• The Journal of Bigdata
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• v.7 no.1
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• pp.125-137
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• 2022

The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.151-159
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• 2007

It is very important to collect all production-related status values during the manufacturing process of semiconductor. The analysis results of the collected data can be used for the operation rate, fault diagnosis, process control and removal of predicted obstacles of equipments, eventually contributing to the improvement of production efficiency. For this propose. many IC makers have adopted EES(Equipment Engineering System). As the use of web has become a daily lift activity lately, it has been suggested to expand the scope of monitoring equipments using HTTP or SOAP protocols. To fulfill the web-based EES, EDA(Equipment Data Aquisition) should be facilitated first by integrating and standardizing various forms of messages generated from many different semiconductor equipments. In this paper, a method for integration between different types of information is suggested based on the analysis of various protocols used for the communication between semiconductor equipments. In addition, a software architecture to support the method is desisted.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2945-2965
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• 2023

The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.447-454
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• 2013

A model-based method is proposed to diagnose the gear crack in the gearbox under variable loading condition with the objective to apply it to the wind turbine CMS(Condition Monitoring System). A simple test bed is installed to illustrate the approach, which consists of motors and a pair of spur gears. A crack is imbedded at the tooth root of a gear. Tachometer-based order analysis, being independent on the shaft speed, is employed as a signal processing technique to identify the crack through the impulsive change and the kurtosis. Lumped parameter dynamic model is used to simulate the operation of the test bed. In the model, the parameter related with the crack is inversely estimated by minimizing the difference between the simulated and measured features. In order to illustrate the validation of the method, a simulated signal with a specified parameter is virtually generated from the model, assuming it as the measured signal. Then the parameter is inversely estimated based on the proposed method. The result agrees with the previously specified parameter value, which verifies that the algorithm works successfully. Application to the real crack in the test bed will be addressed in the next study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.613-622
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• 2015

The convergence of IT technology and marine facilities monitoring system is needed for effective monitoring systems to marine facilities. Especially the spread of smart device such as smart phone, smart pad, smart TV provide an environment that can check the status of the marine facility for marin facilities manager. However, smart phones and smart pads are used in a variety of OS used. Thus the monitoring system of the various service environments is difficult. In addition, There is inconvenience that must individually developed monitoring system for each device. In order to solve this problem NMMS (N-Screen Marine-facility Monitoring System) is proposed. NMMS is consist of Real-time monitoring system, Fault diagnosis system, Data storage system. To improve variety of smart devices accessibility, we use HTML 5. Through NMMS, marine facilities manager can use smart device such as PC, Notebook, smart phone, smart pad for marine facilities monitoring.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.128-139
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• 2017

Railway is one of the public transportation systems along with shipping and aviation. With the recent introduction of high speed train, its proportion is increasing rapidly, which results in the higher risk of catastrophic failures. The wheel bearing to support the train is one of the important components requiring higher reliability and safety in this aspect. Recently, many studies have been made under the name of prognostics and health management (PHM), for the purpose of fault diagnosis and failure prognosis of the bearing under operation. Among them, the most important step is to extract a feature that represents the fault status properly and is useful for accurate remaining life prediction. However, the conventional features have shown some limitations that make them less useful since they fluctuate over time even after the signal de-noising or do not show a distinct pattern of degradation which lack the monotonic trend over the cycles. In this study, a new method for feature extraction is proposed based on the observation of relative frequency energy shifting over the cycles, which is then converted into the feature using the information entropy. In order to demonstrate the method, traditional and new features are generated and compared using the bearing data named FEMTO which was provided by the FEMTO-ST institute for IEEE 2012 PHM Data Challenge competition.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.797-804
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• 2013

In this study, the authors develop a methodology for a diagnostic system with a vibration parameter that is influenced by environmental factors. The data tends to have a varying average over time. Often, these features are found in statistical data retrieved from a production line. If we utilize existing statistical techniques for these features, we could derive an incorrect diagnostic conclusion based on the different average values. To overcome the limitations of previous methods, the authors apply a function analyzed through regression analysis to predict the mean value and corresponding upper and lower limits at each stage. This technique also provides corresponding statistical parameters in varying dynamic means. To validate the proposed methods, we retrieve data from the engine assembly line of H Motors and verify the results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.10
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• pp.805-812
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• 2013

The operational flight program(OFP) which has the functions of I/O processing with avionics, flight control logic calculation, fault diagnosis and redundancy mode is embedded in the flight control computer of Smart UAV. The OFP was developed in the environment of PowerPC 755 processor and VxWorks 5.5 real-time operating system. The OFP consists of memory access module, device I/O signal processing module and flight control logic module, and each module was designed to hierarchical structure. Memory access and signal processing modules were verified from bench test, and flight control logic module was verified from hardware-in-the-loop simulation(HILS) test, ground integration test, tethered test and flight test. This paper describes development environment, software structure, verification and management method of the OFP.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.161-168
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• 2019

Recently, the development and dissemination of electric vehicles is increasing as a solution for carbon and emission reduction. In Korea, the supply of electric vehicles and the expansion of chargers are increasing rapidly every year under the supervision of the Ministry of Environment. In this paper, we study the portable smart test technology which enables quick check of charge related to faults in both electric car and charger to solve the problem of failure which is inevitable in the diffusion of electric car charger. To verify the normal operation of the communication protocol between the electric car and the charger, a hardware module and software were constructed, and a portable tester based on the international standard considering the V2G technology was developed and evaluated.