• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.135-141
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• 2000

The major role of temperature sensors in thermal error compensation system of machine tools is improving machining accuracy by supplying reliable temperature data on the machine structure. This paper presents a new method for fault diagnosis of temperature sensors and recovery of faulted data to establish the reliability of thermal error compensation system. The detection of fault and its location is based on the correlation coefficients among temperature data from the sensors. The multiple linear regression model which is prepared using complete normal data is also used fur the recovery of faulted data. The effectiveness of this method was tested by comparing the computer simulation results and measured data in a CNC machining center.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.06b
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• pp.1-7
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• 1998

본 연구에서는 3차원 솔리드 모델러로부터 Modeling한 후 제작된 model 에 사용자가 원하는 측정 위치를 지정함으로써 자동적으로 측정용 NC Data를 얻을 수 있는 알고리즘을 설계하고 이를 Program화하였다. 3-D Modeler로서 Unigraphics를 사용하였으며, 공작기계는 FANUC Controller를 장착한 Machining Center이다. 측정용 센서는 접촉식 Probe를 사용하였다. 본 연구를 통하여 CAD시스템에서 구축된 Geomaatric Model로부터 직접 측정을 위한 NC data를 얻고 이 data를 가공후의 측정 Data와 비교하여 봄으로써 제품의 가공정밀도를 확인해 볼 수 있으며, 가공시의 간섭 check, 잔삭가공여유, 과절삭등 다양한 정보를 얻을 수 있을 것이다. 향수 지속적인 연구개발을 통하여 data의 통계처리 및 공작기계의 오차 보정등을 고려하여 줌으로써 기계상에서의 측정 data에 대한 신뢰도를 구축할 수 있을 것으로 사료된다.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.291-296
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• 1998

The DAta management and Communication NETworks (DACONET), Which it is designed as a subsystem for Man-Machine Interface System of Korea Advanced LIquid MEtal Reactor(KALIMER MMIS) and advanced design concept is approached, is described. The DACONET has its roles of providing the real-time data transmission and communication paths between MMIS systems, providing the quality data for protection, monitoring and control of KALIMER and logging the static and dynamic behavioral data during KALIMER operation. The DACONET is characterised as the distributed real-time system architecture with high performance, Future direction, in which advanced technology is being continually applied to Man-Machine interface System Development of Nuclear Power Plants, will be considered for designing data management and communication networks of KALIMER MMIS

• Journal of Information Science Theory and Practice
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• v.8 no.4
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• pp.20-28
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• 2020

In this study, the RDA DMP Common Standard (RDCS), a data model for implementing a machine actionable Data Management Plan (maDMP), was analyzed in four aspects. First, the twelve class models proposed by RDCS were analyzed. Second, whether the DMP attribute was included in the class attribute was analyzed. Third, we analyzed the namespace used for RDCS properties. Fourth, the values and identifiers used in RDCS properties were analyzed. As a result of the analysis, four directions for improvement were derived. First, it is necessary to add an academic record class to describe information such as papers and reports, which are representative academic documents. Second, the primary research institution, responsibility, resources, option attribute, and additional attributes are needed to describe the researcher's affiliation information. Third, it is necessary to additionally use a namespace such as Friend of a Friend that can be used universally. Fourth, the use of digital object identifier should be considered to identify academic literature.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.39-48
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• 2021

In this paper, a GAN-based data augmentation method is proposed for topology optimization. In machine learning techniques, a total amount of dataset determines the accuracy and robustness of the trained neural network architectures, especially, supervised learning networks. Because the insufficient data tends to lead to overfitting or underfitting of the architectures, a data augmentation method is need to increase the amount of data for reducing overfitting when training a machine learning model. In this study, the Ganerative Adversarial Network (GAN) is used to augment the topology optimization dataset. The produced dataset has been compared with the original dataset.

• Asia pacific journal of information systems
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• v.31 no.2
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• pp.185-196
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• 2021

The paper aims to analyze and predict sales of liquor in the state of Iowa by applying machine learning algorithms to models built for prediction. We have taken recourse of Azure ML and Spark ML for our predictive analysis, which is legacy machine learning (ML) systems and Big Data ML, respectively. We have worked on the Iowa liquor sales dataset comprising of records from 2012 to 2019 in 24 columns and approximately 1.8 million rows. We have concluded by comparing the models with different algorithms applied and their accuracy in predicting the sales using both Azure ML and Spark ML. We find that the Linear Regression model has the highest precision and Decision Forest Regression has the fastest computing time with the sample data set using the legacy Azure ML systems. Decision Tree Regression model in Spark ML has the highest accuracy with the quickest computing time for the entire data set using the Big Data Spark systems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.288-293
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• 2005

A earn profile grinding machine is a mandatory machine tool for manufacture of high precision contoured cam. Experimental evaluation of modal analysis is an effective tool to investigate dynamic behavior of a machine. This paper presents the measurement system and experimental investigation on the modal analysis of a grinding machine. The weak part of the machine is found by the experimental evaluation. The results provide structure modification data for good dynamic behaviors. And safety of the machine was confirmed by the modal analysis of modified machine design. Finally, the cam profile grinding machine was successfully developed.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.17-21
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• 2017

In this paper, the service execution accuracy was compared by ontology based rule inference method and machine learning method, and the amount of data at the point when the service execution accuracy of the machine learning method becomes equal to the service execution accuracy of the rule inference was found. The rule inference, which measures service execution accuracy and service execution accuracy using accumulated data and pattern matching on service results. And then machine learning method measures service execution accuracy using cross validation data. After creating a confusion matrix and measuring the accuracy of each service execution, the inference algorithm can be selected from the results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.124-130
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• 1991

5-axis NC machining of sculptured surface using non-ballendmill cutters (eg. facemilling cutters) is widely used in the machining of turbine blades and marine propellers. Since there are more degrees of freedom in 5-axis machining than in 3-axis machining, generating "optimum" cutter paths and finding desirable cutter positions become very important in order for an efficient use of 5-axis NC machines. Also critical in 5-axis NC machining are collision avoidance, gouging checking, and efficient kinematic solutions. In this paper we discuss the above issues in generating 5-axis CL data. They are : kinematics modeling of NC machine; inverse kinematics solution; interference between machine component and surface; cutter gouging. A unique search method for obtaining optimal CL data is proposed. The proposed method has been successfully implemented in the machining of marine propellers on a dual 5-axis (ie, 9-axis) NC machine.C machine.