• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2009년도 제40회 하계학술대회
• /
• pp.2041_2042
• /
• 2009

The diagnostic/prognostic problems for condition based maintenance or Prognostics and Health Management has been used. Primary objectives of diagnosis/prognosis are maximizing system availability and minimizing downtime from fault isolation through more effective troubleshooting efforts. Diagnosis aims to detect the onset of failures to improve system performance and reduce life cycle cost by reducing the failure time. The prognosis can reduce operational and support total ownership cost and improve safety of machinery and complex systems. In this Paper, a fault diagnosis methodology has been described using a monopropellant propulsion system model as a test bench.

• 한국소음진동공학회논문집
• /
• 제24권9호
• /
• pp.675-681
• /
• 2014

This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.

• 전기학회논문지P
• /
• 제58권4호
• /
• pp.432-436
• /
• 2009

This paper is described that advanced study on network design of remote diagnosis system for power facilities of electric railway. In the field, it is very difficult for worker to diagnosis power facilities including catenary because workers should be maintenance on AC power supply. Therefore, to properly design on remote diagnosis system, we have searched the inside and outside of the country-related technology trends. Also we confirmed that required technologies to design interface technology required for the development of sensor devices and the USN network was designed in accordance with required skills. Throughout variety of requirements, we have development iRFS based ZA sensors and iRFM to receive data of sensor. Also CC2420 is applied as single-chip which used 2.4GHz IEEE802.15.4 compliant RF tranciver designed for low-power and low-voltage wireless applications for ZigBee communication.

• Journal of information and communication convergence engineering
• /
• 제15권2호
• /
• pp.85-90
• /
• 2017

Expert systems for health diagnosis are only for medical experts who have deep knowledge in the field but we need a self-checking pre-diagnosis system for preventive public health monitoring. Korea Traditional Medicine is popular in use among Korean public but there exist few available health information systems on the internet. A computerized self-checking diagnosis system is proposed to reduce the social cost by monitoring health status with simple symptom checking procedures especially for Korea Traditional Medicine users. Based on the national reports for disease/symptoms of Korea Traditional Medicine, we build a reliable database and devise an intelligent inference engine using fuzzy c-means clustering. The implemented system gives five most probable diseases a user might have with respect to symptoms given by the user. Inference results are verified by Korea Traditional Medicine doctors as sufficiently accurate and easy to use.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1997년도 추계학술대회 논문집
• /
• pp.442-445
• /
• 1997

A challenging activity in the manufacturing industry is to perform in real time the continuous monitoring of the process state, the situation assessment and identification of the problem on line and diagnosis of the cause and importance of the problem if he process does not work properly. This paper describes LAT(Ladder Analysis Tool) system for fault tree generation to improving the fault diagnosis of CNC machine tools. The system consists of 4 steps which can automatically ladder analysis from ladder diagram to two diagnosis function models. The two diagnostic models based on he ladder diagram is switching function model and step switching function model. This system tries to overcome diagnosis deficiencies present machine tool.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2003년도 춘계학술대회 논문집
• /
• pp.430-433
• /
• 2003

Air-operated valve is one of principal valves that are using to control fluid flow. A period diagnosis for safety of power plants is necessary. But there are many difficulties such as economic loss caused by intone of high cost devices and a matter hard to deal with users. In this study we developed the diagnosis system that usersofpower plants are easy to handle. The diagnosis system is composed of database module, reliability analysis module, design safety nodule and diagnosis test and evaluation module.

• 전기학회논문지
• /
• 제56권12호
• /
• pp.2084-2090
• /
• 2007

The DGA (Dissolved Gases Analysis) technique has been widely using for fault diagnosis of the power transformers. Some electric power utility company establishes the criteria of DGA to improve reliability, because of difference of operation environment and design of power transformer. In this paper, we introduce intelligent diagnosis system for DGA result of KEPCO (Korea Electric Power Cooperation). This system can classify patterns type of gases ratio that frequently occurs in recent result of gases analysis using Fuzzy Inference. The classification of Patterns let us know that major causes of gases generation based on type of patterns. Finally, Neural Network based on patterns diagnose transformer. NN was trained using result data of DGA of actually faulted transformers recently. Result of intelligent diagnosis system is right well in comparison with actual inner inspection of transformers.

• 한국해양공학회:학술대회논문집
• /
• 한국해양공학회 2001년도 춘계학술대회 논문집
• /
• pp.32-37
• /
• 2001

This paper describes a noble fault diagnosis method using inter node search technique in PN model. First, a complicated fault system is modeled as PN graphic expressions. Next, to find out sources for faults on which we focus, the PN model is analyzed using the backward chaining of T-invariance. In this step, the technique of inter node search is applied for reducing some range of sources in a fault. Also, colnposing method of incidence matrix in PN is proposed. Then, it makes the diagnosis system to very flelible system because new knowledges about the sources in a fault can be added easily to conventional systems. Finally, the proposed method is applied to the automobile trouble diagnosis system to confirm the validity of the method.

• 대한전기학회논문지:전력기술부문A
• /
• 제52권2호
• /
• pp.99-106
• /
• 2003

In this paper, an intelligent fault location and diagnosis system is proposed. The proposed system identifies the fault location in two-step procedure. The first step identifies candidates of fault location using an fault distance calculation using an iterative method. The second step is diagnosis the actual fault location in the candidates by comparing the current waveform patterns with the expected operation of the protective devices and considering the interrupted load after the operation protective device. The simulations results in the case study demonstrates a good performance of the proposed fault location and diagnosis system.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2003년도 추계학술대회 논문집(III)
• /
• pp.529-534
• /
• 2003

Within industry induction motors have a broad application area to drive pumps, fans, elevators and electric trains. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motor's supply current, since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.