• 대한기계학회논문집A
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• 제32권9호
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• pp.728-732
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• 2008

This paper presents ion-based micro vibration sensor for the ultra-high frequency vibration detection. Presented sensor uses the motion of anion and cation in an electrolyte. Electrolyte vibration sensors have the high shock survival characteristics and a simple read-out circuit because of the small mass and own charges of ions. Presented sensor measures the induced electric potential by the mechanical-electrical coupling. It consist of electrolyte chamber and detection electrode. Electrolyte chamber was fabricated by PDMS molding. Detection electrode was made of gold evaporation on pyrex glass. Size of electrolyte chamber was designed as $600{\times}600{\times}100um$. Detection electrode had 200nm-thick and 42um-gap. In the experimental study, 5.8M sodium Chloride (NaCl) solution was used as electrolyte in 36nl-chamber. Mechanical vibration was measured from 2kHz to 4MHz.

• Journal of Advanced Marine Engineering and Technology
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• 제28권2호
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• pp.285-291
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• 2004

Early detection of an internal malfunction of machinery plays a very important part in all condition monitoring programs. Sensors to detect amplitude. velocity and acceleration are widely used in vibration detection and control. Piezoceramic materials are largely used in sensors and actuators for vibration monitoring and control due to their relatively large output from an induced strain and their arguable self powering characteristics. In this paper a cheap and yet reliable sensors/actuators were developed to detect vibration. The results show that low cost PZT can be designed for optimum detection of bearing vibration. This paper presents the experimental results of a number of piezoceramics characteristics in terms of resonant frequencies and variation of PZT constants with temperature.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.583-589
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• 2001

For several decades many researchers have studied various algorithms, known as non-destructive testing, to identify abnormalities within a structure. Damage detection technique using vibration signal is a kind of these methods. Many researchers have published lots of papers dealing vibration signal to identify structural damage. All the methods for damage detection using vibration signal can be divided into two big categories. The first category is the method that requires some reference model such as finite element model, and the second is the method that does not require any reference model but needs only experimental data. This paper will be devoted to classify damage detection methods that utilize vibration signal.

• Structural Engineering and Mechanics
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• 제45권2호
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• pp.159-168
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• 2013

The effect of structural uncertainties or measurement errors on damage detection results makes the robustness become one of the most important features during identification. Due to the wide use of vibration signatures on damage detection, the development of vibration-based techniques has attracted a great interest. In this work, a review on vibration-based robust detection techniques is presented, in which the robustness is considerably improved through modeling error compensation, environmental variation reduction, denoising, or proper sensing system design. It is hoped that this study can give help on structural health monitoring or damage mitigation control.

• 한국정밀공학회지
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• 제12권10호
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• pp.50-56
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• 1995

Chatter Vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life, machine life and the productivity of machining process. The real-time detection of the chatter vibration is is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer, Accelermeter and AE sensor. Especially, Acoustic Emission(AE) generated during turning was investigated the possibility for real-time detection of chatter vibration. Turning experiments were performed using carbide insert tip under realistic cutting conditions and tapered workpiece of SM45C. Consquently, the real-time detection using multi-sensing system can be used for Inprocess monitoring of chatter vibration.

• 정보처리학회논문지A
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• 제17A권2호
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• pp.81-92
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• 2010

진동 정보를 통해 기계 설비의 상태나 고장 유무를 판단하는 연구들이 다수 진행 중에 있는데, 대부분의 연구에서는 설비에 대한 진동을 모니터링하거나 고장 유무를 판별하여 사용자에게 알리는 수준이다. 본 논문에서는 진동에 의한 고장 진단과 판별을 보다 정교하게 수행하는 선박 엔진의 고장 감지 기법과 시스템을 제안하였다. 일차적으로 이중적 진동 정보 판별 기법을 적용하여 진동 정보를 확인한 다음에 고장 유무를 검사한다. 만일 고장이 발생한 경우에는 진동 정보의 오류 부분만을 이용하여 고장 진동 파형에 대한 오차 범위를 기준으로 어떤 유형의 고장인지를 판별할 수 있는 기법을 적용하였다. 또한 선박의 진동 경향 분석과 엔진 안전 보존을 목적으로 진동 정보를 데이터베이스에 저장하고 추적할 수 있도록 시스템을 구현하였다. 제안 시스템을 선박 엔진의 고장 판별 유무와 고장 진동 파형 감별 인자에 대해 실험을 수행한 결과 고장 유무 판별은 약 100% 정확성을 가졌고 고장 진동 파형의 유형 인식에서는 약 96% 정확성을 가졌다.

