• Nuclear Engineering and Technology
• /
• 제55권6호
• /
• pp.2096-2106
• /
• 2023

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-driven fault diagnosis faces the problem of small and imbalanced samples, resulting in low model training efficiency and poor generalization performance. Therefore, a deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis. First, a conditional generative adversarial model is designed based on convolutional neural networks to effectively augment imbalanced samples. The original sample features can be effectively extracted by the model based on conditional generative adversarial strategy and appropriate number of filters. In addition, high-quality generated samples are ensured through the visualization of model training process and samples features. Then, a deep convolutional neural network (DCNN) is designed to extract features of mixed samples and implement intelligent fault diagnosis. Finally, based on multi-fault experimental data of motor and bearing, the performance of DCCGAN model for data augmentation and intelligent fault diagnosis is verified. The proposed method effectively alleviates the problem of imbalanced samples, and shows its application value in intelligent fault diagnosis of actual NPPs.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제51권9호
• /
• pp.413-422
• /
• 2002

In a power plant, disturbance detection and diagnosis are massive and complex problems. Once a disturbance occurs, it can be either persistent, self cleared, cleared by the automatic controllers or propagated into another disturbance until it subsides in a new equilibrium or a stable state. In addition to the Physical complexity of the power plant structure itself, these dynamic behaviors of the disturbances further complicate the fault monitoring and diagnosis tasks. A data structure called a disturbance interrelation analysis graph(DIAG) is proposed in this paper, trying to capture, organize and better utilize the vast and interrelated knowledge required for power plant disturbance detection and diagnosis. The DIAG is a multi-layer directed AND/OR graph composed of 4 layers. Each layer includes vertices that represent components, disturbances, conditions and sensors respectively With the implementation of the DIAG, disturbances and their relationships can be conveniently represented and traced with modularized operations. All the cascaded disturbances following an initial triggering disturbance can be diagnosed in the context of that initial disturbance instead of diagnosing each of them as an individual disturbance. DIAG is applied to a typical cooling water system of a thermal power plant and its effectiveness is also demonstrated.

• 한국정보과학회논문지:시스템및이론
• /
• 제30권3_4호
• /
• pp.160-167
• /
• 2003

정적 shuffle-exchange 네트워크는 여러 응용 알고리듬에 적용되고 현재 많이 사용되는 다중 단계 네트워크에 비해 적은 하드웨어를 사용하는 등 많은 장점이 있으나 아직까지 어떤 병렬처리 컴퓨터에도 채택된 없었다. 그 이유 중에 하나는 결함 내성 기능이 없었기 때문이다. 본 논문에서는 다중 결함 포용 정적 shuffle-exchange network를 소개한다. 본 논문에서 제시되는 결함 포용 정적shuffle-exchange 네트워크는 k 결함을 제어하기 위해서 최소 2k의 추가 처리 요소들과 각 처리 요소들은 최대 4k의 추가 shuffle 링크를 필요로 한다. k 결함 내성을 가진 정적 shuffle-exchange 네트워크를 m개의 동일한 모듈로 분리하여 네트워크의 신뢰성을 증가시키는 것을 보였다.

• Structural Engineering and Mechanics
• /
• 제75권2호
• /
• pp.175-191
• /
• 2020

In this study, multi-story structures are actively controlled using metaheuristic algorithms. The soil conditions such as dense, normal and soft soil are considered under near-fault ground motions consisting of two types of impulsive motions called directivity effect (fault normal component) and the flint step (fault parallel component). In the active tendon-controlled structure, Proportional-Integral-Derivative (PID) type controller optimized by the proposed algorithms was used to achieve a control signal and to produce a corresponding control force. As the novelty of the study, the parameters of PID controller were determined by different metaheuristic algorithms to find the best one for seismic structures. These algorithms are flower pollination algorithm (FPA), teaching learning based optimization (TLBO) and Jaya Algorithm (JA). Furthermore, since the influence of time delay on the structural responses is an important issue for active control systems, it should be considered in the optimization process and time domain analyses. The proposed method was applied for a 15-story structural model and the feasible results were found by limiting the maximum control force for the near-fault records defined in FEMA P-695. Finally, it was determined that the active control using metaheuristic algorithms optimally reduced the structural responses and can be applied for the buildings with the soil-structure interaction (SSI).

• Nuclear Engineering and Technology
• /
• 제27권5호
• /
• pp.670-686
• /
• 1995

본 논문의 저자는 원자력 발전소와 같은 복잡한 대규모의 시스템의 실시간 고장진단 방법을 1994년 IEEE TNS Vol. 41, No. 4 호[1］에 발표하였다. 이번 논문에서는 고장전파모델(FPM)로서 같은 'Timed SDG Model' 를 사용하고 있으나 고장전파시간( FPT)을 에메논리 개념을 이용하여 정확하게 구하기 어려운 FPT을 실질적으로 이용할 수 있도록 했으며, 또한 고장전파확율(FPP)개념을 도입하여 하나이상의 고장원인 절점 (Node)들을 절점고장율과 더불어, 보다 효과적으로 판별할 수 있도록 했다. 또 FPM내에서 고장의 전파확율를 고려함으로서 보다 실질적인 고장 진단방법을 제시하였으며 본 제안된 방법을 고리 원전 2호기 1차계통에 적용하여 1차계통 FPM내의 각 FPP이 ‘1’인 경우에 한하여 그 성능을 입증하여 보았다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제54권9호
• /
• pp.547-555
• /
• 2005

