• 한국자동차공학회논문집
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• 제24권1호
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• pp.99-111
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• 2016

This paper presents an integrated fault diagnosis algorithm for driving motor of In-wheel independent drive electric vehicle. Especially, this paper proposes a method that integrated the high level fault diagnosis and the low level fault diagnosis in order to improve a robustness and performance of the fault diagnosis system. The high level fault diagnosis is performed using the vehicle dynamics analysis and the low level fault diagnosis is carried using the motor system analysis. The validity of the high level fault diagnosis algorithms was verified through $Carsim^{(R)}$ and MATLAB/$Simulink^{(R)}$ cosimulation and the low level fault diagnosis's validity was shown by applying it to a MATLAB/$Simulink^{(R)}$ interior permanent magnet synchronous motor control system. Finally, this paper presents a fault diagnosis strategy by combining the high level fault diagnosis and the low level fault diagnosis.

• 품질경영학회지
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• 제52권2호
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• pp.357-376
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• 2024

Purpose: The purpose of this study is to design an objective and comparable diagnostic system for diagnosing the technology level of military maintenance depots and verify its actual applicability. Methods: Literature Review, Capability Maturity Model Integration, Analytic Hierarchy Process. Results: Military maintenance depot maintenance quality level diagnosis items, Maintenance quality level by maintenance technology area, Guidelines for diagnosing maintenance quality level, Quality level comparison results by area and implications for improvement. Conclusion: In order to systematically evaluate the maintenance quality of military maintenance depots, this study was conducted with the goal of designing an overall maintenance quality diagnosis system, including diagnosis areas, diagnosis items, and a diagnosis score award system, by improving the existing evaluation method. In addition, the newly developed maintenance quality diagnosis system was applied to actual evaluation activities and the results were returned to members, confirming the usefulness of the developed maintenance quality diagnosis system in the field.

• 한국정밀공학회지
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• 제15권2호
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• pp.35-44
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• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.

• 한국정밀공학회지
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• 제14권11호
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.706-712
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• 2009

본 논문에서는 프레스공정라인에서 발생하는 고장을 감지하고 분류하기 위한 고장진단기법을 제안한다. 또한 윤활유 레벨을 자동감지 하기 위한 방법도 제안하다. 제안한 방법에서는 FFT 주파수해석과 여러 경계인수를 갖는 ART2 신경회로망을 사용하며, LabVIEW를 이용하여 고장진단 및 윤활유 레벨 자동감시를 위한 GUI(Graphical User Interface) 프로그램을 제작하여 고장진단을 수행하였다. 실험결과들로부터 제안한 유도전동기 고장진단 및 윤활유 레벨 자동감시시스템의 성능을 확인하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.790-795
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• 1994

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item, component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introducd to Hierarchical Artificial Neural Network(HANN) for this purpose. HANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification,forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trainined by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing HANN with multitasking and message transfer between processes in SUN workstation. We tested HANN in reactor system.

• Nuclear Engineering and Technology
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• 제36권1호
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• pp.73-82
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• 2004

The deaerator of a power plant is one of feedwater heaters in the secondary system, and it is located above the feedwater pumps. The feedwater pumps take the water from the deaerator storage tank, and the net positive suction head(NSPH) should always be ensured. To secure the sufficient NPSH, the deaerator tank is equipped with the level control system of which level sensors are critical items. And it is necessary to ascertain the sensor state on-line. For this, a model-based fault detection and diagnosis(FDD) is introduced in this study. The dynamic control model is formulated from the relation of input-output flow rates and liquid-level of the deaerator storage tank. Then an adaptive state estimator is designed for the fault detection and diagnosis of sensors. The performance and effectiveness of the proposed FDD scheme are evaluated by applying the operation data of Yonggwang Units 3 & 4.

• 대한공간정보학회지
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• 제23권2호
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• pp.49-58
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• 2015

그 동안 국내외에서는 도시경쟁력 평가, 도시쇠퇴진단 등 도시의 재활성화를 위한 수준진단체계를 다양한 방법으로 구축하여 왔다. 그러나 기존 연구들에서 일반적인 도시를 진단하고 평가하는 것과는 달리 U-City의 수준을 진단하는 것은 U-City의 특성상 매우 복잡하고 어려운 작업이다. U-City는 다양한 구성요소가 서로 연계 융합되어 있어 일반적인 도시의 수준진단체계로는 그 수준을 가늠하기 힘들다. 따라서 U-City를 체계적으로 진단하기 위해서는 우선 U-City의 구조적 특성을 먼저 살펴보고 각 구성요소간의 관계성을 바탕으로 한 진단체계를 구성하는 것이 필요하다. 이에 본 연구에서는 U-City법상에 제시된 정의를 바탕으로 유비쿼터스도시계획, 유비쿼터스도시기반시설, 유비쿼터스도시기술, 유비쿼터스도시서비스 등 U-City를 구성하는 요소는 물론이고, 이를 통해 달성하고자 하는 U-City의 목표 등 다양한 요인을 종합적으로 감안한 U-City 수준진단체계의 방향성을 제시하고자 한다. 본 연구의 결과는 지역별로 상이한 U-City 품질격차를 해소하고 완성도 높은 U-City 구현을 위한 발판으로 작용할 것으로 기대된다.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.207-212
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• 2008

There are several sensors in the liquid cargo ship. In the liquid cargo ship, we can get values from various sensors that are level sensor, temperature sensor, pressure sensor, oxygen sensor, VOCs sensor, high overfill sensor, etc. It is important to guarantee the reliability of sensors. In order to guarantee the reliability of sensors, we have to study the diagnosis of sensor fault. The technology of smart sensor is widely used. In this paper, the technology of smart sensor is applied to diagnosis of level sensor fault for liquid cargo ship. In order to diagnose sensor fault and find the sensor position, in this paper, we proposed algorithms of diagnosis of sensor fault using independent sensor diagnosis unit and self fault diagnosis using sensor modeling. Proposed methods are demonstrated by experiment and simulation. The results show that the proposed approach is useful. Proposed methods are useful to develop smart level sensor.

• 한국임상수의학회지
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• 제21권3호
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• pp.298-301
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• 2004

Pregnancy diagnosis by ultrasonography was performed for both pregnant and non-pregnant Asiatic black bears which were being under hibernation. Pregnancy was diagnosed for a pregnant bear by detecting images of heart-beat and vertebrae on ultrasonograph. Serum progesterone levels were measured for both pregnant and non-pregnant bears. The level of serum progesterone was 5.79 ng/ml for a pregnant bear and 0.76 ng/ml for a non-pregnant bear, respectively, thereby it was considered that measurement of serum progesterone level can be also useful for pregnancy diagnosis for Asiatic black bear.