• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.3
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• pp.155-161
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• 1996

For the condition monitoring of the journal bearing in rotating machinery, a system for their diagnosis by acoustic emission(AE) was developed. AE has been used to detect abnormal conditions in the bearing system. It was found from the field application study as well as the laboratory experiment using a simulated journal bearing system that AE RMS voltage was the most efficient parameter for the purpose of current study. Based on the above results, algorithms and judgement criteria for the diagnosis system was established. The system is composed of four parts as follows: the sensing part including AE sensor and preamplifier, the signal processing part for RMS-to-DC conversion to measure AE ms voltage, the interface part for transferring RMS voltage data into PC using A/D converter, and the software part including the graphic display of bearing conditions and the diagnosis program.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.453-454
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• 2011

에너지 플랜트, 화학공장 등 대형 기계설비의 복잡도 증가는 그에 따른 위험요소 복잡도를 증가시키고 있다. 대형 기계설비에 대한 위험 관리와 시스템 신뢰도 향상을 위해서는 위험도 기반의 안전 설계/해석, 상태 감시 및 진단을 이용한 설비 모니터링, 인적 신뢰도 향상이 요구되며 설계 단계에서부터 운영 및 유지보수 단계까지의 시스템 생애주기 전반에 걸친 지속적인 활동을 필요로 한다. 인적 신뢰도를 향상시키기 위해서는 설비 운영자가 응급 또는 이상상황에 대처할 수 있는 능력 즉, 안전사고 대응 능력 확보가 필수적이다. 대상 설비에 대한 실제 훈련은 시간, 비용, 훈련자의 안전 확보가 어렵고 반복적인 훈련 및 평가가 어렵기 때문에 가상 환경을 이용한 안전대응 훈련 플랫폼을 설계하였다. 훈련자에게 몰입형 가상 환경을 제공하기 위하여 가상현실 및 안전사고 시뮬레이션 기술을 이용하였으며 이를 통하여 훈련자의 안전을 유지하면서 안전대응 능력을 향상시킬 수 있다.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.134-140
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• 2016

Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.143-147
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• 2005

Monitoring and diagnosis of the operating machines are very important for safety operation and maintenance in the industrial fields. These machines are most rotating machines and the diagnosis of the machines has been researched for long time. We can easily see the faulted signal of the rotating machines from the changes of the signals in frequency. The Linear Predictive Coding(LPC) is introduced for signal analysis in frequency domain. In this paper, we propose fault detection and diagnosis method using the Linear Predictive Coding(LPC) and residual signal energy. We applied our method to the induction motors depending on various status of faulted condition and could obtain good results.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.11-12
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• 2019

본 논문에서 에스컬레이터 기계실 내부 전동기, 감속기, 구동 체인의 IoT 소음 및 진동 센서를 부착하여 에스컬레이터 운영중 실시간 상태 감시가 가능한 IoT 기반 에스컬레이터 고장 예지 시스템을 제안한다. IoT 소음 및 진동 센서는 에스컬레이터 운영 중 발생하는 소음 및 진동 데이틀 수집하여 PHM(Prognostics and Health Management) 서버로 전송하며, 서버에서는 진단 알고리즘을 통해 고장 유 무를 판단한다. 소음 데이터를 이용한 체인 피치 길이 알고리즘을 검증하기 위하여 실제 체인의 길이를 측정한 결과 값과 비교한 결과 99.8% 정확도를 가지며, 진동 데이터를 이용하여 전동기, 감속기의 상태 판단을 위한 알고리즘 검증을 위해 AST 사의 진동 센서와 비교한 결과 약간의 오차는 발생하지만 ISO 10816-3을 기준으로 한 판단 결과 값은 동일한 결과 값을 가지는 것을 확인하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.329-336
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• 2008

The facilities with new technologies in the recent power plants become larger and need a lot of high cost for maintenance due to stop operations and accidents from the operating machines. Therefore, it claims new systems to monitor the operating status and predict the faults of the machines. This research classifies the normal/abnormal status of the machines into 5 levels which are normal-level/abnormal-level/care-level/dangerous-level/fault and develops the new system that predicts faults without stop operation in power plants. We propose the regional segmentation technique in the frequency domain from the data of the operating machines and generate the Peak-codes similar to the Bar-codes, The high efficient and economic operations of the power plants will be achieved by carrying out the pre-maintenance at the care level of 5 levels in the plants. In order to be utilized easily at power plants, we developed the algorithm appling to a notebook computer from signal acquisition to the discrimination.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.950-955
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• 2003

This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.9
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• pp.835-842
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• 2016

In Korea, urban railway cars are typically maintained using the strategy of predictive maintenance. In an effort to overcome the limitations of the existing strategy, there is increased interest in adopting the condition-based maintenance strategy. In this study, a novel method is proposed to detect faults in the solenoid valves of the braking system in urban railway vehicles. We determined the key component (i.e., solenoid valve) that leads to braking system faults through the analysis of failure modes, effects, and criticality. Then, an equivalent circuit model was developed with the compensation of the temperature effect on solenoid coils. Finally, we presented how to detect faults with the equivalent circuit model and current signal measurements. To demonstrate the performance of the proposed method, we conducted a case study using real solenoid valves taken from urban railway vehicles. In summary, it was shown that the proposed method can be effective to detect faults in solenoid valves. We anticipate the outcome from this study can help secure the safety and reliability of urban railway vehicles.

• Journal of the Korean Vacuum Society
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• v.12 no.2
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• pp.93-104
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• 2003

For evaluation of durability of low vacuum pumps, it is required to examine the performance and degradation of low vacuum pumps. Pump degradation may result from abnormalities associated with the performance in many areas of pump operation. The diagnostics method can be used to monitor the pump performance in the semi-conductor process line. Based on the mechanical defect of the pump, the dynamic response and reliability of the system for performance test, and the dynamic characteristics of the pump were experimentally assessed. The theoretical work rate for the compression process in the pump was calculated, and then the efficiency of the pump associated with the power consumption was evaluated. This analysis will be useful in detecting pump degradation with increasing the power consumption. To determine the predominant factors of pump degradation, it is important to evaluate the entire pumping system. We studied vibration, dynamic pressure, pumping speed, and power consumption of low vacuum pumps. Our results can be utilized for the future research on the evaluating technology of durability of low vacuum pumps.