• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.4
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.321-324
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• 2004

본 논문에서는 유도전동기 고장진단을 위하여 계층적인 하이브리드 뉴럴네트웍을 제안하였다. 시스템의 입출력 데이터에 근거하여 패턴을 분류하고자 할 때 직접적인 분류가 어렵거나 성능이 좋지 않을 경우 적절한 방법을 통하여 변환을 하거나 또는 패턴 분류기의 특성에 맞도록 변환하여 패턴 분류 성능을 향상하는 등 단계별 변환 및 분류 기법을 이용하였다. 제안된 방법에서는 실험에 의해 측정된 전류값을 주기별로 주성분분석(PCA) 기법을 이용하여 입력차원을 축소한 후 이를 조건부 FCM으로 방사기저함수의 초기치를 최적화하여 학습을 하였다. 이는 주성분분석이 가지는 특성을 이용하여 데이터의 특징을 나누었으며 이를 뉴럴네트웍의 학습 기능을 이용하여 모델의 최종 성능을 개선하는 것이다. 각각의 알고리즘이 가지는 특징을 활용하면서도 단점을 계층적으로 보안하여 유도 전동기 고장 진단 성능을 개선하였다. 이를 실제 계측된 유도전동기 데이터를 이용하여 제안된 방법의 유용성을 보이고자 한다.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.36-41
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• 2008

Fault detection and diagnosis(FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. An experimental study has been performed on fault detection and diagnosis method for a water chiller. Bayes classifier, which is one of classical pattern classifiers, is adopted in deciding whether fault occurred or not. FDD algorithm can detect refrigerant leak failure, when 20% amount of charged refrigerant for normal operation leaks from the water chiller. The refrigerant leak failure caused COP reduction by 6.7% compared with normal operation performance. When two kinds of faults, such as a decrease in the mass flow rate of cooling water and temperature sensor fault of cooling water inlet, are detected, COP is a little decreased by these faults.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.283-288
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• 2015

The possible erroneous output data of the sensor nodes can cause the performance limit or the degradation of the reliability in the whole wireless sensor networks(WSN). In this paper, we propose a new sensor node scheme with multiple sensors and a new fault diagnostic algorithm. The algorithm can increase the reliability of the whole WSNs by utilizing measurements of the multiple sensors on the node and by determining the validity of the date by comparing the value of each sensor. It can increase the cost and complexity of the node, but is suitable for the area where the high reliability is critical.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.71-75
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• 1991

This paper deals with designing a real-time fault and accommodation system. The LQG controller is adopted in the normal state and the output of LQG controller is corrected using Separated Bias Estimator in the faulty state. The proposed scheme has been applied to the two-tank control system and showed satisfactory performance.

• Proceedings of the SAREK Conference
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• 2004.06a
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• pp.144-144
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• 2004

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.59-70
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• 2022

In this paper, we proposed an active fault tolerant control (AFTC) method for the position control of a quadrotor with complete loss of effectiveness of one motor. We obtained the dynamics of a quadrotor using Lagrangian equation without small angle assumption. For detecting the fault on a motor, we designed a fault detection module, which consists of the fault detection and diagnosis (FDD) module and the fault detection and isolation (FDI) module. For the FDD module, we designed a nonlinear observer that observes the states of a quadrotor based on the obtained dynamics. Using the observed states of a quadrotor, we designed residual signals and set the appropriate threshold values of residual signals to detect the fault. Also, we designed an FDI module to identify the fault location using the designed additional conditions. To make a quadrotor track the desired path after detecting the fault of a motor, we designed a fault tolerant controller based on the multiple sliding surface control (MSSC) technique. Finally, through simulations, we verified the effectiveness of the proposed AFTC method for a quadrotor with complete loss of effectiveness of one motor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1279-1289
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• 1992

Fault-tolerant system in improved the reliability and safety by using hardware and software redundancy. Fault mask and detection, identification techniques are conditionally used with system's application areas. Here DMR system is operated with standby and fail-safe module method that has minimal hardware and software redundancy, then its reliablity and safety comparison is presented respectively. Also this paper proposed an effective methods of dealing with transient faults as compared system's MTTFs to transient faults tolerance capabilities of self-diagnosis program.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.147-154
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• 1998

As technical systems in building are being developed, the processes and systems get more difficult for the average operator to understand. When operating a complex facility, it is beneficial in equipment management to provide the operator with tools which can help in dicision making for recovery from a failure of the system. The main object of the study is to develop real-time automatic fault detection and diagnosis system for optimal operation of IBS building.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1305-1307
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• 2022

자동차 부품의 결함은 시스템 전체의 성능 저하 및 인적 물적 손실이 발생할 수 있으므로 생산라인에서의 불량 검출은 매우 중요하다. 따라서 정확하고 균일한 결과의 불량 검출을 위해 딥러닝 기반의 고장 진단 시스템이 다양하게 연구되고 있다. 하지만 제조현장에서는 정상 샘플보다 비정상 샘플의 발생 빈도가 현저히 낮다. 이는 학습 데이터의 클래스 불균형 문제로 이어지게 되고, 이러한 불균형 문제는 고장을 판별하는 분류 모델의 성능에 영향을 끼치게 된다. 이에 본 연구에서는 모터의 동작음으로부터 불량 모터를 판별하는 불량 검출 시스템 설계를 위한 데이터 불균형 해결 방법을 제안한다. 자동차 사이드 미러 모터의 동작음을 학습 및 테스트를 위한 데이터 셋으로 사용하였으며 손실함수 계산 시 학습 데이터 셋의 클래스별 샘플 수 가 반영되는 label-distribution-aware margin(LDAM) loss 와 Inception, ResNet, DenseNet 신경망 모델의 비교 분석을 통해 불균형 데이터를 처리할 수 있는 가능성을 보여주었다.