• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2014년도 추계학술대회 논문집
• /
• pp.84-89
• /
• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1998년도 하계학술대회 논문집 B
• /
• pp.420-422
• /
• 1998

All Fault Detection and Diagnosis(FDD) methods utilize classification techniques. The objective of this study was to demonstrate the application of classification techniques to the problem of diagnosing faults in data generated by a variable-air-volume(VAV) air-handling unit(AHU) simulation model and to describe the characteristics of the techniques considered. Artificial neural network classifier and fuzzy clustering classifier were considered for fault diagnostics.

• 조명전기설비학회논문지
• /
• 제19권5호
• /
• pp.80-86
• /
• 2005

유도전동기는 프로세스산업과 다른 산업분야에 광범위하게 적용되는 매우 중요한 기기이다. 프랜트를 운전함에 있어서 이의 신뢰성, 효율 및 성능은 매우 중요한 관심사항이다. 특히 유도전동기의 고장을 미리 검출하여 진단하고 고장 아래에서도 시스템이 안전하고 신뢰성 있는 성능을 가질 수 있는 고장허용제어의 실현이 매우 중요하다. 따라서 본 논문에서는 고정자전류신호 검출과 디지털 신호 프로세싱에 의한 효과적인 유도전동기의 베어링 고장검출 및 진단 기반을 가진 고장허용제어 시스템을 구축하였다. 또한 모타 고장허용제어에 기본이 되는 제어 하드웨어 구조를 제시하였으며 실험을 통하여 이 시스템의 실시간 데이터 취득 성능을 확인하였다.

• 전기학회논문지
• /
• 제59권8호
• /
• pp.1456-1463
• /
• 2010

The safety critical systems in nuclear power plants should be designed to have a high level of fault tolerant capability because those systems are used for protection or mitigation of the postulated accidents of nuclear reactor. Due to increasing of the system complexity of the digital based system in nuclear fields, the reliability of the digital based systems without an auto-test or a self-diagnostic feature is generally lower than those of analog system. To overcome this problem, additional redundant architectures in each redundant channel and self-diagnostic features are commonly integrated into the digital safety systems. The self diagnostic function is a key factor for increasing fault tolerant capabilities in the digital based safety system. This paper presents an availability and safety evaluation model to analyze the effect to the system's fault tolerant capabilities depending on self-diagnostic features when the loss or erroneous behaviors of self-diagnostic function are expected to occur. The analysis result of the proposed model on the several modules of a safety platform shows that the improvement effect on unavailability of each module has generally become smaller than the result of usage of conventional models and the unavailability itself has changed significantly depending on the characteristics of failures or errors of self-diagnostic function.

• 한국소음진동공학회논문집
• /
• 제12권10호
• /
• pp.799-807
• /
• 2002

The vibration signal can give an indication of the condition of rotating machinery, highlighting potential faults such as unbalance, misalignment and bearing defects. The features in the vibration signal provide an important source of information for the faults diagnosis of rotating machinery. When additional training data become available after the initial training is completed, the conventional neural networks (NNs) must be retrained by applying total data including additional training data. This paper proposes the fault diagnostics algorithm using the ART-Kohonen network which does not destroy the initial training and can adapt additional training data that is suitable for the classification of machine condition. The results of the experiments confirm that the proposed algorithm performs better than other NNs as the self-organizing feature maps (SOFM) , learning vector quantization (LYQ) and radial basis function (RBF) NNs with respect to classification quality. The classification success rate for the ART-Kohonen network was 94 o/o and for the SOFM, LYQ and RBF network were 93 %, 93 % and 89 % respectively.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제5권9호
• /
• pp.285-292
• /
• 2016

