• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.263-269
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• 2012

Condition-based maintenance (CBM) has been used as a useful concept for optimizing maintenance plan and decreasing maintenance cost in several kinds of plant sites. This study introduced an example that developed an integrated management system for maintenance parameters and hydraulic turbine of hydro-power plant in order to improve its maintenance system as applying CBM techinique. The integrated management system consists of three parts. One is a hardware part including PDA inspection system and several kind of precision measuring instruments. Another is a vibration monitoring system on hydraulic turbine. The other is a software part that takes charge of making hierarchy tree of maintenance parameters and their inspection route, managing accumulated database, assessing health condition of components, and supporting interface with other enterprise management system. The system has been installed at Chuncheon Hydro-power plant for test and demonstration. It is expected that the system can contribute database construction for diagnostics and prognostics on facility health condition and systematic accumulation of know-how on operation and maintenance of plant.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.6
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• pp.574-581
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• 2012

Condition-based maintenance(CBM) has been used as a useful concept for optimizing maintenance plan and decreasing maintenance cost in several kinds of plant sites. This study introduced an example that developed an integrated management system for maintenance parameters and hydraulic turbine of hydro-power plant in order to improve its maintenance strategy as applying CBM techinique. The integrated management system consists of three parts. One is a hardware part including PDA inspection system and several kind of precision measuring instruments. Another is a vibration monitoring system on hydraulic turbine. The other is a software part that takes charge of making hierarchy tree of maintenance parameters and their inspection route, managing accumulated database, assessing health condition of components, and supporting interface with other enterprise management system. The system has been installed at Chuncheon hydro-power plant for test and demonstration. It is expected that the system can contribute database construction for diagnostics and prognostics on facility health condition and systematic accumulation of know-how on operation and maintenance of plant.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.230-233
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• 2016

In this paper, we developed the ice machine conditions monitoring system that confirms conditions of the ice machine. The developed system is composed of Communication Board, Server Program, and Web-based User Application. Communication Board which is connected to the ice machine periodically sends various data, such as current, voltage, the refrigerant pressure and temperature, the external temperature and humidity. Server Program stores the data received from Communication Board into database. The manager or the ice machine operator can see the state of the own machine through User Application based on Web. When a symptom is detected on the ice machine, the manager and the operator can checks the current condition of the ice machine by using the data obtained in real time and also prevents the machine troubles by taking proper actions.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.178-186
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• 2009

Most of automotive plastic parts are injection molding products. Inspection of total product is impossible, because number of product to inspect is too many and various. Condition-based Monitoring was proposed to decrease cost and time for inspecting. In this research, a system that predicts quality of part at fabrication point of time, and confirms informations through the internet was developed. Cavity sensors were installed inside of mold, and gathered signals as measuring, and through this process Sensor-based Monitoring system can be observed manufacturing of a part. Monitoring system transmits signals to client through the internet, and finally developed system provides manufacturing informations and predictions of quality as web-based monitoring.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1076-1077
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• 2007

CMS(Condition Monitoring System) is a useful tool to predict the defect of machine condition, for example, Motor, Bearing, Gear, Fan, etc. And, recently CMS is very important on plant. In this paper, describe the bearing electric arcing with example.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.523-529
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• 2009

Smart sensor is known as intelligent sensor, it is different with other conventional sensors in the case of intelligent system embedded on it. Smart sensor has many benefits e.g. low-cost in usage, self-decision and self-diagnosis abilities. This sensor consists of perception element(sensing element), signal processing and technology of communication. In this work, a bridge and structure of smart sensor has been investigated to be capable to condition monitoring routine. This investigation involves low power consumption, software programming, fast data acquisition ability, and authoritativeness warranty. Moreover, this work also develops smart sensor to be capable to perform high sampling rate, high resolution of ADC, high memory capacity, and good communication for data transfer. The result shows that the developed smart sensor is promising to be applied to various industrial fields.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.243-245
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• 2005

Condition monitoring is desirable for increasing machinery availability, reducing consequential damage, and improving operational efficiency. In this paper, a model-based method using neural network modeling of induction noter in vibration spectra is proposed for machine fault detection and diagnosis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals to continuous spectra so that the neural network model can be trained with vibration spectra. And the faults are detected from changes in the expectation of vibration spectra modeling error. The effectiveness of the proposed method is demonstrated through experimental results.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.10a
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• pp.36-39
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• 2000

This paper presents the technology of condition diagnosis & life estimation on insulation system of the traction motor. In the non-destructive methods for diagnosis of coil insulation state, residual dielectric strength is estimated by the D-map which consist of the partial discharge quantity Q and average degradation degree $\Delta$. In the operating history of machine, the N-Y life estimation method is based on the stop-starting numbers and operating times with considering each degradation factor by the thermal, electrical and heat-cycle stress. With the on-line conditioning monitoring on the currents of traction motors, detecting the abnormal operating state due to bearing faults, stator or armature faults, eccentricity related faults and broken rotor bars can be performed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.161-167
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• 2020

In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.78-82
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• 2001

Electronic Weighting Machine is used an electronic scale which has many trouble because of broken load cells. In this paper, we propose an intelligent Diagnosis System will for an electronic weighting machine using fuzzy logic. It's purpose be detect of the load cell's trouble. The electronic circuit of system, which call 'junction box', will be connected resistances in a series at circuit of Wheatstone Bridge for monitoring the condition of load cells.