• Smart Structures and Systems
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• 제26권1호
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• pp.11-21
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• 2020

The hinge joint is the key to the overall cooperative working performance of the assembled beam bridge, and it is also the weakest part during the service period. This paper proposes a method for monitoring and evaluating the lateral cooperative working performance of fabricated beam bridges based on dynamic strain correlation coefficient indicator. This method is suitable for monitoring and evaluation of hinge joints status between prefabricated girders and overall cooperative working performance of bridge, without interruption of traffic and easy implementation. The remote cloud monitoring and diagnosis system was designed and implemented on a real assembled beam bridge. The algorithms of data preprocessing, online indicator extraction and status diagnosis were given, and the corresponding software platform and scientific computing environment for cloud operation were developed. Through the analysis of real bridge monitoring data, the effectiveness and accuracy of the method are proved and it can be used in the health monitoring system of such bridges.

• 드라이브 ㆍ 컨트롤
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• 제18권1호
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• pp.24-30
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• 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.

• Journal of Oral Medicine and Pain
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• 제14권1호
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• pp.89-103
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• 1989

In order to evaluate the influences of Myo-monitoring on masticatory muscles, Myo-monitoring on 31 normal persons and 30 persons with one more temporomandibular dysfunction symptoms during 45 minutes or above. The author observed velocities of mandibular opening and closing movement, variabilities of mandibular rest position and EMG activities of temporal and masseter muscles. The obtained results were as follows : 1. There were no significant differences on velocities of mandibular opening and closing movement between before and after Myo-monitoring. 2. There were significant differences on vertical dimension and total dimension form mandibular rest position to centric occlusion between before and after Myo-monitoring but no significant differences on anteroposterior and lateral dimension. 3. Activities of temporal and masseter muscles were decreased in Myo-Monitoring. 4. There were disappeared significant differences on EMG activity values between normal and symptom groups after myo-monitoring.

• 한국태양에너지학회 논문집
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• 제36권5호
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• pp.91-100
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• 2016

This paper proposes the PV module fault diagnosis sensor which is applied to Zigbee wireless network, and monitoring system using the developed sensor. It is designed with embedded sensor in junction box. The diagnosis elements for algorithm were voltage and temperature. For that reason, It is able to reduce the price and separate the fault of bypass diode from shading differently from other monitoring systems. This fault diagnosis algorithm verified through the Field-installed operations of PV module.

• 전기학회논문지P
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• 제64권1호
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• pp.29-34
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• 2015

DC bus electrolytic capacitors are used in variety of equipments as smoothing element of the power converters because it has high capacitance for its size and low price. It is responsible for frequent breakdowns of many static converters and inverter drive systems. Therefore it is important to diagnosis monitoring the condition of an electrolytic capacitor in real-time to predict the failure of power converter. In this paper, the on-line remote diagnosis monitoring system for DC BUS electrolytic capacitors of power converter using low-cost type Zigbee communication modules is developed. To estimate the health status of the capacitor, the equivalent series resistor(ESR) of the component has to be determined. The capacitor ESR is estimated by using RMS computation using AC coupling method of DC link ripple voltage/current. The Zigbee communication-based experimental results show that the proposed remote DC capacitor diagnosis monitoring system can be applied to DC/DC converter and UPS successfully.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.271-290
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• 2013

The acceleration information is significant for the structural health monitoring, which is the basic measurement to identify structural dynamic characteristics and structural vibration. The efficiency of the accelerometer is subsequently important for the structural health monitoring. In this paper, the distance measure matrix and the support level matrix are constructed firstly and the synthesized support level and the fusion method are given subsequently. Furthermore, the synthesized support level can be served as the determination for diagnosis on accelerometers, while the consensus data fusion method can be used to recover the acceleration information in frequency domain. The acceleration acquisition measurements from the accelerometers located on the real structure National Aquatics Center are used to be the basic simulation data here. By calculating two groups of accelerometers, the validation and stability of diagnosis and recovering on acceleration based on the data fusion are proofed in the paper.

• 한국지능시스템학회논문지
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• 제18권3호
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• pp.341-346
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• 2008

본 연구에서는 화물 운송에 사용되는 운반선 중 하나인 액체운반선을 유지 관리하기위한 통합 자동화 시스템인 스마트 카고 탱커 진단 모니터링 시스템을 개발하였다. 본 연구를 통해 선박의 특수성을 고려한 선박용 능동형 스마트 센서 개발 기술을 확보하고 고신뢰성 및 내환경성을 가진 기자재를 개발하고자 하였다. 본 연구에서 제안한 카고 모니터링 시스템은 증기 압력 모니터링 부분, 카고 수위 모니터링 부분, 수위 초과 모니터링 부분, 가스 모니터링 부분, 탱크 온도 모니터링 부분으로 구성된다. 본 시스템은 각 단위 시스템으로부터 전송되는 신호의 신뢰성, 적절성 그리고 센서 자체의 이상 유무를 스스로 진단한다. 최종적으로 각 시스템의 고장진단 및 예측을 통하여 운항중인 선박에서 효과적으로 화물을 유지 관리 할 수 있도록 하는 포괄적인 통제 모니터링 시스템 개발을 목적으로 한다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2000년도 제2회 학술대회 논문집 일렉트렛트 및 응용기술전문연구회
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• pp.36-39
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• 2000

This paper presents the technology of condition diagnosis & life estimation on insulation system of the traction motor. In the non-destructive methods for diagnosis of coil insulation state, residual dielectric strength is estimated by the D-map which consist of the partial discharge quantity Q and average degradation degree $\Delta$. In the operating history of machine, the N-Y life estimation method is based on the stop-starting numbers and operating times with considering each degradation factor by the thermal, electrical and heat-cycle stress. With the on-line conditioning monitoring on the currents of traction motors, detecting the abnormal operating state due to bearing faults, stator or armature faults, eccentricity related faults and broken rotor bars can be performed.

• 전산구조공학
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• 제9권2호
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• pp.163-171
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• 1996

구조물 모니터링 시스템의 전산환경을 구성하기 위해 필요한 지식 및 정보를 파악하고 이를 지식기반화하는 방법을 제시하였다. 전산환경의 구축을 위한 정보로는 센서 및 하드웨어, 신호처리, 그리고 손상발견/평가를 위한 지식등이 필요한데, 이들은 모두 다른 형태의 지식이므로, -즉 수학연산, 서술적 지식, 수치모델등- 어느 특정의 모델링 기법 단독으로는 이들을 효과적으로 수용하기가 매우 어렵다. 이를 해결하기 위하여 객체지향적 모델링기법과 논리언어를 혼합사용하는 방법 (Hybrid Modeling Paradigm)이 제시되었고, 이의 타당성 및 효율성 검증을 위해 모델구조물을 이용한 예제를 수행하였다.

• 한국안전학회지
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• 제20권3호
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• pp.1-8
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• 2005

The industrial induction motor is widely used in the rotating electrical machine for the transmission of power. It is very reliable equipment, but it could lead to the loss of production and lift when failure occurs. Therefore, the failure data is acquired and analyzed by attaching an exclusive instrument to existing induction motor. However, these instruments could lead to side effects, increasing the production costs, because they are very expensive. The purpose of this study is the development of an induction motor bearing failure diagnosis system constructed using LabVIEW which can be supplied the kernelled function, process monitoring and current signature analysis. In addition, the availability and reasonability of the constructed system was examined for an induction motor with failure defects in outer raceway and ball bearing. From the results, it shows that failure diagnosis system constructed is useful for real-time monitoring with detection of bearing defects over the web.