A fault-tolerant gait of multi-legged robots with static walking is a gait which can maintain gait stability and continue its walking against an occurrence of a leg failure. This paper proposes fault-tolerant gait planning of a quadruped robot walking over a rough planar terrain. The considered fault is a locked joint failure, which prevents a joint of a leg from moving and makes it locked in a known position. In this Paper, two-phase discontinuous gaits are presented as a new fault-tolerant gait for quadruped robots suffering from a locked joint failure. By comparing with previously developed one-phase discontinuous gaits, it is shown that the proposed gait has great advantages in gait performance such as the stride length and terrain adaptability. Based on the two-phase discontinuous gait, quasi follow-the-leader(FTL) gaits are constructed which enable a quadruped robot to traverse two-dimensional rough terrain after an occurrence of a locked joint failure. During walking, two front legs undergo the foot adjustment procedure for avoiding stepping on forbidden areas. The Proposed wait planning is verified by using computer graphics simulations.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2008년도 제31회 추계학술대회논문집
• /
• pp.192-195
• /
• 2008

다중 트림 상태에서 헬리콥터용 소형 터보샤프트 엔진에 부착된 센서의 고장을 검출하기 위한 방법을 제시한다. 먼저 헬리곱터의 엔진, 로터, 되먹임(feedback) 제어루프가 포함된 비선형 모델을 구하고 다중 트림 상태에서의 선형 모델을 추출하였다. 고장 검출 방법은 칼만필터에 기반한 방법을 채용하였는데 트림 상태가 변화할 때에 필터의 추정값이 연속적으로 변화하도록 상태변수 초기값을 재구성하였다. 또한 어떠한 센서가 고장이 일어났는지 구분할 수 있도록 어떤 센서의 고장을 검출한 다음 문제가 없는 경우 다음 센서의 고장 검출을 수행하는 단계적인 방법을 사용하였다. 시뮬레이션을 통하여 제시한 방법이 다중 트림 상태에서 각 센서의 고장을 잘 검출함을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권5호
• /
• pp.1186-1207
• /
• 2024

Bearings are one of the main components of mechanical equipment and one of the primary components prone to faults. Therefore, conducting fault diagnosis on bearings is a key issue in mechanical equipment research. Belief rule base (BRB) is essentially an expert system that effectively integrates qualitative and quantitative information, demonstrating excellent performance in fault diagnosis. However, class imbalance often occurs in the diagnosis task, which poses challenges to the diagnosis. Models with interpretability can enhance decision-makers' trust in the output results. However, the randomness in the optimization process can undermine interpretability, thereby reducing the level of trustworthiness in the results. Therefore, a hierarchical BRB model based on extreme gradient boosting (XGBoost) feature selection with interpretability (HFS-IBRB) is proposed in this paper. Utilizing a main BRB alongside multiple sub-BRBs allows for the conversion of a multi-classification challenge into several distinct binary classification tasks, thereby leading to enhanced accuracy. By incorporating interpretability constraints into the model, interpretability is effectively ensured. Finally, the case study of the actual dataset of bearing fault diagnosis demonstrates the ability of the HFS-IBRB model to perform accurate and interpretable diagnosis.

• 한국전기전자재료학회논문지
• /
• 제19권10호
• /
• pp.942-946
• /
• 2006

We simulated insulation defects of stator winding wire on high voltage generator by 5 types. 4 types have one discharge source and other one has multi discharge source by simulation. For accurate decision, measurements used to PRPD pattern to occurred partial discharge source of various types. In this research, when PRPD pattern carried out or analyzed pattern recognition of discharge source, it used to powerful tools. In this result, PRPD Pattern defined to have single discharge source of 4 types by insulation defect. When insulation defect simulated, all the defected winding have not the same result. Errors for a little different can make mistakes from a subtle distinction. The difference between internal and void discharge have magnitude of pulse amplitude of inner discharge bigger than void discharge and have a shape of bisymmetry. But void discharge has a shape of bisymmetry against maximum value on polarity respectively. In cases of slot and surface discharge, we confirmed to show similar results those other researchers. In case of multi-discharge, as a result of we could classify not perfect match with occurred patterns in single discharge eachother. In the future, we will have to recognize and classify with results of multi-discharge.

• 대한전기학회논문지:전력기술부문A
• /
• 제55권6호
• /
• pp.227-235
• /
• 2006

In this paper, autonomous separation methodology of faulted section based on network is proposed newly, which can minimize the outage effect as compared with the existing center-based faulted section separation method by determining and separating autonomously the faulted section by the free operation information exchange among IEDs on the feeder of distribution system. The all IEDs is designed in network in which client/server function is possible in order to separate autonomously the faulted section using PtP(Peer to Peer) communication. Also, Inference based solution of IED for the autonomous faulted section separation is designed by rules obtained from the analyzing results of distribution system topology. Here, the switch IEDs transmit on network the fault information utilizing on multi-casting communication method, at the fame time, determine selfly whether they operates or not by inferencing autonomously the faulted section using the inference-based solution after receiving the transmitted information. Finally, in order to verify the effectiveness and application possibility of the proposed methodology, the diversity fault cases are simulated for the typical distribution system.