• Journal of Power Electronics
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• 제18권5호
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• pp.1608-1617
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• 2018

The rapid and correct isolation of faulty submodules (SMs) is of great importance for improving the reliability of modular multilevel converters (MMCs). Therefore, a fast diagnosis method containing fault detection and fault location determination was presented in this paper. An improved incremental predictive model of arm current was proposed to detect failures, and the multi-step prediction method was used to eliminate the negative impact of disturbances. Moreover, a control method was proposed to strengthen the fault characteristics to rapidly locate faulty arms and faulty SMs by detecting the variation rate of the SM capacitor voltage. The proposed method can rapidly and easily locate faulty SMs under different load conditions without the need for additional sensors. The experimental results have validated the effectiveness of the proposed method by using a single-phase MMC with four SMs per arm.

• 한국자동차공학회논문집
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• 제16권4호
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• pp.173-178
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• 2008

Electro-hydraulic brake system has many advantages. It provides improved braking performance and stability functions. It also removes complex mechanical parts for freedom of design, improves maintenance requirements and reduces unit weight. However, the EHB system should be dependable and have back-up redundancy in case of a failure. In this paper, the model-based fault diagnosis system is developed to monitor the brake status using the analytical redundancy method. The performance of the model-based fault diagnosis system is verified in real-time simulation. It demonstrates the effectiveness of the proposed system in various faulty cases.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.24-26
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• 2005

At present, KS-1000 which is one of a commercial measurement instrument for motor fault diagnosis has been used in industrial field. The measurement system of KS-1000 is composed of three part : harmonic acquisition, signal processing by KS-1000 algorithm, diagnosis for motor fault. First of all, voltage signal taken from harmonic sensor is analysed for frequency by KS-1000 algorithm. Then, based on the result values of analysis skilled expert makes a judgment about whether motor system is the abnormality or degradation state. But the expert system such a motor fault diagnosis is very difficult to bring the expectable results by mathematical modeling due to the complexity of judgment process. In this reason, we propose an automation system using fuzzy model based on genetic algorithm(GA) that builded a qualitative model of a system without priori knowledge about a system provided numerical input output data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.45.3-45
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• 2001

This paper deal with a fault detection algorithm for front wheel passenger car systems by using robust $H{\infty}$ control theory. Firstly, we present a unified formulation of vehicle dynamics for front wheel car systems and transform this formulation into state space form. Also, by considering the cornering stiffness which depends on the tyre-road contact conditions, a multiplicative uncertainty for vehicle model is described. Next, the failures of sensor and actuator for vehicle system are defined in which the fault .lter is considered. From the nominal vehicle model, an augmented system includes the multiplicative uncertainty and the model of fault filter is proposed. Lastly by using $H{\infty}$ norm property the fault detect conditions are deefi.ned, and the actuator and sensor failures are detected and isolated by designing the robust $H{\infty}$ controller, respectively.

• International Journal of Air-Conditioning and Refrigeration
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• 제9권3호
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• pp.63-71
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• 2001

This paper presents a model-based method for detecting and diagnosing some faults in the cooling tower of healing, ventilating, and air-conditioning systems. A simple model for the cooling tower is employed. Faults in cooling tower operation are detected through the deviations in the values of system characteristic parameters such as the heat transfer coefficient-area product, the tower approach, the tower effectiveness, and fan power. Three distinct faults are considered: cooling tower inlet water temperature sensor fault, cooling tower pump fault, and cooling tower fan fault. As a result, most values of the system characteristics parameter variations due to a fault are much higher or lower than the values without faults. This allows the faults in a cooling tower to be detected easily using above methods. The diagnostic rules for the faults were also developed through investigating the changes in the different parameter due to each faults.

