• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.22 no.12
• /
• pp.1227-1236
• /
• 2012

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.19 no.6
• /
• pp.103-111
• /
• 2015

To evaluate the compressive strength of concrete, rebound test and ultra pulse velocity methods as well as core test were widely used. The predicted strength effected by age, maturity and degradation of concrete, is a slight difference between in-situ concrete strength. The compressive strength of standard cylinder specimens and core samples by obtained from drilling will have a difference since the concrete is disturbed during the drilling by machinery. And the rebound number and ultra pulse velocity are also changed according to the age and maturity of concrete that effected to the surface hardness and microscpic minuteness. The authors performed the experimental work to reflect the age and core effect to the results from NDE test. The test results considering on the core and age of concrete were compaired with the proposed equation to predict the compressive strength.

• The KIPS Transactions:PartA
• /
• v.17A no.2
• /
• pp.81-92
• /
• 2010

There has been some research in the equipment defect detection based on vibration information. Most research of them is based on vibration monitoring to determine the equipment defect or not. In this paper, we introduce more accurate system for engine defect detection based on vibration information and we focus on detection of engine defect for boat and system control. First, it uses the duplicated-checking method for vibration information to determine the engine defect or not. If there is a defect happened, we use the method using error part of vibration information basis with error range to determine which kind of error is happened. On the other hand, we use the engine trend analysis and standard of safety engine to implement the vibration information database. Our simulation results show that the probability of engine defect determination is 100% and the probability of engine defect classification and detection is 96%.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.675-680
• /
• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around the world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance. CMS(Condition Monitoring System) can be used to aid plant operator in achieving these goals. Its aim is to provide operators with information regarding th e health of their machine, which in turn, can help them improve operation efficiency. In this work, wind turbine fault diagnostic algorithm which can diagnose the mass unbalance and aerodynamic asymmetry of the blades is proposed. Proposed diagnostic algorithm utilizes both FFT(Fast Feurier Transform) of the signal from accelerometers installed inside of nacelle and simple diagnostic logic. Furthermore, to verify the applicability of the proposed system, 3W small sized wind turbine system is tested and physical experiments are carried out.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.13 no.1 s.53
• /
• pp.69-77
• /
• 2009

An underwater structure is made to put with serious damage state by special environmental factors. If this damage phenomena persist, as for the structure, it is generated a structural serious problem because of the corrosion of a reinforcing bar and the loss of the concrete cut end. Repair work of an underwater structure is very harder than repair work in land, and it is actual that certification about a maintenance effect is uncertain. And the existing repair method is applied to a structure damaged with you without verification of a repair effect by a foreign reward and experience. In this study, a repair method about an underwater structure was proposed and observed a behavior characteristic and interface failure of an specimens. and comparison analyzed an effect of a proposed maintenance method.

• Tribology and Lubricants
• /
• v.24 no.3
• /
• pp.111-121
• /
• 2008

An integrated in-line oil monitoring detector assigned for continuous in situ monitoring multiple parameters of oil performance for predicting economically optimal oil change intervals and equipment condition control is presented in this study. The detector estimates oil deterioration based on the information about chemical degradation, total contamination, water content of oil and oil temperature. The oil oxidation is estimated by "chromatic ratio", total contamination is measured by the changes in optical intensity of oil in three optical wavebands ("Red", "Green" and "Blue") and water content is evaluated as Relative Saturation of oil by water. The detector is able to monitor oils with low light absorption (hydraulic, transformer, turbine, compressor and etc. oils) as well as oils with rather high light absorption in visible waveband (diesel and etc. oils). In a case study that the detector is applied to a diesel engine oil, it is found that the detector provides good results on oil chemical degradation as well as soot concentration.

• Tribology and Lubricants
• /
• v.26 no.1
• /
• pp.73-77
• /
• 2010

One of the important trends for condition monitoring in the 21st century is the development of smart sensors that will permit the cost-effective continuous monitoring of key machine equipments. In this study, an integrated in-line oil monitoring sensor assigned for continuous in situ monitoring multiple parameters of oil performance is presented. The sensor estimates oil deterioration based on the information about chemical degradation, total contamination, water content of oil and oil temperature. The oil oxidation is estimated by "chromatic ratio", total contamination is measured by the changes in optical density of oil in three optical wave-bands ('Red', 'Green' and 'Blue') and water content is evaluated as relative saturation of oil by water. In order to evaluate the sensor's effectiveness, the sensor was applied to several used oil samples in steel making industry and the results were compared with those measured by standard test methods.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.20 no.2
• /
• pp.185-190
• /
• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.822-824
• /
• 2012

21세기는 유전자, 질병검사를 통해 질병 예방, 예후 관리, 재택 및 원격 진료 시스템을 구축하여 초고감도, 실시간으로 환자의 건강 상태를 모니터링 하고, 진단, 처방할 수 있는 IT/BT/NT를 결합한 유비쿼터스 의료 시스템이 대두할 것으로 기대되고 있다. 유비쿼터스 의료 시스템의 핵심적인 역할을 할 것으로 기대되는 바이오센서는 측정 기술로서 획기적인 발전을 거듭하고 있으며 생물학, 화학, 의학, 전자, 물리, 컴퓨터, 기계 공학 등 최첨단 학문의 관련 기술이 복합적으로 융합되면서 실용화에 필요한 요소 기술들이 접목되고 점점 소형화, 시스템화 되어 가고 있는 추세이다. 특히 SiNW(silicon nanowire) 바이오센서 같은 경우 양쪽의 전극이 소스와 드레인 역할을 하고 SiNW receptor가 검출대상과 결합하면 게이트 역할을 하게 된다. 불순물의 농도에 따라 전기적 특성이 결정되는데 검출하고자하는 대상이 receptor와 결합하게 되면 마치 MOS에서 게이트에 전압을 인가한 동작과 같은 역할을 하게 되어 소소와 드레인 사이에 채널이 형성되고 하나의 저항처럼 동작하게 된다. 본 논문에서는 기존의 MOS를 이용하여 현재 전자소자나 바이오센서 등 많은 분야에서 응용되고 있는 SiNW 바이오센서의 기능과 유사하게 피드백 회로를 통해 구현하였다. 피드백 회로의 정상 작동 확인과 SiNW 바이오센서의 역할을 대체한 MOS 소자의 정상 작동을 확인을 위해 블루투스 통신을 이용하여 모니터에 전압 값을 표시한다.

• Journal of Drive and Control
• /
• v.18 no.1
• /
• pp.24-30
• /
• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.