• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.472-477
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• 2017

Oil spills cause a lot of damage to the environment. Oil destroys the water environment and ecosystem in a very short period of time once they are contaminated by it, it takes a lot of time to recover from the contamination and the cleaning process is very difficult. Therefore, oil detectors are greatly needed as they can monitor any oil spills over the sea, rivers, and lakes. There are two kinds of technology available for detecting oil, viz. the contact and non-contact types. The former is based on the use of the conductivity, capacitance and microwaves, while the latter employs infrared, UV, laser, optic and radar technologies. As there are also various hurdles in the measuring of oil on water, such as the presence of waves, refraction of light, temperature and saltiness, it is imperative to select the right oil detector which is appropriate for the specific environment. In this study, a contact type oil detector is developed, which can be used in oil related industries, such as refineries, petrochemical companies, and power generation stations. The detector is made up of the sensor module, which floats on the water, and the controller which processes the signal coming from the sensor module and displays it. It is designed in such a way that the existence of oil is detected through the sensor and the change in the permittivity is observed to determine the volume and type of spilled oil.

• The KSFM Journal of Fluid Machinery
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• v.7 no.2 s.23
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• pp.41-49
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• 2004

Condition monitoring is very important in turbo machinery because single failure could cause critical damages to its plant. So, automatic fault recognition has been one of the main research topics in condition monitoring area. We have used a relatively new fault recognition method, Hidden Markov Model(HMM), for mechanical system. It has been widely used in speech recognition, however, its application to fault recognition of mechanical signal has been very limited despite its good potential. In this paper, discrete HMM(DHMM) was used to recognize the faults of rotor system to study its fault recognition ability. We set up a rotor kit under unbalance and oil whirl conditions and sampled vibration signals of two failure conditions. DHMMS of each failure condition were trained using sampled signals. Next, we changed the setup and the rotating speed of the rotor kit. We sampled vibration signals and each DHMM was applied to these sampled data. It was found that DHMMs trained by data of one rotating speed have shown good fault recognition ability in spite of lack of training data, but DHMMs trained by data of four different rotating speeds have shown better robustness.

• Journal of Sensor Science and Technology
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• v.31 no.4
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• pp.266-270
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• 2022

Owing to the rising volume of seaborne trade, oil spills damage the marine environment for over 250 yearly. Thus, various analysis methods such as the Fourier-transform infrared (FTIR), Raman spectroscope, and gas chromatography are used to monitor oil spills at sea, but these methods are expensive. Recently, to reduce operational costs, an underwater fluorometer was adopted. However, this approach is not ideal for the remote sensing of oil spills because the device gets submerged in the sea. In this study, we have designed and developed a monitoring system that uses ultraviolet fluorescence to detect spilled oil or water from a distance, as well as proposed an analyzing method defining based on water Raman signal and QF535. Each fluorescence spectrum of water, oil (crude oil), and Bunker A was obtained using the system, and was calculated and analyzed from the spectrum individually. Based on the results of the analysis, we could successfully identity water and oil at a long distance.

• Environmental engineer
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• v.25 s.258
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• pp.14-19
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• 2008

• Environmental engineer
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• v.25 s.259
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• pp.14-19
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• 2008

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.10
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• pp.101-106
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• 2013

This paper proposes the new high precision monitoring sensor for the Marine Installation. Among variety of sensor network systems, wireless information transmission through the marine is one of the enabling technologies for the development of future marine-observation systems and sensor networks. Applications of marine monitoring range from oil industry to aquaculture, and include instrument monitoring, pollution control, climate recording, prediction of natural disturbances. For these marine applications to be available, however, the provision of precise location information using monitoring sensor is essential. In this paper, the dynamic characteristics for obtaining the location information of monitoring sensor is analyzed. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably excellent performance for the Monitoring for the Marine Installation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.147-152
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• 2016

