• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.122-127
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• 2008

The source of wayside noise for the train are the aerodynamic noise, wheel/rail noise, and power unit noise. The major source of railway noise is the wheel/rail noise caused by the interaction between the wheels and rails. The Structure borne noise is mainly a low frequency problem. The train noise and vibration nearby the elevated railway make one specific issue. The microphone array method is used to search sound radiation characteristics of elevated structure to predict the noise propagation from an elevated railway. In this paper, the train noise and structure borne noise by train are measured. From the results, we investigated the effect on the sound absorption tunnel for elevated railway.

• Journal of the korean Society of Automotive Engineers
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• v.6 no.1
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• pp.56-62
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• 1984

Various automotive and machine parts are having the shape of circular ring and the study and the verification of its dynamic characteristics can be the important basis of quality control and improvement of performance of inner and outer race of ball and roller radial bearing, ring gear, seal, etc. In this study, three separate sets of governing equations on the flexural vibration of circular ring were formulated each considering the effects of viscous damping, rotatory inertia and shear deformation, and three frequency formulas were derived. Numerical values of frequencies of circular and rectangular cross section ring were tabulated and compared with experimental value. Some important parameters were found in the ring vibration characteristics.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.62-70
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• 2007

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.23-29
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• 2008

Magnetic abrasive polishing is one of the nontraditional machining technologies newly developed. But it was very difficult to cut non-magnetic materials using MAP process because the process was fundamentally possible by help of a magnetic farce. In this study, we aimed to verify analytically formation of the magnetic field in a case of the nonmagnetic materials especially focused on an aluminum alloy. And also an improving strategy of the magnetic force for the non-magnetic materials was proposed and experimentally verified. Design of experimental method was adopt for assessment of parameters' effect on the MAP results of the aluminum alloy.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.259-262
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• 2009

IEC 61850 based substation automation system mainly consists of human machine interface and a various of IEDs in charge of protective and control functions of the substation. Both of them should require the performance verification of IEC 61850 communication services because their communication relation is the same as client and server throughout the digital network. This paper shows a research result on the testing method of basic communication interface of the IEC 61850 based client, which was implemented by the analysis of real communication between HMI and IED of IEC 61850 based substation automation system and refereed to IED IEC 61850 conformance test procedures.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.565-572
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• 2020

This study developed a software platform using machine learning of artificial intelligence to optimize the distillation column system. The distillation column is representative and core process in the petrochemical industry. Process stabilization is difficult due to various operating conditions and continuous process characteristics, and differences in process efficiency occur depending on operator skill. The process control based on the theoretical simulation was used to overcome this problem, but it has a limitation which it can't apply to complex processes and real-time systems. This study aims to develop an empirical simulation model based on machine learning and to suggest an optimal process operation method. The development of empirical simulations involves collecting big data from the actual process, feature extraction through data mining, and representative algorithm for the chemical process. Finally, the platform for the distillation column was developed with verification through a developed model and field tests. Through the developed platform, it is possible to predict the operating parameters and provided optimal operating conditions to achieve efficient process control. This study is the basic study applying the artificial intelligence machine learning technique for the chemical process. After application on a wide variety of processes and it can be utilized to the cornerstone of the smart factory of the industry 4.0.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.34-42
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• 2015

Modeling and control of human-involved manufacturing systems poses a huge challenge on how to model all possible interactions among system components within the time and space dimensions. As the manufacturing environment are getting complicated, the importance of human in the manufacturing system is getting more and more spotlighted to incorporate the manufacturing flexibility. This paper presents a formal modeling methodology of affordance-based MPSG (Message-based Part State Graph) for a human-machine collaboration system incorporating supervisory control scheme for flexible manufacturing systems in automotive industry. Basically, we intend to extend the existing model of affordance-based MPSG to the real industrial application of humanmachine cooperative environments. The suggested extension with the real industrial example is illustrated in three steps; first, the manufacturing process and relevant data are analyzed in perspectives of MABA-MABA and the supervisory control; second, the manufacturing processes and task allocation between human and machine are mapped onto the concept of MABA-MABA; and the last, the affordance-based MPSG of humanmachine collaboration for the manufacturing process is presented with UMLs for verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1993-1998
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• 2010

This paper presents an integrated control module for controlling transportation machine and automatic navigation using a combined technology of mobile telematics and transportation machine telematics, i.e. Mobile In Vehicle (MIV). This development includes hardware implementation and its verification of control mechanism applied to vehicle. In particular, the module is designed to be versatile in such a way that it can collect various information and facilitate various options for convenience by supporting existing networks, such as TCP/IP, Wi-Fi and 3G mobile radio networks. The study offers its versatility, intelligence and cost-effectiveness by enabling the module to support network-independent service, whereas conventional modules operate only in a certain network. Based on this module, a multiple of subsequent convenient functions for transportation machine can further be developed for safe and intelligent transportation machines.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.531-538
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• 2024

While the importance of the water quality environment is being emphasized, the water quality index for improving the water quality of urban rivers in Gwangju Metropolitan City is an important factor affecting the aquatic ecosystem and requires accurate prediction. In this paper, the XGBoost and LightGBM machine learning algorithms were used to compare the performance of the water quality inspection items of the downstream Pyeongchon Bridge and upstream BanghakBr_Gwangjucheon1 water systems, which are important points of Gwangju Stream, as a result of statistical verification, three water quality indicators, Nitrogen(TN), Nitrate(NO3), and Ammonia amount(NH3) were predicted, and the performance of the predictive model was evaluated by using RMSE, a regression model evaluation index. As a result of comparing the performance after cross-validation by implementing individual models for each water system, the XGBoost model showed excellent predictive ability.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.