• Proceedings of the Safety Management and Science Conference
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• 2000.05a
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• pp.241-248
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• 2000

Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automation system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.325-325
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• 2004

최근 UC 공작기계의 활용성 및 산업전반에 차지하는 중요성이 날로 증가하고, If기술을 접목한 네트워크 솔루션의 비약적인 발달에 힘입어 대부분의 공정들이 자동화됨에 따라 최종 부품의 가공정밀도는 전적으로 CNC 공작기계에 의존한다고 할 수 있다. 그러나 공작기계 각 구성 부품들의 가공오차와 조립 시 발생하는 기하학적 오차, 장시간 사용으로 인한 마모, 구조물의 온도 상승에 따른 열팽창 등으로 인하여 공구와 공작물간에 상대적인 공칭거리와 실제로 운동하는 거리와의 차이가 발생한다.(중략)

• Journal of the Korea Safety Management & Science
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• v.2 no.3
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• pp.185-195
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• 2000

Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automatino system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.644-646
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• 2023

스마트팩토리는 협동 로봇과 같은 프로그래머블한 설비의 유기적인 협업을 통해 최적화된 공정을 수행한다. 따라서 수집되는 센서 데이터의 특징과 환경 조건의 복잡도가 높아, 예지보전을 위한 AI 소프트웨어의 개발 시 요구사항 기반의 체계적인 개발 및 검증이 필수적이다. 본 논문에서는 AI 소프트웨어의 요구사항을 사용자와 시스템 관점에서 정의하고, AI 모델 개발 프로세스와 스마트팩토리 예지보전 측면에서 분석한다. 도출된 요구사항을 CNN 기반의 협동 로봇 기어 마모 예측 모델의 개발에 적용하여 데이터 관리와 모델 신뢰성 관점의 요구사항을 분석 및 검증하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.57-63
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• 2001

The wound rotor type induction motor(WRIM) control system which is widely used in the industry has many maintenance problem because of external resistors and magnetic contactors. In this paper, the simple sensorless vector control algorithm for WRIM is proposed without any additional devices except detecting rotor currents. Because the external resistors are disconnectd and the rotor slip rings are shorten, the power loss due to external resistors is removed and the maintenance problem is improved remarkably. Also, the vector control performance becomes better because the proposed sensorless vector control algorithm does not use the rotor resistance which is usually used to estimate the slip frequency in case of indirect vector control scheme. The proposed algorithm is verified by the digital simulation and the experiment.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.825-831
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• 2020

In modern society, automobiles have become an essential means of transportation. It is the only consumable that is worn by contacting the ground among automobile parts. If the tyres are severely worn, the tyres may be break, presenting a risk of a serious accident to the driver. To avoid this risk, drivers should check tyre pressure and tread condition before driving a car. Tyre inflation pressure can be easily measured by TPMS, but in the case of tyre tread conditions, it can be cumbersome when the driver measures it directly using a coin or vernier caliper. This hassle can expose the driver to traffic accidents due to tyre breakage by neglecting to measure the condition of the tyre tread. In this paper, we introduce the contents of research to design an IoT service-based system that can automatically measure automobile tyres, and we verified the possibility of realizing the system by actually implementing and testing some components of the system.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1409-1410
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• 2015

현대기술의 발달로 인해 인간의 삶 중 많은 부분을 기계가 차지하고 있다. 특히 로봇공학 분야는 위험하거나 혹은 매우 정밀함을 요하는 일, 단순반복 등 인간이 기피하거나 하기 어려운 일을 대신 해줌으로서 많은 관심을 받고 있다. 이에 우리는 우리 생활에 가장 깊숙히 들어와 있는 로봇팔분야에 대해 말하고자 한다. 현재 로봇팔은 산업용은 물론, 의료용, 재해용 등 다양한 분야에서 사용되고 있다. 하지만 매우 정밀하고 정확한 작업을 위해 만들어져 있음에도 불구하고, 약간의 충격에도 이상이 생긴다거나, 기기의 이음세 부분의 잦은 회전으로 마모가 발생하게 되고 그에 따라 미세한 오차가 발생한다. 그런 상황을 방지하고자, 우리는 PSD(Position Sensitive Detecter)센서를 이용해 실시간으로 굽힘각을 측정 및 감시하여 보다 정확한 구동을 유도하려 한다. 이는 단순한 로봇팔만이 아닌 휴머노이드나 다른 회전을 이용하는 기기라면 어디든 쉽게 적용 할 수 있을 것이다.

• Journal of IKEEE
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• v.26 no.3
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• pp.488-493
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• 2022

In manufacturing sites, bearing fault in eletrically driven motors cause the entire system to shut down. Stopping the operation of this environment causes huge losses in time and money. The reason of this bearing defects can be various factors such as wear due to continuous contact of rotating elements, excessive load addition, and operating environment. In this paper, a motor driving environment is created which is similar to the domestic manufacturing sites. In addition, based on the established environment, we propose a dataset for bearing fault detection by collecting changes in vibration characteristics that vary depending on normal and defective conditions. The sensor used to collect the vibration characteristics is Microphone G.R.A.S. 40PH-10. We used various machine learning models to build a prototype bearing fault detection system trained on the proposed dataset. As the result, based on the deep neural network model, it shows high accuracy performance of 92.3% in the time domain and 98.3% in the frequency domain.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.2
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• pp.145-150
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• 2020

Water wall tube is one of the major factors consisting of a fluidized bed boiler and it plays very important role for the generation of electricity within the boiler. But these water wall tubes within the fluidized bed boiler are subject to the ware and corrosion caused by the high temperature gas and the flowing medium. If water leak is occurred, the secondary damage by the water leak will occur. As a result of that, the power generation efficiency decreases noticeably. Therefore, the maintenance of the water wall tube is very important. In this study, we designed a exciter sensor based on simulation and composed a remote field eddy current system for the defect evaluation of the outer water wall tube. Starting from the shape design of exciter, we conducted simulations for various design factors such as the water wall tube size, material, frequency, lift-off and so on. Based on the results, we designed the optimum exciter sensor for the water wall tube test within the fluidized bed boiler.