• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.863-868
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• 2008

This paper investigates the abnormal noise of polygon mirror scanner motor due to the mechanical contact. In the high speed polygon mirror scanner motor the vibration of polygon mirror scanner motor is one of the main sources of abnormal noise, because structure-borne noise due to the vibration is bigger than aerodynamic noise, especially when the rotating part contacts the stationary parts. This research determines the main harmonics of structure-borne noise by using sound quality evaluation. It also develops an experimental set-up to measure the mechanical contact and vibration of polygon mirror scanner motor simultaneously. This paper also show that mechanical contact between rotating shaft and stationary sleeve is one of the dominant vibration sources of structure-borne noise which cause the abnormal noise of the high speed polygon mirror scanner motor by using the developed experimental set-up.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.1049-1052
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• 2006

Object of this study is to develop an Stack Silencer System for quieting abnormal noise around power plant. Abnormal noise gets resident people to feel uncomfortable. Stack Silencer System is to minimize pressure loss of exhaust gas and to maximize noise reduction effect from abnormal noise frequency band. Stack Silencer System is installation in stack and absorbing material is an aluminum foam. Reduction effect measures insertion loss of $8.2{\sim}19.4dB$ by Stack silencer installation. After Stack Silencer System installation, pressure loss of exhaust gas measured $5{\sim}9mmH_2O$.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.380-384
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• 2001

The household reftigerator's noise which is closely related with resident environment can hardly be evaluated its sound quality using the Korean Standards. Radiation characteristics of compressor noise consist of tonal noise in low frequency range and, or narrow band noise in high frequency range. In this study, measuring method for detecting the abnormal and low-level noise in high frequency band is presented, and control method for its reduction is proposed. After installing wall which is similar to living condition, we determined a major concerning frequency band of noise. It can be found the directivity of high frequency noise radiated from compressor by using experiment and analysis. According to isolation of noise transfer path, remarkable noise reduction is achieved.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.490-494
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• 2004

The purpose of this paper was to identify the mechanism that caused abnormal vibration and noise on the piping system connected to discharge flow of BFP(Boiler Feed water Pump) in a coal fired power plant, and to develop the device that can reduce the level of abnormal vibration and noise. Major results of this project can be summarized as follows: First, we analyzed the acoustic mode for the discharge piping of BFP to trace a path of the noise, and assumed that noise and vibration on the piping system can be related with length of pipe. Second, a minimized model of the piping system was set up to simulate abnormal vibration and noise within the specific range of operating frequencies, and as a result we confirmed that the acoustic mode affected the piping system considerably. Finally the test device which can reduce the level of abnormal noise and vibration was built to verify validity applying for the piping system. Then we concluded that the noise and vibration generated from the piping system was attributed to the acoustic resonance in piping system, and so developed new device which can reduce the level of noise and vibration under 40%. Put Abstract here.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.866-869
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• 2004

Power transformers, air-intakes and stacks in the urban combined power plant are main noisy sources. Because of Inhabitant complaint by abnormal noise transferred from the power plant. the noise was investigated at power plant and uptown area. The result of diagnosis made the acoustic resonance phenomenon by 580Hz's combustion dynamic pressure with the standing wave mode of sound fields in exhaust passageway of gas turbine into main noise source of public complain. The abnormal noise is caused by the resonance exhaust noise transferred through stacks of power plant.

• 한국철도학회:학술대회논문집
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• 한국철도학회 1999년도 춘계학술대회 논문집
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• pp.208-217
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• 1999

This paper presents spectrum analysis technique to identify abnormal noise produced in diesel railcars. Coherence and coherent power spectrum are very useful in determining source identifications. Experiments are applied to two different cars with similar phenomena about the case of stop and running condition. Metal contact in mounting bracket part which is excited by excessive transmission vibration is found to cause abnormal noise.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 추계학술대회 논문집
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• pp.813-814
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• 2010

• 폴리머
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• 제37권5호
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• pp.642-648
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• 2013

이상소음은 고분자 판재가 상호간에 미끄럼 운동을 할 때 마찰에 의한 스틱-슬립 메카니즘에 의하여 발생한다. 본 연구에서는 실험적 방법을 통하여 이상소음을 줄이기 위하여 가전제품에 많이 사용되는 ABS, PP, MIPS, POM 고분자 소재에 대하여 ABS를 기초로 하여 소재간의 조합이 이상소음에 미치는 영향을 알아보았다. 소재간 마찰에 의한 이상소음을 평가하기 위한 실험방법과 장치를 제안하였으며, 실험변수로는 소재의 조합뿐만 아니라 고분자 판재의 표면 거칠기, 수직 접촉하중, 상대운동 속도 등을 두었다. 본 연구를 통하여 이상소음 저감을 위해서 ABS 소재와 POM 소재 조합이 가장 좋음을 알 수 있었으며, 다른 재료조합에 대한 결과도 상호 비교하였다.

• 한국음향학회지
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• 제43권3호
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• pp.270-276
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• 2024

본 연구에서는 기계전자 제품에 사용되는 소재의 마찰실험을 통해 스틱슬립 특성을 분석하고 냉장고 내부에서 발생하는 이상소음을 저감하는 개선안을 제안하였다. 소재의 스틱슬립 현상을 분석하기 위해 마찰실험장치를 제작하고 마찰실험을 수행하였다. 또한 냉장고 내부에서 발생하는 이상소음의 현상과 위치를 분석하기 위해 내부부품의 진동과 소음 레벨을 측정하였다. 그리고 냉장고 현상분석 결과와 마찰실험 결과를 비교하여 냉장고 내부에서 발생하는 이상소음은 내부부품의 스틱슬립 현상에 의한 것임을 확인하였다. 마지막으로 이상소음을 저감하는 개선안을 제안하기 위해 다구찌 기법을 이용한 마찰실험을 수행하였다. 그리고 개선안을 냉장고에 적용하여 성능을 검증하였다.

• Nuclear Engineering and Technology
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• 제53권4호
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• pp.1181-1188
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• 2021

When abnormal events occur in a nuclear power plant, operators must conduct appropriate abnormal operating procedures. It is burdensome though for operators to choose the appropriate procedure considering the numerous main plant parameters and hundreds of alarms that should be judged in a short time. Recently, various research has applied deep-learning algorithms to support this problem by classifying each abnormal condition with high accuracy. Most of these models are trained with simulator data because of a lack of plant data for abnormal states, and as such, developed models may not have tolerance for plant data in actual situations. In this study, two approaches are investigated for a deep-learning model trained with simulator data to overcome the performance degradation caused by noise in actual plant data. First, a preprocessing method using several filters was employed to smooth the test data noise, and second, a data augmentation method was applied to increase the acceptability of the untrained data. Results of this study confirm that the combination of these two approaches can enable high model performance even in the presence of noisy data as in real plants.