• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.9
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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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• v.28 no.2
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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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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• v.45 no.2
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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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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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.

• The KIPS Transactions:PartA
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• v.17A no.2
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• pp.81-92
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• 2010

There has been some research in the equipment defect detection based on vibration information. Most research of them is based on vibration monitoring to determine the equipment defect or not. In this paper, we introduce more accurate system for engine defect detection based on vibration information and we focus on detection of engine defect for boat and system control. First, it uses the duplicated-checking method for vibration information to determine the engine defect or not. If there is a defect happened, we use the method using error part of vibration information basis with error range to determine which kind of error is happened. On the other hand, we use the engine trend analysis and standard of safety engine to implement the vibration information database. Our simulation results show that the probability of engine defect determination is 100% and the probability of engine defect classification and detection is 96%.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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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.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.61-71
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• 2011

To measure the fatigue of metallic objects at high speed vibration while non-contact precision displacement measurement on how to have a lot of research conducted. Noncontact high-speed vibration detection sensor of the eddy current sensors and laser sensors are used, but it is very expensive. Recently, High-speed vibrations detection using an inexpensive inductive sensor to have been studied, but is still a beginner. In this paper, a new design of an inexpensive inductive proximity sensor has been suggested in order to measure high frequency dynamic displacements of metallic specimens in a noncontact manner. Detection of the existing inductive sensors, detection, integral, and amplified through a process to detect the displacement noise due to weak nature of analog circuits and integral factor in the process of displacement detection is slow. The proposed method could be less affected by noise, the analog receive and high-speed signal processing is a new way, because AD converter (Analog to Digital converter) without using the vibration frequency signals directly into digital signals are converted. In order to evaluate the sensing performance, The proposed sensor module using non-contact vibration signals were detected while shaker vibration frequencies from 30Hz to 1,100 Hz at intervals of vibrating metallic specimens. Experimental results, Vibration frequency detection range of the metallic specimins within close proximity to contactless 5mm could be measured from DC to 1,100Hz and vibration amplitude of the resolution was $20{\mu}m$. Therefore, the proposed non-contact inductive sensor module for precision vibration detection sensor is estimated to have sufficient performance.

• Wind and Structures
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• v.24 no.4
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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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.