• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.123-137
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• 2014

The aviation gas turbine is composed of many expensive and highly precise parts and operated in high pressure and temperature gas. When breakdown or performance deterioration occurs due to the hostile environment and component degradation, it severely influences the aircraft operation. Recently to minimize this problem the third generation of predictive maintenance known as condition based maintenance has been developed. This method not only monitors the engine condition and diagnoses the engine faults but also gives proper maintenance advice. Therefore it can maximize the availability and minimize the maintenance cost. The advanced gas turbine health monitoring method is classified into model based diagnosis (such as observers, parity equations, parameter estimation and Gas Path Analysis (GPA)) and soft computing diagnosis (such as expert system, fuzzy logic, Neural Networks (NNs) and Genetic Algorithms (GA)). The overview shows an introduction, advantages, and disadvantages of each advanced engine health monitoring method. In addition, some practical gas turbine health monitoring application examples using the GPA methods and the artificial intelligent methods including fuzzy logic, NNs and GA developed by the author are presented.

• Journal of the Korean Institute of Gas
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• v.4 no.3 s.11
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• pp.19-25
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• 2000

In order to prevent secondary disaster such as gas explosion which comes after a devastating magnitude earthquake, the seismic monitoring and transmission system for natural gas governor station was developed. To measure ground motions precisely and operate the seismic monitoring system efficiently, the position and method of accelerometer installation were recommended by the analysis of ground noise patterns of governor station. For making a decision on prompt shut-off of gas supplies in the event of a great earthquake, the real-time calculation algorithm of PGA(Peak Ground Acceleration) and SI(Spectrum Intensity) were developed and it has been implemented in the seismic monitoring and transmission system.

• 한국가스학회:학술대회논문집
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• 2004.11a
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• pp.71-77
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• 2004

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.129-134
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• 2024

This study aims to talk about the necessity of solving the PFC gas emission problem raised by the recent development of the semiconductor industry and the remote plasma source method monitoring system used in the semiconductor industry. The 'monitoring system' means that the researchers applied machine learning to the existing monitoring technology and modeled it. In the process of this study, Residual Gas Analyzer monitoring technology and linear regression model were used. Through this model, the researchers identified emissions of at least 12700mg CO2 to 75800mg CO2 with values ranging from ion current 0.6A to 1.7A, and expect that the 'monitoring system' will contribute to the effective calculation of greenhouse gas emissions in the semiconductor industry in the future.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.352-356
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• 2018

This paper relates to a technology for monitoring a liquefied gas storage tank in the special gas field where demand is increasing owing to the continuous growth of related fields such as the semiconductor, display, and ICT convergence electronics industries. We have proposed a system for real - time monitoring using wireless sensor network technology, and implemented a system consisting of a sensor unit, transmitter module, and receiver module to be attached to a liquefied gas storage tank. The system was applied to LCO2 tanks among various liquefied gas storage tanks to verify the feasibility. The storage tanks employed in the experiments has capacities of 16,179 l and was 1,920 mm in inner diameter. Furthermore, the density was 1.03 g/l. The measured data were compared with reference data on the remaining gas level versus the $CO_2$ height of the surface, expressed using a conventional water meter, provided by an existing storage tank supplier. The experimental results show that the data is similar to the standard data provided by the tank supplier, and has a high accuracy and reliability within an error range of 0.03%.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1727-1731
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• 2004

We propose an ART2 neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, fault classifier by ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters is used for fault isolation. The performances of the proposed fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.369-376
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• 2018

This paper presents an android-based implementation of real-time remote monitoring system for industrial gas turbines. The use of remote monitoring techniques can be beneficial in terms of not only the reduction of monitoring cost but also the earlier detection of abnormal status. In order to achieve the ability of protecting sensitive information from unauthorized persons, the proposed system supports secure transmissions using the RSA(Rivest Shamir Adleman) algorithm. In the event of abnormal situation on the gas turbine, the remote monitoring system generates an alarm to attract the user's attention by exploiting a push-message technique. The proposed system has been verified through a series of experiments with an experimental setup including a virtual data generator.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.1
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• pp.67-76
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• 2007

Bioventing is commonly used for petroleum hydrocarbon (PHC) spills. This process provides better subsurface oxygenation, thus stimulating degradation by indigenous microorganisms. Therefore soil vapor monitoring points (VMPs) are extremely important in determining the potential effectiveness of bioventing and in long-term monitoring of bioventing progress. In this study in-situ soil gas monitoring well (GMW) was developed and presented the pilot test results which recover the contaminated site by bioventing method. The result of application was successful and it was expected that GMW developed could be applied to the evaluation procedure of bioventing effectiveness and long-term remediation potential.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.27-31
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• 2021

VI probe, which is one of various in-situ plasma monitoring sensor, is frequently used for in-situ process monitoring in mass production environment. In this paper, we correlated the plasma etch results with VI probe data with the small amount of gas flow rate changes to propose usefulness of the VI probe in real-time process monitoring. Several different sized contact holes were employed for the etch experiment, and the etched profiles were measured by scanning electron microscope (SEM). Although the shape of etched hole did not show satisfactory relationship with VI probe data, the chamber status changed along the incremental/decremental modification of the amount of gas flow was successfully observed in terms of impedance monitoring.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.247-253
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• 2015

The components of an aero-engine gas path cannot be monitored in a timely way due to a lack of real-time monitoring technologies. As an attempt to address this problem, we have conducted research on a condition monitoring technology based on the charging characteristics of particles in an aero-engine gas path, and emphatically analyze the formation of particles in an aero-engine gas path, the charging mechanism of carbon particles and the factors that influence the charge quantity and polarity. The verification experiments are performed on the simulated experiment platform and a turbo-shaft engine test bench. The results show the carbon particles' carry charge, and an obvious change in the total electrostatic charge level in the aero-engine gas path due to the increased carbon particles produced by burning or abnormal metal particles; the charge number is related to the size of particles, and the bigger carbon particles carry a negative charge and metal particles carry a positive charge; the change in engine power can lead to an obvious change in the level of electrostatic charge in the gas path, and the change in electrostatic charge results from the extra carbon particles formed in the rich-oil burning process. The research provides a reference for establishing the baseline of electrostatic charge while the engine runs on different power. The study also demonstrates the validity of the electrostatic monitoring technology and establishes a base for developing the application of electrostatic monitoring technology in aero-engines.