• 대한기계학회논문집A
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• 제27권11호
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• pp.1864-1872
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• 2003

Hidden Markov Model(HMM) has been widely used in speech recognition, however, its use in machine condition monitoring has been very limited despite its good potential. In this paper, HMM is used to recognize rotor fault pattern. First, we set up rotor kit under unbalance and oil whirl conditions. Time signals of two failure conditions were sampled and translated to auto power spectrums. Using filter bank, feature vectors were calculated from these auto power spectrums. Next, continuous HMM and discrete HMM were trained with scaled forward/backward variables and diagonal covariance matrix. Finally, each HMM was applied to all sampled data to prove fault recognition ability. It was found that HMM has good recognition ability despite of small number of training data set in rotor fault pattern recognition.

• Smart Structures and Systems
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• 제29권6호
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• pp.791-797
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• 2022

A complex system is comprised of numerous entities containing physical components, devices and hardware, events or phenomena, and subsystems, there are intricate interactions among these entities. To reasonably identify the critical fault propagation paths, a system fault propagation model is essential based on the system failure mechanism and failure data. To establish an appropriate mathematical model for the complex system, these entities and their complicated relations must be represented objectively and reasonably based on the structure. Taking a command and control system as an example, this paper proposes a hierarchical fault propagation analysis method, analyzes and determines the edge betweenness ranking model and the importance degree of each sub-system.

• 한국인터넷방송통신학회논문지
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• 제22권3호
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• pp.9-14
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• 2022

각종 기기들이 연결되는 사물인터넷(internet of things) 시스템에서 중요한 부품의 고장은 경제적, 인명의 손실을 야기할 수 있다. 시스템 내에서 발생하는 고장으로 인한 손실을 줄이기 위해 고장 검진 기술이 IoT에서 중요한 기술로써 여겨지고 있다. 본 논문에서는 그래프 신경망 기반 방법을 사용하여 시스템 내의 설비에서 취득된 진동 데이터의 특징을 추출하여 고장 여부를 판단하고 유형을 분류하는 방법을 제안한다. 딥러닝 모델의 학습을 위해, CWRU(case western reserve university)에서 취득된 고장 데이터 셋을 입력 데이터로 사용한다. 제안하는 모델의 분류 정확도 성능을 확인하기 위해 기존 제안된 합성곱 신경망(convolutional neural networks) 기반 분류 모델과 제안된 모델을 비교한다. 시뮬레이션 결과, 제안된 모델은 불균등하게 나누어진 데이터에서 기존 모델보다 분류 정확도를 약 5% 향상 시킬 수 있는 것을 확인하였다. 이후 연구로, 제안하는 모델을 경량화해서 분류 속도를 개선할 예정이다.

• Structural Engineering and Mechanics
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• 제75권1호
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• pp.71-86
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• 2020

This paper presents a study on the mechanical behavior of buried pipelines crossing faults using experimental and numerical methods. A self-made soil-box was used to simulate normal fault, strike-slip fault and oblique slip fault. The effects of some important parameters, including the displacement and type of fault, the buried depth and the diameter of pipe, on the deformation modes and axial strain distribution of the buried pipelines crossing faults was studied in the experiment. Furthermore, a finite element analysis (FEA) model of spring boundary was developed to investigate the performance of the buried pipelines crossing faults, and FEA results were compared with experimental results. It is found that the axial strain distribution of those buried pipelines crossing the normal fault and the oblique fault is asymmetrical along the fault plane and that of buried pipelines crossing the strike-slip fault is approximately symmetrical. Additionally, the axial peak strain appears near both sides of the fault and increases with increasing fault displacement. Moreover, the axial strain of the pipeline decreases with decreasing buried depth or increasing ratios of pipe diameter to pipe wall thickness. Compared with the normal fault and the strike-slip fault, the oblique fault is the most harmful to pipelines. Based on the accuracy of the model, the regression equations of the axial distance from the peak axial strain position of the pipeline to the fault under the effects of buried depth, pipe diameter, wall thickness and fault displacement were given.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1489-1492
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• 1997

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square distribution is applied fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.