• 한국생산제조학회지
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• 제22권3호
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• pp.343-348
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• 2013

In line with the advances in factory automation, various pieces of equipment are now operated in batch processes controlled by computers. However, many kinds of faults can occur in complicated and large systems, which can result in low productivity and economic loss. The reliability and safety of systems have been studied because of the difficulty of determining the severity and location of faults. Therefore, it is necessary to detect and diagnose such faults in order to guarantee the reliability and safety of the equipment. In this paper, a diagnosis method for the ball bearings of a hydraulic pump is applied using a vibration signal for the maintenance of injection molding equipment. The bearings' defects are selected as a main failure mode through a failure mode and effect analysis (FMEA). Usually, there are nonlinear and impulse components of vibration in a ball bearing with faults. For the effective fault diagnosis of a ball bearing, nonlinear diagnostic methods and time-frequency analysis are applied, in addition to the methods currently used, such as power spectrum, time series analysis, and statistical methods. As a result of this study, a failure diagnosis system is provided that is useful even for non-experts. This is a condition-based method that makes it possible to resolve problems in a timely and economical way, in contrast to the prior method, which required regular but wasteful maintenance based on the experience of expensive external experts.

• 한국구조물진단유지관리공학회 논문집
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• 제16권3호
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• pp.51-59
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• 2012

본 연구에서는 도로용 패널로 사용되는 프리캐스트 콘크리트 슬래브의 양중, 이동 및 설치 등 제품의 제작 및 시공 시 발생될 수 있는 양중에 따른 안전 설계요소를 분석하였다. 그 결과를 토대로 축소형 슬래브(Full-scale용 슬래브의 1/2 크기 규모로 $1.8m{\times}3m{\times}0.15m$) 2개와 Full-scale용 슬래브($3.9m{\times}5.95m{\times}0.29m$) 1개를 제작하였으며, 콘크리트 및 철근 게이지를 설치하여 슬래브의 양중 및 트럭에 적재하여 이동 시 급작스런 동적거동으로 인해 발생되는 콘크리트 슬래브의 변형률을 측정하였다. 축소형 슬래브의 경우 60도로 양중 시 정지상태의 변형률에 비해 약 3.54배의 변형률에 도달하였다. 그러나 Full-scale용 슬래브는 양중 및 운반 중의 동적 거동을 계측한 결과 동적변형률이 그리 크지는 않아 양중과 운반 시에 파손될 염려는 거의 없는 것으로 판단되어 본 연구에서 채택한 양중 시스템의 안전성을 확인하였다.

• Smart Structures and Systems
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• 제24권5호
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• pp.669-681
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• 2019

Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV's flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.102-108
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• Tribology and Lubricants
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• 제19권1호
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• pp.36-42
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• 2003

Nowadays the importance of equipment reliability and efficiency is increasing and the concept of Total Fluid Management is introduced to make production cost down and improve equipment reliability. In this paper, basic survey on the current status of lubricants application and equipment maintenance is made. Lubrication point of the factory was 233 and 60 percent of the point was lubricated by hydraulic oils. Lubricants used at 87 points were different from those of original equipment manufacturers' recommendation. And 40 percent of the points are heavily contaminated. Exchange of oils, use of filter, computerization and so on were recommended. And introduction of Total Fluid Management concept is required.

• Structural Monitoring and Maintenance
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• 제7권2호
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• 한국정밀공학회지
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• 제21권12호
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• pp.75-83
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• 2004

With the rotating machinery getting more accurate and diversified, the necessity fur an appropriate diagnosis technique and maintenance system has been greatly recognized. However, until now, the operator has executed a monitoring of the machine by the senses or simple the change of RMS (root mean Square) value. So, the diagnostic expert system using the fuzzy inference which the operator can judge easily and expertly a condition of the machine is developed through this study. In this paper, the hardware and software of the diagnostic expert system was composed and the identification of the diagnostic performance of the developed system for 5 fault phenomena was carried out.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.582-589
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• 1998

This paper presents the analysis results of ex-core and in-core neutron noise, acceleration signals and pressure fluctuation measured at Ulchin Nuclear Unit 1 & 2 to identify and monitor the reactor internals vibration including fuel motion. A phase separation algorithm developed by authors was applied to the neutron noises to clearly identify the reactor internals vibratory motion. The beam mode frequency of the core support barrel was identified to be 8Hz and the shell mode to be 20Hz. The first frequency of the fuel assembly was also found to be 3Hz, while first two acoustic frequencies of the primary coolant system were 6 and 17.5Hz. By monitoring and analyzing these frequencies periodically, it is possible to diagnose the operating condition of reactor internals and to provide an early detection of faults for the predictive maintenance.

• 전기학회논문지
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• 제63권2호
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• pp.297-305
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• 2014

Nowadays new water supply projects have been on the decline as the water-power constructions have saturated, which means that the existing power equipment have slowly aged and they require more efforts to maintain the system performance. An effective asset management method of power equipment has become a great necessity from both economical and technical aspects. To be balanced, the asset management should look into all three parts: management, engineering, and information. The purpose of this paper is to study a Risk-Based Maintenance (RBM) matrix method through the deterioration evaluation algorithm for an efficient reliability assessment of oil-immersed power transformers by considering both asset management and technical evaluation. Make use of this result, the equipment will be decided to be replace or repair otherwise on service.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.96.4-96
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• 2002

Thermal infrared imaging is a highly promising technology for condition monitoring and predictive maintenance of electronic, electrical and mechanical elements in nuclear power plants. However, conventional low-cost infrared imaging systems suffer from poor spatial resolution compared to commercial CCD cameras. This paper describes an approach to enhance inspection performances for calandria reactor area of Wolsung nuclear power plant through the technique of superimposing thermal infrared image into real CCD image. In the occurrence of thermal abnormalities on observation points and areas of calandria reactor area, unusual hot image taken from thermal infrared camera is mapped upon re...