• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.40-46
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• 2000

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.110-112
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• 2009

Transient acoustic pressure in the near field of an impacted plate carries information that can be utilized for recovering the impact force history. The inverse calculation approach using BEM-based NAH, which is conventionally used for time harmonic excitation, can be applied for reconstructing the transient waves using the principle of Fourier transform and spectral analysis. Then, using the recovered velocity in normal direction of the plate surface, the corresponding structural intensity can be obtained and the identification of input power can be performed. However, several manipulations should be given to overcome numerical artifacts, such as aliasing and erratic oscillation at discontinuity, and to suppress the effect of noise. Experiment using a simply supported plate is presented for demonstration purpose.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1127-1129
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• 1997

In this paper, we developed to artificial neural network for load characteristic identification of power system. We can acquire active power and reactive power of individual load depending on the variation of voltage and frequency from the experimentation of a dynamic characteristic of load. The data of the experimental results were be used in learning of ANN. A proposed ANN model is applied to analyze the transient stability. To demonstrate the propriety of the power system transient stability with load model using ANN, the simulation of the two-machine five-bus system is carried out.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.129-133
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• 2003

The work described in this paper deals with the proposed application of an Artificial Neural Network Model for the Advanced Pressurized Water Reactor APR-1400 transient identification. The approach adopted for testing the network take note of the expectation which should be fulfilled by a network for real-time application, like testing with data in on-line mode and use of actual or real-life patterns for training. The recall test performed demonstrates that use of neural network for transient identification is indeed an attractive preposition.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.197-205
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• 2013

Real time transient stability assessment mainly depends on real-time prediction. Unfortunately, conventional techniques based on offline analysis are too slow and unreliable in complex power systems. Hence, fast and reliable stability prediction methods and simple stability criterions must be developed for real time purposes. In this paper, two new methods for real time determining critical clearing time based on clustering identification are proposed. This article is covering three main sections: (i) clustering generators and recognizing critical group; (ii) replacing the multi-machine system by a two-machine dynamic equivalent and eventually, to a one-machine-infinite-bus system; (iii) presenting a new method to predict post-fault trajectory and two simple algorithms for calculating critical clearing time, respectively established upon two different transient stability criterions. The performance is expected to figure out critical clearing time within 100ms-150ms and with an acceptable accuracy.

• Journal of computational fluids engineering
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• v.10 no.2
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• pp.69-81
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• 2005

A fluid transient analysis for the propellant flow in a monopropellant propulsion system is conducted by using the method of characteristics(MOC). It reviews algebraic simultaneous equations method and Cramer's rule method utilized to drive the compatible and characteristic equations to understand MOC extensively. The identification of fluid transient phenomena of propulsion system of Koreasat 1 is carried out through parametric studies. The valve response time is one of the dominant parameters governing the fluid transient phenomena. The results show that the shorter closing time induces the greater pressure response amplitude. And it shows that the installation of in-line orifice is effectively to limit the fluid transients in rapid valve response time and at high pressure. But it seems that the effect of orifice weakens at slow valve response time and at low pressures.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.6
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• pp.738-747
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• 1999

Vector controlled induction motor have been widely used in high performance applications. How-ever the performance is sensitive to the variations of motor parameters especially the rotor time constant which varies with the temperature and the saturation of the magnetizing inductance. In this paper the authors propose new identifying method for time-varying parameters of an induction motor which is based on adaptive vector control with serial block algorithm. Vector con-trol system realized on synchronous frame and parameter identification system realized on sta-tionary frame are not easily affected by the vector control frame. Parameter mismatch in the control system results in heavy transient variation in speed and torque response. In order to compensate degradation of the responses at the middle and low speed region adaptive identifier is introduced. To verify the feasibility of this technique compute simu-lations carried out.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1279-1289
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• 1992

Fault-tolerant system in improved the reliability and safety by using hardware and software redundancy. Fault mask and detection, identification techniques are conditionally used with system's application areas. Here DMR system is operated with standby and fail-safe module method that has minimal hardware and software redundancy, then its reliablity and safety comparison is presented respectively. Also this paper proposed an effective methods of dealing with transient faults as compared system's MTTFs to transient faults tolerance capabilities of self-diagnosis program.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.15-20
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• 2001

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability discusses a methodology to identify crucial transmission lines for stability prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system, and it shows capabilities of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.5
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• pp.271-278
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• 2003

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability, this paper discusses a methodology to identify crucial transmission lines for stability Prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a Procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system and the KEPCO systems in the year of 2003 and it shows capabilities of the proposed method