to a real blood pump.

• 한국정밀공학회지
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• 제17권7호
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• pp.98-105
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• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.619-624
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• 2004

In this research, the structural health monitoring method using wavelet packet analysis and artificial neural network (ANN) is developed. Wavelet packet Transform (WPT) is applied to the response acceleration of a 3 element-cantilever beam which is subjected to impulse load and Gaussian random load to decompose the response signal, then the energy of each component is calculated. The first ten largest components in magnitude among the decomposed components are selected as input to an ANN to identify the damage location and severity. This method successfully predicted the amount of damage in the structure when the structure is subjected to impulse load. However, when the beam is subjected to Gaussian random load which can be considered as ambient vibration it did not yield satisfactory results. This method is applicable to structures such as machinery gears that are subjected to repetitive loads.