• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.92-95
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• 2019

Automation control and the data for control of industrial equipment for the diagnosis and prediction is a key to success in the 4th industrial revolution. It increases process efficiency and productivity through data collection, realtime monitoring, and the data analysis. However, university and research environment are still suffering from logging the data in manual way, and we occasionally loss the equipment data logging due to the lack of automatic data logging system. State variable presents the current condition of the equipment operation which is closely related to process result, and it is valuable to monitor and analyze the data for the equipment health monitoring. In this paper, we demonstrate the collection of equipment state variable data via programmable logic controller (PLC) and the visualization of the collected data over the Web access supervisory control and data acquisition (SCADA). Test vehicle for the implementation of the suggested SCADA system is a relay switched physical vapor deposition system in the university environment.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.343-346
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• 2008

To improve the reliability and extend the life for a wind-turbine gearbox, the gearbox needs to be monitored and analysed exactly. This study was conducted to analyze and detect the gearbox conditions when lubricating oil contaminated by wear particles was used. Characteristics of the gearbox failure by wear particles were monitored simultaneously by the on-line measurement sensor of vibration, oil condition and temperature. For the detail vibration analyses, frequency analysis(FFT) was performed. The results of the study were summarized as follows: Vibrational signal was found sensitive to abnormal changes of the gearbox conditions when lubricant was contaminated by wear particles. Also, using frequency analysis for the harmonics of gear mesh frequency(GMF), it is found that the failure of gearbox was caused by the damages of meshing gears. However, temperature and oil condition measuring signals were found not so effective to detect any gearbox failure by oil contamination.

• International Journal of Fluid Machinery and Systems
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• v.5 no.4
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• pp.143-151
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• 2012

Predicting the future condition of machine and assessing the remaining useful life are the center of prognostics. This paper contributes a new prognostic method based on grey model and survival probability. The first step of the method is building a normal condition model then determining the error indicator. In the second step, the survival probability value is obtained based on the error indicator. Finally, grey model coupled with one-step-ahead forecasting technique are employed in the last step. This work has developed a modified grey model in order to improve the accuracy of prediction. For evaluating the proposed method, real trending data of low methane compressor acquired from condition monitoring routine were employed.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.6
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• pp.324-329
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• 2004

Six stator slot couplers(SSC) and a flux probe sensor installed on the stator winding slots of large turbine generator. Assessment of insulation condition has been based upon the measurements of partial discharge(PD) of stator windings and shorted-turn of rotor windings in operating large turbine generator. The maximum PD magnitude(Qm), normalized quantify number(NQN), PD pattern and shorted-turn were measured using on-line insulation condition monitoring system. The NQN and Qm of slot PD side in the phase A are indicated the highest value in six SSC sensors. Monitoring system results showed that discharge at conductor surface and internal discharge were detected at the surface of stator winding and in voids of the groundwall insulation. Insulation of stator and rotor windings in large turbine generator was judged to be in good condition.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.500-501
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• 2007

Automation systems for higher performance and efficiency in railway electrification systems are driving ever more demanding needs for new condition monitering systems which can consist of sensors connected to the substation and catenary systems. This paper reviews the recently developed condition monitering system, based on a IP network-based multi-agent system, wireless communications and sensor networks for railway electrification system. A new concept for information management, condition monitoring and control of power transmission are considered as railway automation in electrification system.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.64-70
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results. it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Corrosion Science and Technology
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• v.15 no.6
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• pp.271-280
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• 2016

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipeline to 100 years is the application of health monitoring and life prediction tools that are able to provide both long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step is the enhancement of technological capabilities that are required for understanding and quantifying the effects of key factors influencing buried steel pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors and electrochemical cells for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating cracking and disbondment, cathodic shielding, transit loss of cathodic protection.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.37-37
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• 2003

Rice is one of the most important crop in the world and is a major export of Thailand. Optical sensors are not useful for rice monitoring, because most cultivated areas are often obscured by cloud during the growing period, especially in South East Asia. Spaceborne Synthetic Aperture Radar (SAR) such as RADARSAT, can see through regardless of weather condition which make it possible to monitor rice growth and to retrieve rice acreage, using the unique temporal signature of rice fields. This paper presents the result of a study of examining the backscatter behavior of rice using multi-temporal RADARSAT dataset. Ground measurements of paddy parameters and water and soil condition were collected. The ground truth information was also used to identify mature rice crops, orchard, road, residence, and aquaculture ponds. Land use class distributions from the RADARSAT image were analyzed. Comparison of the mean DB of each land use class indicated significant differences. Schematic representation of temporal backscatter of rice crop were plotted. Based on the study carried out in Pathum Thani Province test site, the results showed variation of sigma naught from first tillering vegatative phase until ripenning phase. It is suggested that at least, three radar data acquisitions taken at 3 stages of rice growth circle namely; those are at the beginning of rice growth when the field is still covered with water, in the ear differentiation period, and at the beginning of the harvest season, are required for rice monitoring. This pilot project was an experimental one aiming at future operational rice monitoring and potential yield predicttion.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.84-88
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results, it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.2
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• pp.121-125
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• 2010

The infrared thermography technology rather than traditional nondestructive methods has benefits with non-contact and non-destructive testings in measuring for the fault diagnosis of the rotating machine. In this work, condition monitoring measurements using this advantage of thermography were proposed. From this study, the novel approach for the damage detection of a rotating machine was conducted based on the spectrum analysis. As results, by adopting the ball bearing used in the rotating machine applied extensively, an spectrum analysis with thermal imaging experiment was performed. Also, as analysing the temperature characteristics obtained from the infrared thermography for in-situ rotating ball bearing under the lubrication condition, it was concluded that infrared thermography for condition monitoring in the rotating machine at real time could be utilized in many industrial fields.