• Tribology and Lubricants
• /
• v.18 no.2
• /
• pp.117-126
• /
• 2002

Abstract - An integrated condition monitoring algorithm based on an expert system was implemented in this work in order to monitor effectively the machine conditions. The knowledge base was consisted of numeric data which meant the posterior probability of each measurement parameter for the representative machine failures. Also the inference engine was constructed as a series of statistical process, where the probable machine fault was inferred by a mapping technology of pattern recognition. The proposed algorithm was, through the user interface, applied for an air compressor system where the temperature, vibration and wear properties were measured simultaneously. The result of the case study was found fairly satisfactory in the diagnosis of the machine condition since the predicted result was well correlated to the machine fault occurred.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.3
• /
• pp.65-78
• /
• 2013

To analyze influences under open fault conditions in switching devices, an integrated simulation and condition monitoring scheme for a permanent magnet synchronous generator (PMSG) based variable speed grid-connected wind turbine system are presented. Among various faults in power electronics components, the open fault in switching devices may arise when the switches are destructed by an accidental over current, or a fuse for short protection is blown out. Under such a faulty condition, the grid-side inverter as well as the generator-side converter does not operate normally, producing an increase of current harmonics, and a reduction in output and efficiency. As an effective way for a condition monitoring of generation system by online basis without requiring any diagnostic apparatus, the estimation schemes for generated voltage, flux linkage, and stator resistance are proposed and the validity of the proposed scheme is proved through comparative simulations.

• Journal of Advanced Marine Engineering and Technology
• /
• v.30 no.2
• /
• pp.253-259
• /
• 2006

There is few study which automatically diagnoses the fault from ship's monitored data. The bigger control and monitoring system is. the more important fault diagnosis and maintenance is to reduce damage caused by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault from monitored data and is composed of fault detection knowledge base and fault diagnosis knowledge base. For all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem, To verify capability of fault detection, diagnosis and prediction, FMS(Fault Management System) is developed by C++. Simulation by FMS is carried out with population data set made by the log book data of 2 months duration from a large full container ship of H shipping company.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2005.06a
• /
• pp.251-256
• /
• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.6 s.38
• /
• pp.37-46
• /
• 2005

In Processing many operations based on distributed environment, it is very important to support the reliability of resources. Providers of resources generally adapt the structure of server-replication to support the reliability of services. Tn server side, it maintains replicas. duplicated server objects. In the structure of this replication, service of stable replica is very important. Therefore the structure to diagnosis the fault of such replica is required. In this Paper, we suggested an effective PUSH fault management algorithm based on PUSH monitoring style of CORBAto overcome weak points of the PULL monitoring style of the replication management system in the distributed object system. Outcomes of the suggested PUSH fault monitoring style were better than other system. We confirmed valuable result in the workloads and timeout-rates.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.228-232
• /
• 1993

This paper describes a on-line monitoring and fault diagnosis system designed for the automation of a medium-size concrete plant. The system is based on the structure of a hardware system of data acquisition and a personal computer. Simulation results are presented to illustrate the system operation. It applies the preconstructed rules to the plant data for the diagnosis of weighing processes.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.487-497
• /
• 2008

This paper addresses the Fault Monitoring System developed by Hyundai-Rotem based on the Mil-HDBK-2155 Failure Reporting, Analysis and Corrective Action System. The purpose of a FRACAS is to provide a documented history of any problems, failures, their associated corrective actions as well as detailing how and why each problem arose or failure occurred during the Warranty Period for Rolling Stock delivered by Hyundai-Rotem. The Fault Monitoring System can assess the reliability, availability and maintainability as well as can predict no. of failure at a time which can input to Life Cycle Cost.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.1
• /
• pp.49-53
• /
• 2008

A fuzzy inference logic system is proposed for gas turbine engine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. The fuzzy inference logic uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. Inputs to the fuzzy inference logic system are measurement deviations of gas path parameters which are transferred directly from the ECM(Engine Control Monitoring) program and outputs are engine module faults. The proposed fuzzy inference logic system is tested using simulated data developed from the ECM trend plot reports and the results show that the proposed fuzzy inference logic system isolates module faults with high accuracy rate in the environment of high level of uncertainty.

• Journal of Advanced Marine Engineering and Technology
• /
• v.28 no.8
• /
• pp.1291-1298
• /
• 2004

In development of monitoring and control systems, one of the most important points is to consider a redundancy so that the system can be operated normally although hardware faults are partly occurred. The purpose of this paper is to introduce a monitoring and control system with a redundancy function for I/O servers and communication networks. I/O servers composed with an active server and a standby server. Each server also has 3 communication ports, 2 ports of them were connected to field units and the other 1 port was connected to the other server. Field units have to be constructed to 2 communication ports connected I/O servers through communication lines. Also, server communication module was implemented for analyzing and handling fault elements. and was submodularized for linking easily with a monitoring and control module. An experiment with 2 servers and 2 field units was constructed to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
• /
• 2007.04c
• /
• pp.46-48
• /
• 2007

This paper presents research about improvement of fault detection algorithm in FRTU on the feeder of distribution system. FRTU(Feeder Remote Terminal Unit) is applied to fault detection schemes for phase fault, ground fault, and cold load pickup and Inrush restraint functions distinguish the fault current and the normal load current. FRTU is occurred FI(Fault Indicator) when current is over pick-up value also inrush current is occurred FRTU indicate FI. Discrete wavelet transform(DWT) analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate inrush current from the fault status by a gradient descent method. In this paper, fault detection is improved using voltage monitoring system with DWT and neural network. These data were measured in actual 22.9kV distribution system.