• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1362-1376
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• 2016

A cloud computing system can be characterized by the provision of resources in the form of services to third parties on a leased, usage-based basis, as well as the private infrastructures maintained and utilized by individual organizations. To attain the desired reliability and energy efficiency in a cloud data center, trade-offs need to be carried out between system performance and power consumption. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. The work presented in this paper is directed towards the development of an Energy-efficient and Performance-aware Cloud System equipped with strategies for dynamic switching of optimization approach. Moreover, a platform is also provided for the deployment of a Wind Farm CMS (Condition Monitoring System) which allows ubiquitous access. Due to the geographically-dispersed nature of wind farms, the CMS can take advantage of the cloud's highly scalable architecture in order to keep a reliable and efficient operation capable of handling multiple simultaneous users and huge amount of monitoring data. Using the proposed cloud architecture, a Wind Farm CMS is deployed in a virtual platform to monitor and evaluate the aging conditions of the turbine's major components in concurrent, yet isolated working environments.

• 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.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.395-399
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• 2007

Renewable energy sources such as wind energy is copiously available without any limitation. Wind turbines are used to tap the potential of wind energy which is available in millions of megawatt. Reliability of wind turbine is critical to extract this maximum amount of energy from the wind. We reviewed different techniques, methodologies, and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns. To keep the wind turbine in operation, implementation of Condition Monitoring System (CMS) is paramount, and for this purpose ample knowledge of these types of system is mandatory. So, an attempt has been made in this direction to review maximum approaches related to CMS in this piece of writing.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.96-101
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• 2014

Wind power is the fastest growing renewable energy source in the world and it is expected to remain so for some times. Recently, there is a constant need for the reduction of Operational and Maintenance(O&M) costs of Wind Energy Conversion Systems(WECS). The most efficient way of reducing O&M cost would be to utilize CMS(Condition Monitoring System) of WECS. CMS allows for early detection of the deterioration of the wind generator's health, facilitating a proactive action, minimizing downtime, and finally maximizing productivity. There are two types of faults such as mass unbalance and aerodynamic asymmetry which are related to wind turbine's rotor faults. Generally, these faults tend to generate various vibrations. Therefore, in this work a simple fault detection algorithm based on spectrums of vibration signals and simple max-min decision logic is proposed. Furthermore, in order to verify its feasibility, several simulation studies are carried out by using GH-bladed software.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.5
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• pp.362-368
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• 2014

Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the musle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.675-680
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around the world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance. CMS(Condition Monitoring System) can be used to aid plant operator in achieving these goals. Its aim is to provide operators with information regarding th e health of their machine, which in turn, can help them improve operation efficiency. In this work, wind turbine fault diagnostic algorithm which can diagnose the mass unbalance and aerodynamic asymmetry of the blades is proposed. Proposed diagnostic algorithm utilizes both FFT(Fast Feurier Transform) of the signal from accelerometers installed inside of nacelle and simple diagnostic logic. Furthermore, to verify the applicability of the proposed system, 3W small sized wind turbine system is tested and physical experiments are carried out.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.1059-1060
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• 2009

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.191-197
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• 2008

This research focused on the development of wireless telemetry system that can monitor heart rates of multiple rehabilitation patients in real time without constraint. The whole system consists of the multiple patient's side devices (PSDs) and one central monitoring system (CMS). The PSD consists of a microphone, amplifier, filter, microcontroller, and RF (Radio Frequency) modem. In addition, the PSD was designed to be wearable and low power consumption. The CMS consists of an RF modem and general PC and it was designed to monitor heart rates from multiple patients simultaneously. The system warns an alarm signal when a patient's heart rate exceeds the pre-set range for each patient. This system can be useful to monitor the heart rate of exercising rehabilitation patients and control the patients condition and the exercising level.

• The Journal of the Acoustical Society of Korea
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• v.35 no.3
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• pp.192-201
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• 2016

Condition Monitoring System (CMS) has been used to detect unexpected faults of wind turbine caused by the abrupt change of circumstances or the aging of its mechanical part. In fact, it is a very hard work to do regular inspection for its maintenance because wind turbine is located on the mountaintop or sea. The purpose of this study is to find out distribution patterns of vibration signals measured from the main mechanical parts of wind turbine according to its operation condition. To this end, acceleration signals of main bearing, gearbox, generator, wind speed, rotational speed, etc were measured through the long period more than 2 years and trend analyses on each signal were conducted as a function of the rotational speed. In addition, correlation analysis among the signals was done to grasp the relation between mechanical parts. As a result, the vibrations were dependent on the rotational speed of main shaft and whether power was generated or not, and their distributions at a specific rotational speed could be approximated to Weibull distribution. It was also investigated that the vibration at main bearing was correlated with vibration at gearbox each other, whereas vibration at generator should be dealt with individually because of generating mechanism. These results can be used for improving performance of CMS that early detects the mechanical abnormality of wind turbine.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.27-33
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• 2013

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.