• Journal of Advanced Marine Engineering and Technology
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• v.30 no.2
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• pp.247-252
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• 2006

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.135-145
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• 2009

The main goal of construction projects from the past has been enhancing efficiency by reducing cost and time. but, seeing the current condition of safety management of many construction companies nowadays, it is true that not much attention has been paid to safety management for a long time. However, there are paradigm shift from the cost and term of works to safety management in the construction industry, from this circumstance the safety management is evaluated more importantly. Though less accident happens compared to past, the accidents are getting greater because construction projects nowadays are bigger and more complex and monetary loss from the accidents are increasing. Also, the severity is getting greater and even fatal. For this reason, more improved safety management is very necessary. Therefore, we are to propose more efficient system for safety management in this thesis. Technical parts for developing system include many technique such as Real Time Locating system, and other techniques like Monitoring module based on BIM, Data Mart, Alarm are also applied together. Through this system, in the construction site, safety management is performed more effectively and widely because the system can manage the human resource and fluid situation. Also, safety manager can conduct more systematically and advanced safety management through human resource dominated safety management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4600-4616
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• 2021

In cognitive radio networks where unlicensed secondary users opportunistically access to licensed spectrum unused by licensed primary users, spectrum sensing is one of the key issues in order to effectively use the frequency resource. For enhancing the sensing performance in energy detection-based spectrum sensing, spatial diversity based on multiple antennas is utilized. However, the sensing performance can be degraded when antennas are spatially correlated, resulting in inducing the harmful interference to primary users. To overcome this problem, in this paper, an advanced energy detector is proposed. In the proposed sensing method, a weight matrix based on the eigenvalues of the spatial channels without any prior information on the primary signals is defined and utilized. In numerical simulations, it is shown that the proposed detector outperforms the conventional detector with regard to false-alarm and detection probabilities when antenna are spatially correlated.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.107-115
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• 2013

Objective: The aim of this study is to identify the training requirements of new nuclear power plant by a comprehensive literature review. Background: The design of instrumental and control systems for New NPP is applied fully digitalized systems. For example, soft-control, large display panels(LDP), and an advanced alarm system were applied to the APR-1400 or SMART. Method: The NUREG-0711 and international guideline of training program was analyzed from the following four phases of SAT(Systemic Approach to Training): Analysis, Design, Development, Implementation and Evaluation. Results: To identify the requirement of training program, 'Feedback' phase was considered and each phase of SAT was classified. Conclusion: A more systematic requirement of training program is needed which considers the computerized system was applied to the new NPP. Application: The results of the publishing can be useful for standardization of the systematic training program for the operators of NPP.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.953-958
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• 2015

Raspberry Pi is a credit card-sized computer with support for a large number of input and output peripherals. This makes it the perfect platform for interaction with many different devices and for usage in a wide range of applications. When combined with Wi-Fi, it can communicate remotely, therefore increasing its suitability for the construction of wireless sensor nodes. In addition, data processing and decision-making can be based on artificial intelligence, what is performed in developed testbed on the example of monitoring and determining the confidence of fire. In this paper, we demonstrated the usage of Raspberry Pi as a sensor web node for fire-safety monitoring in a building. When the UV-flame sensors detect a flame as thin as that of a candle, the Raspberry Pi sends a push-message to notify the assigned smartphone of the on-site situation through the GCM server. A mobile app was developed to provide a real-time video streaming service in order to determine a false alarm. If an emergency occurs, one can immediately call for help.

• Journal of Ocean Engineering and Technology
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• v.35 no.1
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• pp.91-97
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• 2021

Marine accidents caused by ships have brought about economic and social losses as well as human casualties. Most of these accidents are caused by small and medium-sized ships and are due to their poor conditions and insufficient equipment compared with larger vessels. Measures are quickly needed to improve the conditions. This paper discusses a video-integrated collision prediction and fall detection system to support the safe navigation of small- and medium-sized ships. The system predicts the collision of ships and detects falls by crew members using the CCTV, displays the analyzed integrated information using automatic identification system (AIS) messages, and provides alerts for the risks identified. The design consists of an object recognition algorithm, interface module, integrated display module, collision prediction and fall detection module, and an alarm management module. For the basic research, we implemented a deep learning algorithm to recognize the ship and crew from images, and an interface module to manage messages from AIS. To verify the implemented algorithm, we conducted tests using 120 images. Object recognition performance is calculated as mAP by comparing the pre-defined object with the object recognized through the algorithms. As results, the object recognition performance of the ship and the crew were approximately 50.44 mAP and 46.76 mAP each. The interface module showed that messages from the installed AIS were accurately converted according to the international standard. Therefore, we implemented an object recognition algorithm and interface module in the designed collision prediction and fall detection system and validated their usability with testing.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.197-202
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• 2023

This paper presents the design method and electrical characteristics of a high-efficiency power amplifier for a 50 Watts class repeater applied to a 5G system and used in in-building, subway, and tunnel. GaN was used for the termination transistor of the power amplifier designed here, and intermodulation signals were removed using DPD to satisfy linearity. In addition, in order to handle various requirements such as amplifier gain control and alarm processing required in the 5G system, the microprocessor is designed to exist inside the power amplifier. The amplifier manufactured to confirm the electrical performance of the power amplifier satisfying these conditions satisfied 46.5 dBm and the overall efficiency of the amplifier was 37%, and it was confirmed that it satisfied various alarm conditions and electrical characteristics required by telecommunication companies.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.98-103
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• 2007

Long term Electrocardiogram (ECG) [1] analysis plays a key role in heart disease analysis. A combined detection of QRS-complex and P-wave in ECG signal for ubiquitous healthcare system was designed and implemented which can be used as an advanced warning device. The ECG features are used to detect life-threating arrhythmias, with an emphasis on the software for analyzing QRS complex and P-wave in wireless ECG signals at server after receiving data from base station. Based on abnormal ECG activity, the server will transfer alarm conditions to a doctor's Personal Digital Assistant (PDA). Doctor can diagnose the patients who have survived from cardiac arrhythmia diseases.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.7-11
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• 2007

The aim of this paper is to design and implement a new ECG signal monitoring and analysis method for the home care of elderly persons or patients, using wireless sensor network (WSN) technology. The wireless technology for home-care purpose gives new possibilities for monitoring of vital parameter with wearable biomedical sensors and will give the patient freedom to be mobile and still be under continuously monitoring. Developed platform for portable real-time analysis of ECG signals can be used as an advanced diagnosis and alarming system. The ECG features are used to detect life-threatening arrhythmias, with an emphasis on the software for analyzing the P-wave, QRS complex, and T-wave in ECG signals at server after receiving data from base station. Based on abnormal ECG activity, the server transfer diagnostic results and alarm conditions to a doctor's PDA. Doctor can diagnose the patients who have survived from arrhythmia diseases.