This paper proposes a new TPC (Transmission Priority Change) algorithm which is used to diagnose failures of a CAN (Controller Area Network) based network system for the oil tank monitoring. The TPC algorithm is aimed to increase the total amount of data transmission and to minimize the latency for an urgent message by changing transmission priority. The urgency of the data transmission has been determined by the conditions of sensors. There are multiple sensors inside of the oil tank, such as temperature, valve, pressure and level sensors. When the sensors operate normally, the sensory data can be collected through the CAN network by the monitoring system. However when there is a dangerous situation or failure situation happened at a sensor, the data need to be handled quickly by the monitoring system, which is implemented by using the TPC algorithm. The effectiveness of the TPC algorithm has been verified by the real experiments. In addition, this paper introduces a method that people can figure out the condition of oil tanks and also can perform the fault diagnosis in real-time by using transmitted packet data. By applying this TPC algorithm to various industries, the convenience and reliability of multiple sensors network system can be improved.

• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.4
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• pp.61-69
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• 2001

Recently, according to the rapid development of computer and electronic technology, most crude oil carriers adopt automated cargo handling system. But an excessive automation makes system so complicate that it could increase the Possibility of accidents due to human error. Although a cargo handling process is done by an expert, the potential of accidents by human factor lies through the whole cargo handling procedure and the current automated system lacks of the functionality to prevent a mis-operation and diagnose the abnormal status of the system. Because the oil concerned accident could be almost a disaster, the primary goal of system development should not be a fully automated system but be a perfectly safe system. This paper deals with the analysis and design of an expert system which can provide mariner with the operational guidance and the facility of crisis management by monitoring system's abnormal condition and human's mis-operation.

• Fisheries and Aquatic Sciences
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• v.18 no.1
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• pp.27-33
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• 2015

Seasoned laver Pyropia spp. is one of the most well-known Korean traditional seafoods, and is becoming more popular worldwide. Various mixed oils are used in the preparation of seasoned laver; however, there is no information available regarding the effects of the blending ratio of oils on the quality of seasoned laver. In this study, the effects of the blending ratio of corn, sesame, and perilla oils on the oxidation and sensory quality of seasoned laver were monitored and optimized using a response surface methodology. An increase in the proportion of corn and sesame oils resulted in an excellent oxidation induction time, whereas a high ratio of perilla oil reduced the thermal oxidative stability of the mixed oil. In the sensory test, the seasoned laver with the highest proportion of sesame oil was preferred. The optimal blending ratio (v/v) of corn, sesame, and perilla oils for both oxidation induction time ($Y_1$) and sensory score ($Y_2$) was 92.3, 6.0, and 1.7%. Under optimal conditions, the experimental values of $Y_1$ and $Y_2$ were $4.41{\pm}0.3h$ and $5.58{\pm}0.8$points, and were similar to the predicted values (4.34 h and 5.13 points). Our results for the monitoring and optimization of the blending ratio provide useful information for seasoned laver processing companies.

• Tribology and Lubricants
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• v.38 no.4
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• pp.143-151
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• 2022

This study analyzes patents related to oil diagnosis of construction equipment. Oil diagnosis is extremely important for maintaining construction equipment properly. Through the evaluation of existing patents, a patent strategy for the future construction equipment market is presented. The related patents are classified and selected in several steps. Finally, 16 valid patents are selected and analyzed in detail. In the classification process, patents are classified by country, year, and company. A market analysis shows that the top 10 companies have a market share of more than 50. In addition to patents related to the oil analysis of construction equipment, patents related to automobile oil analysis and development of oil sensors are investigated to identify the contents of patents in other fields that can be applied to oil diagnosis technology for construction equipment. Moreover, not only the contents of research articles of two Korean construction companies, but also the research trends in the literature in this field are used in the analysis. The related patents of the two Korean companies are few. Companies with a high market share, including Caterpillar, hold many patents, and patents for diagnosis algorithms using such technologies as artificial intelligence and artificial neural networks, along with oil sensor-based condition monitoring technology, are gradually expanding.