• 한국산학기술학회논문지
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• 제15권9호
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• pp.5474-5479
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• 2014

본 연구는 중형 유도전동기 신제품 개발 단계에서 브라켓 주조품 제작시 발생하는 품질문제를 미리 평가하기 위하여 수행한 것으로, 브라켓 주조품의 제작과정인 주조 및 기계가공시 용탕 충진 양상, 결함 발생, 잔류응력 및 변형 등 제품의 품질상태를 수치해석적인 방법을 사용하여 평가하였다. 평가 결과 최종 기계가공 후 브라켓 주조품에 발생하는 잔류응력은 -53~54MPa, 변형량은 최대 1.8mm로 크지 않으며 내부 품질관리 기준에 부합함을 알 수 있었다.

• Journal of Power Electronics
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• 제18권2호
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• pp.492-501
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• 2018

In the rotor-flux oriented control used in induction motors, the electrical parameters of the motors should be identified. Among these parameters, the mutual inductance and rotor resistance should be accurately tuned for better operations. However, they are more difficult to identify than the stator resistance and stator transient inductance. The rotor resistance and mutual inductance can change in operations due to flux saturation and heat generation. When detuning of these parameters occurs, the performance of the control is degenerated. In this paper, a novel method for the concurrent identification of the two parameters is proposed based on recursive least square estimation and model reference adaptive control.

• Journal of Electrical Engineering and information Science
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• 제3권1호
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• pp.86-93
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• 1998

In this paper, we propose an effective on-line identification method for rotor resistance, which is useful in making speed control of induction motors without rotational transducers robust with respect to the variation in rotor resistance. Our identification method for rotor resistance is based on the linearly perturbed equations of the closed-loop system for sensorless speed control about th operating point. Our identification method for rotor resistance uses only the information of stator currents and voltages. In can provide fairly good identification accuracy regardless of load conditions. Some experimental results are presented to demonstrate the practical use of our identification method. For our experimental work, we have built a sensorless control system, in which all algorithms are implemented on a DSP. Our experimental results confirm that our on-line identification method allows for high precision speed control of commercially available induction motors without rotational transducers.

• 한국소음진동공학회논문집
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• 제14권11호
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• pp.1091-1100
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• 2004

This paper presents an approach for the monitoring and detection of faults in induction machine by using data fusion technique and Dempster-Shafer theory Features are extracted from motor stator current and vibration signals. Neural network is trained and Hosted by the selected features of the measured data. The fusion of classification results from vibration and current classifiers increases the diagnostic accuracy. The efficiency of the proposed system is demonstrated by detecting motor electric and mechanical faults originated from the induction motors. The results of the test confirm that the proposed system has potential for real time application.

• Journal of international Conference on Electrical Machines and Systems
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• 제2권1호
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• pp.45-50
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• 2013

This paper presents design of induction motor in very low temperature for LNG main cargo pump and comparison of two motors. One is the motor for using in room temperature and another is the motor for using very low temperature. This paper designs with Equivalent circuit Method and uses Finite Element Method to analysis. The motor for very low temperature considers variation of coil resistivity due to temperature change and compare torque characteristic with the motor for room temperature. Design element of motor for very low temperature considers resistivity variation following temperature change on going through this paper. The result shows that two types of motors are almost same torque curve characteristic even though they are not the same environment.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.54-59
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• 2006

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for these data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1503-1504
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• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1505-1506
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• 2008

In this paper, a robust adaptive backstepping control is developed for efficiency optimization of induction motors with uncertainties. The proposed control scheme consists of efficiency flux control(EFC) using a sliding mode adaptive flux observer and robust speed control(RSC) using a function approximation for mechanical uncertainties. In EFC, it is important to find the flux reference to minimize power losses of induction motors. Therefore, we proposed the optimal flux reference using the electrical power loss function. The sliding mode flux observer is designed to estimate rotor fluxes and variation of inverse rotor time constant. In RSC, the unknown function approximation technique employs nonlinear disturbance observer(NDO) using fuzzy neural networks(FNNs). The proposed controller guarantees both speed tracking and flux tracking. Simulation results are presented to illustrate the effectiveness of the approaches proposed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.549-555
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• 2003

The technology of machine condition monitoring is used effectively to detect the machine faults at an early stage using different machine quantities, such as current, voltage, temperature and vibration. Induction motors are most widely used to drive pumps, compressors and fans in industrial drives. This paper presents approach to data fusion using Dempster-Shafer theory because only one technique has uncertainty. So we can obtain advanced accuracy of the machine fault diagnosis. Vibration and current quantities are applied to diagnose three-phase induction motor.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.303-306
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• 1994

This paper presents a new rotor resistance identification algorithm for induction motors. The algorithm is derived form the fact that the slip frequency given in the d-q rotating frame is equal to that measured in the x-y fixed frame. Rotor resistance varies greatly with the machine temperature. In certain cases, the rotor resistance can increase 100 % over its ambient or nominal value. This deteriorates the dynamic performance of vector control systems for induction motors. However, the control scheme proposed in this paper is robust with respect to variations in rotor resistance because an efficient identification algorithm for rotor resistance is employed. To illuminate the performance of the proposed controller further, the simulation results are presented.