• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제16권3호
• /
• pp.173-180
• /
• 2016

Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

• 전기학회논문지
• /
• 제59권9호
• /
• pp.1673-1679
• /
• 2010

A photovoltaic (PV) generator is significantly regarded as one important alternative of renewable energy systems recently. Fault detection and diagnosis of engineering dynamic systems is a fundamental issue to timely prevent unexpected damages in industry fields. This paper presents an intelligent monitoring approach and fault detection technique for PV generator systems by means of artificial neural network and statistical signal detection theory. We devise a multi-Fourier neural network model for representing dynamics of PV systems and apply a general likelihood ratio test (GLRT) approach for investigating our decision making algorithm in fault detection and diagnosis. We make use of a test-bed of ubiquitous sensor network (USN) based PV monitoring systems for testing our proposed fault detection methodology. Lastly, a real-time experiment is accomplished for demonstrating its reliability and practicability.

• 제어로봇시스템학회논문지
• /
• 제4권5호
• /
• pp.666-673
• /
• 1998

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 test and GLR(General likelihood ratio) test are applied for fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

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

• 대한설비공학회:학술대회논문집
• /
• 대한설비공학회 2008년도 하계학술발표대회 논문집
• /
• pp.103-108
• /
• 2008

Automatic control makes the air-handling unit go into operation and determines the functions of high-efficient and energy-saving machines. Yamatake, an automatic control system manufacturer, have expanded fault detection and diagnosis, and data volumes so as to achieve higher technology in control by developing a sensor which makes field data visible, an actuator and Intelligent Conponent. This study, thus, focuses on applications for saving energy with Intelligent Conponent and goes in for easing global warming by creating future field data-based applications.

• 한국전자통신학회논문지
• /
• 제11권1호
• /
• pp.59-64
• /
• 2016

본 논문에서는 주택의 전기화재 방지를 위해 아크고장전류로부터 아크 진단 기능을 가지는 지능형 분전반이 개발된다. 지능형 분전반의 주 제어장치는 단상전력관리를 지원하는 단상 전력관리 장치와 아크전류로부터 아크 고장을 진단하기 위한 아크 진단 장치로 구성된다. 본 논문에서는 단상 전력관리 장치와 아크진단장치의 시작품이 설계, 제작되며, 전기화재의 원인을 분전반으로부터 원격 서버 시스템에 전송하기 위해서 주제어장치와 아크 고장 진단 장치와의 연동기능이 개발된다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 B
• /
• pp.677-679
• /
• 1999

This paper introduces a implementation of fault detection for national highway line 3. Fault detection system was installed and operated on national highway line 3, environmental elements caused by abnormal status or faults has often happened. Therefore, the function of fault detection system is to speedy notify fault site, cause as well as scale of fault to manager. Though the fault detection and diagnosis system has been imported in the field of process of water and electric power, it is just beginning step in the field of ITS(Intelligent Transportation Systems). In general, Maintenance system is performed the online/offline process of detection, diagnosis and measure. This paper is studied online detection process, which is realtime remote detection.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제7권2호
• /
• pp.102-108
• /
• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제9권2호
• /
• pp.99-104
• /
• 2009

The turn-to-turn short is one major fault of the motor faults of BLDC motors and can appear frequently. When the fault happens, the motor can be operated without breakdown, but it is necessary to maintain the motor for continuous working. In past research, several methods have been applied to detect winding faults. The representative approaches have been focusing on current signals, which can give important information to extract features and to detect faults. In this study, current sensors were installed to measure signals for fault detection of BLDC motors. In this study, the Park's vector method was used to extract the features and to isolate the faults from the current measured by sensors. Because this method can consider the three-phase current values, it is useful to detect features from one-phase and three-phase faults. After extracting two-dimensional features, the final feature was generated by using the two-dimensional values using the distance equation. The values were used in fuzzy similarity to isolate the faults. Fuzzy similarity is an available tool to diagnose the fault without model generation and the fault was converted to the percentage value that can be considered as possibility of the fault.

• 대한전기학회논문지:전력기술부문A
• /
• 제49권10호
• /
• pp.516-523
• /
• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.