• Journal of Mechanical Science and Technology
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• 제20권7호
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• pp.929-940
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• 2006

Early detection and diagnosis of incipient induction machine faults increases machinery availability, reduces consequential damage, and improves operational efficiency. However, fault detection using analytical methods is not always possible because it requires perfect knowledge of a process model. This paper proposes a neural network based expert system for diagnosing problems with induction motors using vibration analysis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals, and the neural network is trained and tested using the vibration spectra. The efficiency of the developed neural network expert system is evaluated. The results show that a neural network expert system can be developed based on vibration measurements acquired on-line from the machine.

• 한국컴퓨터정보학회논문지
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• 제16권5호
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• pp.61-71
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• 2011

금속물체의 피로도를 측정하기 위하여 고속으로 진동시키면서 비접촉으로 정밀하게 변위를 측정하는 방법에 대한 연구가 많이 이루어지고 있다. 비접촉 고속 진동 검출센서들은 와류 센서나 레이저 센서들을 주로 사용하고있지만 매우 고가이다. 최근 저가의 유도성 센서를 고속 진동검출에 적용하려는 연구가 이루어지고 있으나 아직은 초보단계이다. 본 연구에서는 저가의 유도성 센서를 이용하여 비접촉으로 고속 진동을 검출하는 새로운 근접 센서모듈 설계방법을 제안하였다. 기존의 유도성 센서모듈들은 검파, 적분, 및 증폭과정을 통하여 변위를 검출하기 때문에 아날로그회로 특성상 잡음에 약하고 적분과정에서 변위 검출속도 저하의 요인이 된다. 제안된 방법은 AD변환기(Analog to Digital converter)를 사용하지 않고 진동 주파수신호를 직접 디지털 신호로 변환하는 새로운 방법으로 아날로그 잡음의 영향을 적게 받으며 고속으로 신호를 처리할 수 있는 장점이 있다. 성능 평가를 위하여 셰이커로 진동 주파수를 30Hz부터 1,100Hz 까지 일정간격으로 금속편을 진동시키면서 제안된 센서 모듈을 이용하여 비접촉으로 진동 신호를 검출하였다. 실험결과 비접촉 근접 거리 5mm 이내에서 진동 주파수 검출범위는 DC에서 1,100Hz까지 측정할 수 있었으며 진동 폭의 해상도는 $20{\mu}m$로 나타났다. 따라서 제안된 유도성 센서모듈은 정밀 비접촉 고속 진동검출 센서로서 충분한 성능을 가지고 있다고 평가된다.

• Wind and Structures
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• 제24권4호
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• pp.385-403
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• 2017

In recent years, the wind energy has played an increasingly important role in national energy sector of many countries. To harvest more electric power, the wind turbine (WT) tower structure becomes physically larger, which may cause more risks during long-term operation. Associated with the great development of WT projects, the number of accidents related to large-scaled WT has also been increased. Therefore, a structural health monitoring (SHM) system for WT structures is needed to ensure their safety and serviceability during operational time. The objective of this study is to develop a hybrid damage detection method for WT tower structures by measuring vibration and impedance responses. To achieve the objective, the following approaches are implemented. Firstly, a hybrid damage detection scheme which combines vibration-based and impedance-based methods is proposed as a sequential process in three stages. Secondly, a series of vibration and impedance tests are conducted on a lab-scaled model of the WT structure in which a set of bolt-loosening cases is simulated for the segmental joints. Finally, the feasibility of the proposed hybrid damage detection method is experimentally evaluated via its performance during the damage detection process in the tested model.

• 제어로봇시스템학회논문지
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• 제9권11호
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• pp.874-882
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• 2003

The condition assessment of engineering systems has increased in importance because the manpower needed to operate and supervise various plants has been reduced. Especially, induction motors are at the core of most engineering processes, and there is an indispensable need to monitor their health and performance. So detection and diagnosis of motor faults is a base to improve efficiency of the industrial plant. In this paper, a model-based fault detection system is developed for induction motors, using steady state vibration signals. Early various fault detection systems using vibration signals are a trivial method and those methods are prone to have missed fault or false alarms. The suggested motor fault detection system was developed using a model-based reference value. The stationary signal had been extracted from the non-stationary signal using a data segmentation method. The signal processing method applied in this research is FFT. A reference model with spectra signal is developed and then the residuals of the vibration signal are generated. The ratio of RMS values of vibration residuals is proposed as a fault indicator for detecting faults. The developed fault detection system is tested on 800 hp motor and it is shown to be effective for detecting faults in the air-gap eccentricities and broken rotor bars. The suggested system is shown to be effective for reducing missed faults and false alarms. Moreover, the suggested system has advantages in the automation of fault detection algorithms in a random signal system, and the reference model is not complicated.