• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.285-285
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• 2000

A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paper describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.12
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• pp.1227-1236
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• 2012

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.276-280
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• 2016

Due to the increasing interest in safety and consistent product quality over a past few decades, demand for effective quality monitoring and safe operation in the modern industry has propelled research into statistical based fault detection and diagnosis methods. This paper describes the application of Hotelling $T^2$ index based Principal Component Analysis (PCA) method for fault detection and diagnosis in industrial processes. Multivariate statistical process control techniques are now widely used for performance monitoring and fault detection. Conventional methods such as PCA are suitable only for steady state processes. These conventional projection methods causes false alarms or missing data for the systems with transient values of processes. These issues significantly compromise the reliability of the monitoring systems. In this paper, a reliable method is used to overcome false alarms occur due to varying process conditions and missing data problems in transient states. This monitoring method is implemented and validated experimentally along with matlab. Experimental results proved the credibility of this fault detection method for both the steady state and transient operations.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.5
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• pp.520-526
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• 2013

As the increasing of capacity and technology of power facilities, rotating machines are getting higher at capacity and voltage scale. Thus the monitoring and diagnosis of generators for fault detection has attracted intensive interest. In this paper, we developed fault diagnosis system for monitoring the fault operations in bad power systems. In order to verify the performance of this fault diagnosis system, we made the small scaled testing system which has the same winding structure of the real synchronous generator. The magnetic flux patterns in air-gap of a small-scale generator under various fault states as well as a normal state are tested by hall sensors and the fault detection system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.6
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• pp.52-60
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• 2003

In aviation navigation using GPS, requirements on availability and integrity must be absolutely satisfied. Current study on accomplishing this integrity includes RAIM(Receiver Autonomous Integrity Monitoring), monitoring integrity internaIly in GPS receiver itself. Parity space technique as one of RAIM techniques has shown the advantages in fault detection and isolation due to each use of its magnitude and direction under the assumption of one fault. ln case of multiple fault, as biases in errors interact decreasing the effect of multiple fault in parity space, the exact fault detection and identification(FDI) may be difficult to be conducted. This paper focuses on FDI study on two faults and explains why parity space techniques applied on single fault is not adequate to the application of multiple fault case and shows that extended parity space technique may improve the performance of RAIM on two faults.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.345-349
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• 2007

In this study a fuzzy trend monitoring method for detecting the engine mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration. etc. Using engine condition data set as a input which generated by linear regression analysis of real engine instrument data, an application of fuzzy logic in diagnostics estimate a cause of fault in each components.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.39-49
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• 2009

Nowadays, according to rapid development of computing environments, information processing and analysis system are very interesting research area. As a viewpoint of data preparation-processing-analysis in knowledge technology, the goal of automated information system is to satisfy high reliability and confidence and to minimize of human-administrator intervention. In addition, we expect the system which can deal with problem and abnormal error effectively as a fault detection and fault tolerance. In this paper, we design a monitoring system as follows. A productive monitoring information from various systems has unstructured forms and characteristics and crawls informative data by conditions and gathering rules. For representing of monitering information which requested by administrator, running-status can be able to check dynamically and systematic like connection/closed status in real-time. Our proposed system can easily correct and processing for monitoring information from various type of server and support to make objective judgement and analysis of administrator under operative target of information system. We implement semi-realtime monitering system using AJAX technology for dynamic browsing of web information and information processing using XML and XPATH. We apply our system to SMS server for checking running status and the system shows that has high utility and reliability.

• Journal of the Korean Solar Energy Society
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• v.38 no.3
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• pp.21-28
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• 2018

The objects of PV (Photovoltaic) monitoring system is to reduce the loss of system and operation and maintenance costs. In case of PV plants with configured of centralized inverter type, only 1 PV module might be caused a large loss in the PV plant. For this reason, the monitoring technology of PV module-level that find out the location of the fault module and reduce the system losses is interested. In this paper, a fault diagnosis algorithm are proposed using thermal and electrical characteristics of PV modules under failure. In addition, the monitoring system applied with proposed algorithm was constructed. The wireless sensor using LoRa chip was designed to be able to connect with IoT device in the future. The characteristics of PV module by shading is not failure but it is treated as a temporary failure. In the monitoring system, it is possible to diagnose whether or not failure of bypass diode inside the junction box. The fault diagnosis algorithm are developed on considering a situation such as communication error of wireless sensor and empirical performance evaluation are currently conducting.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.57-71
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• 2001

Global competition to increase production output and to improve quality is spurring manufacturing companies to use condition monitoring and fault diagnostic systems for predictive maintenance. As monitoring, testing, and measuring techniques develop, predictive control of components and complete systems have become more practical and affordable. In this article, we will consider the computer based data acquisition system for condition monitoring and the condition parameter analysis techniques for fault detection and diagnostics in the machinery and briefly discuss reliability prediction and the limit value determination in condition monitoring.

• The Journal of Information Technology
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• v.7 no.4
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• pp.61-69
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• 2004

On-line monitoring of fault discharge is an important approach for indicating the condition of electrical insulation of stator winding in high voltage motor. In this paper, several key aspects of on-line monitoring system are discussed, involving the characteristics of fault discharge of stator winding in high voltage motor, spectrum analysis of four simulation fault signals, feature extraction of internal fault discharge from apply voltage to breakdown. The study of the partial discharge activities allows to highlight the ageing stage in the winding fault under test. During the life of the winding insulation fault, the shape of PD signal change relating to the ageing stage. The ageing of stator winding insulation fault of high voltage motor is investigated based on the characteristics of partial discharge pulse distribution and statistical parameters, such as maximum, skewness and kurtosis using discrete wavelet trnasform coefficients.