• Journal of Korean Association for Spatial Structures
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• v.6 no.3 s.21
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• pp.35-41
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• 2006

Various monitoring sensors have been used for the monitoring, damage and vibration prediction of structures. They have been used for sensing damage in a variety of materials and structures such as piezoelectric materials (PZT) and electric strain gauges. But, many experiments of vibration were not performed. The PZT changes physical force if load cell to electrical signal due to deformation of structure. The voltage change of piezoelectric sensors for plates are used for vibration prediction. In this study, a fundamental study for vibration prediction using piezoelectric sensors are discussed in plates.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.219-224
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• 2005

Vibration response of the tower structure of a 750kW wind turbine (W/T) generator is investigated by measurement and analysis. Acceleration response of the W/T tower under various operation condition is monitored in real time by the vibration monitoring system using LabVIEW. Resonance state of the tower structure is diagnosed in the operating speed range. Resonance frequency range of the test model is investigated with the wind speed data of the test site. To predict the tower resonance frequency, tower is modeled as an equivalent beam with a lumped mass and Rayleigh energy method is applied. Calculated tower bending frequency is in good agreement with the measured value and the result shows that the simplified model can be used in the design stage of the W/T tower.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1067-1072
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• 2001

In this study, the vibration diagnosis program for onboard machinery has been developed. The developed program includes signal monitoring module, system diagnosis module, and system modification module. The signal monitoring module is to monitor the vibration signal in time and frequency domains. And the system diagnosis module, which is developed by using Neural Network with error back propagation algorithm, can detect the abnormal symptom indicating the malfunction of the machinery onboard ships. The investigations of the developed system are presented through the experiment using Rotor Kit. Abnormal vibration signals are created by adding additional weight, manually misaligning the shaft, and loosening the bolts.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.429-434
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• 2004

Vibration response of the tower structure of a 750kW wind turbine generator is investigated by measurement and analysis. Acceleration response of the tower under various operation condition is monitored in real time by vibration monitoring system using LabVIEW. Resonance state of the tower structure is diagnosed in the operating speed range. To predict the tower resonance frequency, tower is modeled as an equivalent beam with a lumped mass and Rayleigh energy method is applied. Calculated tower bending frequency is in good agreement with the measured value and the result shows that the simplified model can be used in the design stage of the wind turbine tower.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.100-108
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• 1995

The In-process minitoring of the chatter vibration is necessarily required to an automatic manufacturing system. In this study, we constructed a multi-sensing system using tool dynamoneter, accelerometer and AE(Acoustic Emission) sensor for a more credible detection of chatter vibration. And a new approach using a multiple neural network to extract the features of multi-sensor for the recognition chatter vibration is proposed. With the Back-propagation training process, the neural network memorize and classify the features of multi-sensor signals. As a result, it is shown by multiple neural network that the chatter vibration can be monitored accurately, and it can be widely used in practical unmanned system.

• Explosives and Blasting
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• v.24 no.2
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• pp.83-91
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• 2006

Over the past few decades, blasting vibration has been mainly analysed to understand characteristics of far field vibration in the area comparatively far from blast hole in the respect of proving limit of building damage. However, over the last few years, many works have been carried out to estimate damage within the rock adjacent to a blast hole, especially for the Purpose of over break in tunnel blasting and rock slope stability There are several methods to estimate rock damage, but method of using blast vibration has been mostly used to estimate rock damage. Formerly, to estimate rock damage, method of expecting near field vibration using the characteristics of far field vibration had mainly used but nowadays, it is practically possible to measure near field vibration according to development of monitoring system. A few repels relating to this have been studied aboard, but very little work has been conducted in our country because of difficulty of monitoring and choice of monitoring system. Accordingly, in this Paper, measurements of near field vibration were conducted and wave forms were analyzed and some problems were investigated in measuring system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.4
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• pp.458-464
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• 2008

The structural health monitoring has been gaining more importance in civil engineering areas such as earthquake and wind engineering. The use of health monitoring system can also provide tools for the validation of structural analytical model. However, only few structures such as historical buildings and some important long bridges have been instrumented with structural monitoring system due to high cost of installation, long and complicated installation of system wires. In this paper, the structural monitoring system based on cheap and wireless monitoring system is investigated. The use of advanced technology of micro-electro-mechanical system(MEMS) and wireless communication can reduce system cost and simplify the installation. Further the application of wireless MEMS system can provide enhanced system functionality and due to low noise densities. Identification results are compared to ones using data measured from traditional accelerometers and results indicate that the system identification using wireless MEMS system estimates system parameters accurately.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.839-841
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• 2014

The Nuclear Steam Supply System(NSSS) is designed to provide an integrated approach that includes areas of monitoring relevant to the integrity of the NSSS. LPMS is designed to function as an alarm system by providing sensor channel alarms for the associated subsystems. LPMS is equipped to provide analysis tools for new alarm events, historical events and for historical periodically stored channel data (e.g. waveforms) for most channels. This paper is intended to introduce the diagnosis principle and abnormal symptom of loose parts monitoring system as a monitoring tool in Nuclear Steam Supply System. And also, we are going to introduce signal analysis program in order to perform the actual diagnosis in power plants.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.149-155
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• 1996

Recent researches in the trouble monitoring system of grinding process have emphasized the use of deep knowledge. Such works include the monitoring and diagnostic systems for cylindrical grinding using sensors on chatter vibration and grinding burn during the process. But, since grinding operations are especially related with a lalrge amount of ambique parameters, it is effectively difficult to detect the grinding troubles occuring during the grinding process. In this paper, monitoring system for grinding utilizes the neural networks based on grinding power signatures. The monitoring system of grinding operations, which makes use of PDP neural networks, is presented. Then, the implementation results by computer simulations and experimental data with respect to chatter vibration and grinding burn are compared.