• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.130-130
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• 2000

This paper presents a robust fault diagnosis and fault tolerant control lot the actuator and sensor faults in the closed-loop systems affected by unknown inputs or disturbances. The fault diagnostic scheme is based on the residual set generation by using robust Parity space approach. Residual set is evaluated through the threshold test and then fault is isolated according to the decision logic table. Once the fault diagnosis module indicates which actuator or sensor is faulty, the fault magnitude is estimated by using the disturbance-decoupled optimal state estimation and a new additive control law is added to the nominal one to override the fault effect on the system. Simulation results show that the method has definite fault diagnosis and fault tolerant control ability against actuator and sensor faults.

• 전자공학회논문지C
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• 제36C권9호
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• pp.44-53
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• 1999

조합회로에 대하여 고장 진단 검사신호를 생성하는 것은 매우 어려운 문제로 남아있다. ISCAS85 c7552회로의 경우, 약 1억 개의 고장짝(Fault pair)을 가지고 있기 때문에 적은 노력과 시간을 사용하여 좀 더 많은 정보를 얻을 필요가 있다. 본 연구에서는 새로운 고장 진단 검사신호 생성 알고리즘이 제안되었고 구현되었다. 또 새로운 알고리즘과의 비교를 위하여 PODEM을 기본으로 하여 DIATEST 알고리즘을 구현하였다. 구현된 두 개의 알고리즘을 ISCAS85 회로에 적용하여 실행하였으며, 그 결과 두 개 알고리즘 모두 99%의 고장 진단율을 보였으나, 새로운 알고리즘은 각 고장의 검출 및 구별을 동시에 고려하기 때문에 고장 진단 사전과, 고장 진단 결정 트리의 제작시 더 많은 정보를 줄 수 있다. 또한 검사신호의 수를 비교했을 때 새로운 고장 진단 검사신호 생성 알고리즘이 절반이하의 개수만이 필요했다. 다만, vector 생성 속도에 있어서는 DIATEST가 우수하였다.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1272-1278
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• 1999

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to fault diagnosis. In this paper, we proposes an FDI system for nonlinear systems using neuro-fuzzy inference system. The proposed diagnostic system consists of two neuro-fuzzy inference systems which operate in two different modes (parallel and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis Function) network to identify the faults. The proposed FDI scheme has been tested by simulation on two-tank system.

• Journal of Mechanical Science and Technology
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• 제19권5호
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• pp.1095-1106
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• 2005

Recently, the conventional controller of machine-tool has been increasingly replaced by the PC-based open architecture controller, which is independent of the CNC vendor and on which it is possible to implement user-defined application programs. This paper proposes CNC­implemented fault diagnosis and web-based remote services for machine-tool with open architecture CNC. The faults of CNC machine-tool are defined as the operational faults occupied by over $70{\%}$ of all faults. The operational faults are unpredictable as they occur without any warning. Two diagnostic models, the switching function and the step switching function, were proposed in order to diagnose faults efficiently. The faults were automatically diagnosed through the fault diagnosis system using the two diagnostic models. A suitable interface environment between CNC and developed application modules was constructed for the internal function of CNC. In addition, a suitable web environment was constructed for remote services. The web service functions, such as remote monitoring and remote control, were implemented, and their operability was tested through the web. The results obtained through this research could be a model of fault diagnosis and remote servicing for machine-tool with open architecture CNC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• 한국기계가공학회지
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• 제15권6호
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• pp.1-8
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• 2016

As demand for paper cups markedly increases, this has brought about a requirement to develop fast paper cup forming machines. However, the fast manufacturing speed of these machines causes faults to occur more frequently in the final product. To reduce the possibility of producing faulty products, it is necessary to develop technologies to monitor the manufacturing process and diagnose the machine status. In this research, we selected the main driving axis of the forming machine for fault diagnosis. We searched the states of rotational elements related to the driving axis and suggested a fault diagnostic system based on spectrum analysis consisting of a real-time data acquisition device, accelerometers, and a diagnosis algorithm. To evaluate the developed fault diagnostic system, we performed experiments using a test station which resembles the actual paper cup forming machine. As a result, we were able to confirm that the proposed system was sufficiently feasible to diagnose any abnormalities in the operation of the paper cup forming machine.

• 한국추진공학회지
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• 제15권2호
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• pp.1-7
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• 2011

다양한 비행환경에서 장시간 체공하며 운용되는 UAV에서 추진시스템을 신뢰성 있게 운용하는 것은 매우 중요하다. 이런 UAV에 사용되는 터보프롭 엔진의 정확한 손상진단은 신뢰성과 이용률을 향상시킬 수 있다. 본 연구에서는 엔진 측정 파라미터들의 변화로부터 퍼지 이론을 적용하여 손상된 구성품을 식별한 후 훈련된 신경망 알고리즘을 식별된 손상 패턴에 적용하여 손상된 양을 정확히 진단할 수있는 방법을 제안하였다. 이렇게 제안된 진단 방법은 단일손상과 다중손상 모두 진단할 수 있다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2010년도 제35회 추계학술대회논문집
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• pp.499-505
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• 2010

다양한 비행환경에서 장시간 체공하며 운용되는 UAV에서 추진시스템을 신뢰성 있게 운용하는 것은 매우 중요하다. 이런 UAV에 사용되는 터보프롭 엔진의 정확한 손상진단은 신뢰성과 이용률을 향상시킬 수 있다. 본 연구에서는 엔진 측정 파라미터들의 변화로부터 퍼지 이론을 적용하여 손상된 구성품을 식별한 후 훈련된 신경망 알고리즘을 식별된 손상 패턴에 적용하여 손상된 양을 정확히 진단할 수 있는 방법을 제안하였다. 이렇게 제안된 진단 방법은 단일손상과 다중손상 모두 진단할 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.685-686
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• 2007

This paper presents an application of power system fault diagnostic algorithm for the PEFP Proton Accelerator Research Center using neural network. Proposed fault diagnostic system is constructed by the radial basis function (RBF) neural network because it has the capabilities of the pattern classification and function approximation of any nonlinear function. Proposed system identifies faulted section in the power system based on information about the operation of protection devices such as relays and circuit breakers. In this paper, parameters of the RBF neural networks are tuned by the GA-TS algorithm, which has the global optimal solution searching capabilities. To show the validity of the proposed method, proposed algorithm has been tested with a practical power system in Proton Accelerator Research Center of PEFP.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1428-1431
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• 1997

This paper presents an efficient fault diagnosis methodology for lare chemical processes. The methodology is based on a two-tier strategy, When a falt occurs in a process, a top tier identifies the sector (process part or unit) that may contain the fault(s). Afterwards, a bottom tier or lower level evaluates the suspicious sector. The process modeling methodology based on functionality-behavior relations of process units, is proposed and utilized in the top-tier. This methodology models a target process as sequences of functions and variables and their relations. In the bottom tier, each sector has a dedicated diagostic module, which is tailored to the available information or models of the sector. For the sectors selected in the top-tier diagnosis, each diagnostic module is executed to identify the actual faults within the sector. Teh utility of the methodology is illustrated in the diagnosis of the CSTR with heat exchanger.