• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.716-722
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• 2014

In order to design the speed controller of the DC motor system, firstly, parameters estimation of the system must be preceded. In this paper, we proposed the application of genetic algorithm(GA) optimization in estimating the parameters of DC motor. Estimated models are considered both first and second order models, and each estimated model is optimized by minimizing three different types of the evaluation function of GA. Also, GA is imported in comparison with estimation result of numerical analysis method because of its power in searching entire solution space with more probability of finding the global optimum. Data for parameter estimation is acquired from input and output signals of the actual experiment device and the butterworth filter also designs for removing noise in the signals. Finally comparison between real data of the actual device and estimated models is presented to indicate effectiveness and resolution of proposed identification method.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.332-345
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• 2013

In this paper, recently, it is described to the piezoelectric transformer technology develops, because it was have to favorable characteristics such as electromagnetic-noise free, compact size, higher efficiency, and superior power density, flux linkage, noiseless, etc. its resonance frequency was used to output waveform of a sine wave. A rotor speed identification method of induction motor based on the theory of flux model reference adaptive system(FMRAS). The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the model are introduced to perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM techniuqe and DC-DC converter. High speed calculation and processing for vector control is carried out by digital signal one chip microprocessor. Validity of the proposed control method is verified through simulation and experimental results.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.17-24
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• 2014

This paper proposes a fault detection method for low-speed rolling element bearings of an induction motor using acoustic emission signals and histogram modeling. The proposed method performs envelop modeling of the histogram of normalized fault signals. It then extracts and selects significant features of each fault using partial autocorrelation coefficients and distance evaluation technique, respectively. Finally, using the extracted features as inputs, the support vector regression (SVR) classifies bearing's inner, outer, and roller faults. To obtain optimal classification performance, we evaluate the proposed method with varying an adjustable parameter of the Gaussian radial basis function of SVR from 0.01 to 1.0 and the number of features from 2 to 150. Experimental results show that the proposed fault identification method using 0.64-0.65 of the adjustable parameter and 75 features achieves 91% in classification performance and outperforms conventional fault diagnosis methods as well.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.376-382
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• 2014

E-Actuator is an essential part of an eVGT, it receives the command from the main ECU and controls the vane. An e-Actuator failure can cause an abrupt change in engine output and it may induce an accident. Therefore, it is required to detect anomalies in the e-Actuator in real time to prevent accidents. In this paper, an e-Actuator fault detection method using on-line parameter identification is proposed. To implement on-line fault detection algorithm, many constraints are considered. The test input and sampling rate are selected considering the constraints. And new recursive system identification algorithm is proposed which reduces the memory and MCU power dramatically. The relationship between the identified parameters and real elements such as gears, spring and motor are derived. The fault detection method using the relationship is proposed. The experiments with the real broken gears show the effectiveness of the proposed algorithm. It is expected that the real time fault detection is possible and it can improve the safety of eVGT system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.4
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• pp.730-738
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• 2007

As well known when the linear machine is operated between two points repeatedly under positioning control, there are various positioning error at the moment of zero speed owing to the non-linear disturbance like as unpredictable friction force. To remove this positioning error, a simple least order disturbance observer is introduced and is actually implemented in this study. Due to this simple algorithm the over-all machine system can be modified to simple arbitrary given one-mass load without any disturbance. So, the total construction process for positioning control system is much easier than old one. Moreover, to generate a proper effective position profile with the limited actual machine force, a very powerful on-line mass identification algorithm using the load force estimator is presented. In the proposed mass identification algorithm, the exact load mass can be calculated during only one moving stage under a normally generated position profile. All presented algorithm is verified with experimental result with commercial linear servo machine system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.2
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• pp.161-169
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• 2004

This paper deals with system identification of a three-story building model with active mass damper (MID) for the controller design. Observer Kalman filter identification (OKID) technique is applied to find the relationship between the experimental results of the input and output. The inputs to the building model with MID are ground accelerations and motor command signal, which are, respectively, simulated earthquake and equivalent control force. The outputs are each floor acceleration and MID acceleration. The MID controller is designed based on the experimentally identified building system. Finally it is shown that experimental results agree accurately with simulated results.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.117-123
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• 2001

In a modern control field, a control engineer who has theoretical backgrounds with some practical knowledge is demanded. That is to say, an engineer who can understand and operate the various parts such as modeling, simulation, system analysis, signal processing, statistics, and hardware is required. In order to prove the theoretical backgrounds and operate various hardwares, a lot of experimental devices for students are designed in universities. Since the conventional experimental devices are manufactured abroad and the prices of the devices are too high, it is difficult to have. If a low cost experimental device can be developed, it will be very useful for a control engineering education. In Ibis paper, an experimental rig which has two control inputs and three sensor outputs to control the end point of a flexible beam is designed and manufactured. This rig can be used for a control field education.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.830-831
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• 2011

The paper makes an investigation on a speed and stator flux linkage estimator for permanent magnet synchronous motor (PMSM) sensorless drives using the technology of model reference adaptive system (MRAS). The designed estimator including two models and two adaptive estimating laws is proved to be stable by the Popov hyper-stability theory. The speed, the stator flux linkage and the resistance are estimated accurately by the proposed estimator while overcoming the shortcoming of the traditional one. The experiment results demonstrate its effectiveness.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.409-412
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• 2000

This paper investigates a novel speed identification of induction motor using 2 layer neural networks. The proposed control strategy is based on neural networks using model of full order state observer. in the proposed neural networks system the error between the desired variable and the adaptive variable is back-propagated to adjust the rotor speed, So that the adaptive variable will coincide with the desired variable. The proposed control algorithm is verified through simulation and experiment using th digital signal processor of TMS320C31