최근 차량에 블루투스와 와이파이 등 근거리 통신기능을 부가하여 스마트폰과 연동함으로써, 최신 자동차는 차량 전자제어장치인 ECU를 통하여 자동차 위치정보, 고장 진단정보 등 다양한 정보를 파악할 수 있도록 엔터테인먼트화 되어 가고 있다. 본 연구를 통하여, 온보드 진단기와 스마트폰의 근거리 통신 기능을 활용하여, 차량 온보드 진단기와 연관하여 여러 가지 스마트폰 모델과 블루투스 및 근거리 무선통신인 NFC와의 호환성 시험을 실시하고, 이를 분석해 보았다. 더 나아가, 스마트폰 연동 블루투스 및 NFC 인터페이스 기능을 갖는 온보드 진단기의 단말기 구성과 고장진단 기능 구현을 비롯하여, 고장진단용 디버깅 프로그램을 개발하였다. 또한, OBD-II 인터페이스를 통해 차량의 고장진단 데이터를 추출하였으며, 끝으로 온보드 진단기 CAN 프로토콜 구현 제시와 함께 이의 결과를 분석하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.706-709
• /
• 1996

In this paper, an algorithm for PLC(Programmable Logic Controller) fault diagnosis system is proposed and experimentation is conducted with a PLC and a virtual plant. Wrong output backward tracking algorithm is proposed in order to find the external faults of PLC. And query with keywords of the fault systems and specially designed test sequence programs are used. We lay emphasis on the backward tracking algorithm to diagnose the faults of PLC. It is shown experimentally that the proposed algorithm can find the faults which a typical self diagnostics in the-commercially available PLC cannot.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2006년도 제26회 춘계학술대회논문집
• /
• pp.218-221
• /
• 2006

가스터빈 엔진의 높은 신뢰성과 운용비의 최소화는 제작자나 사용자 모두에게 중요한 문제이며, 정성적, 정량적 성능저하 예측을 포함한 다양한 성능진단기법이 시도되고 있다. 탈설계점에서의 성능진단은 설계점 성능진단에 비해 학습, 또는 처리해야 할 데이터 규모가 방대함에 따라 예측오차와 수렴도면에서 해결되어야 할 문제점들을 안고 있다. 따라서 이를 위해 본 연구에서는 가스경로해석 기법을 적용한 엔진성능진단코드를 개발하였으며, 이를 스마트 무인기용 터보축 엔진에 적용하여 설계점 및 고도 변화에 따른 탈설계점 영역에 대하여 단일 성능저하를 정량적으로 예측하여 GSP를 통한 예측결과와 비교하였다.

• Journal of Power Electronics
• /
• 제18권5호
• /
• pp.1567-1576
• /
• 2018

The reliability of grid-connected inverters can be improved by algorithms capable of diagnosing faults in LCL filters. A fault diagnostic method during inverter startup is proposed. The proposed method can accurately generate and monitor information on the peak value and the location of the peak frequency component of the step response of a damped LCL filter. To identify faults, the proposed method compares the evaluated response with the response of a healthy higher-order damped LCL filter. The frequency components in the filter voltage response are first analytically obtained in closed form, which yields the expected trends for the filter faults. In the converter controller, the frequency components in the filter voltage response are computed using an appropriately designed fast Fourier transform and compared with healthy LCL response parameters using a finite state machine, which is used to sequence the proposed startup diagnostics. The performance of the proposed method is validated by comparing analytical results with the simulation and experimental results for a three-phase grid-connected inverter with a damped LCL filter.

• Journal of Electrical Engineering and Technology
• /
• 제11권1호
• /
• pp.29-37
• /
• 2016

Fast and accurate fault diagnosis of the position sensor is of great significance to ensure the reliability as well as sensor fault tolerant operation of the Switched Reluctance Wind Generator (SRWG). This paper presents a fault diagnostic scheme for a SRWG based on the residual between the estimated rotor position and the actual output of the position sensor. Extreme Learning Machine (ELM), which could build a nonlinear mapping among flux linkage, current and rotor position, is utilized to design an assembled estimator for the rotor position detection. The data for building the ELM based assembled position estimator is derived from the magnetization curves which are obtained from Finite Element Analysis (FEA) of an SRWG with the structure of 8 stator poles and 6 rotor poles. The effectiveness and accuracy of the proposed fault diagnosis method are verified by simulation at various operating conditions. The results provide a feasible theoretical and technical basis for the effective condition monitoring and predictive maintenance of SRWG.