• 한국정보통신학회논문지
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• 제7권6호
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• pp.1291-1296
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• 2003

본 연구는 3상 소형 유도전동기의 고정자 권선 고장의 효과적인 진단을 위하여 고정자 전류에 대하여 Park's Vector 기법을 적용하였다. 본 기법은 고정자 3상 전류를 측정하여 Park's vector 변환을 통하여 직축, 횡축 전류로 변환하고, 이를 이용하여 고장 진단을 위한 Park's Vector Pattern을 얻어 정상 상태 패턴과 고장 권선 패턴을 비교하였다. 고정자 권선 한 상에 2턴, 10턴, 그리고 20 턴의 단락고장을 발생시켜 정격부하의 25%, 50%, 100% 부하변동에 따른 각각의 Park's Vector Pattern을 비교하여 얻은 실험 결과는 제안한 방법의 유용성을 보여준다.

• Journal of Power Electronics
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• 제17권4호
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• pp.972-982
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• 2017

The Park's vector of stator current is a popular technique for the detection of induction motor faults. While the detection of the faulty condition using the Park's vector technique is easy, the classification of different types of faults is intricate. This problem is overcome by the Multiple Park's Vector (MPV) approach proposed in this paper. In this technique, the characteristic fault frequency component (CFFC) of stator winding faults, rotor winding faults, unbalanced voltage and bearing faults are extracted from three phase stator currents. Due to constructional asymmetry, under the healthy condition these characteristic fault frequency components are unbalanced. In order to balanced them, a correction factor is added to the characteristic fault frequency components of three phase stator currents. Therefore, the Park's vector pattern under the healthy condition is circular in shape. This pattern is considered as a reference pattern under the healthy condition. According to the fault condition, the amplitude and phase of characteristic faults frequency components changes. Thus, the pattern of the Park's vector changes. By monitoring the variation in multiple Park's vector patterns, the type of fault and its severity level is identified. In the proposed technique, the diagnosis of faults is immune to the effects of unbalanced voltage and multiple faults. This technique is verified on a 7.5 hp three phase wound rotor induction motor (WRIM). The experimental analysis is verified by simulation results.

• 제어로봇시스템학회논문지
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• 제20권4호
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• pp.408-413
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• 2014

In this paper, we propose a fault diagnosis method based on Park's Vector Approach using the Euler's theorem. If we interpreted it as Euler's theorem, it is possible to easily find the phase angle difference between the healthy condition and the fault condition. And, we analyzed the variation of the phase angle and performed the diagnostic method of the induction motor using feature vectors that were obtained by using a Fourier transform. The analysis of time and speed variation of the motor was performed and, as a result, we could find more soft variations than rough variations. In particular, the analysis of the distortion through each phase shows that two-turn and four-turn shorted motors are linearly separable. In this experiment, we know that the maximum breakdown threshold value for determining steady-state fault detection is 49.0788. Simulation and experimental results show the more detectable than conventional method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2070-2072
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• 2003

본 연구는 3상 소형 유도전동기의 고정자 권선 고장의 효과적인 진단을 위하여 고정자 전류에 대하여 Park's Vector를 이용한 기법을 적용하였다. 본 기법은 고정자 3상 전류를 측정하여 Park's vector 변환을 통하여 직축, 횡축 전류로 변환하고 이를 이용하여 고장 진단을 위한 Park's Vector Pattern을 통하여 고장진단을 수행하였다. 제안한 방법의 유용성을 확인하기 위하여 고정자 권선 한 상에 2턴, 10턴, 그리고 20턴의 단락고장을 발생시켜 정격부하의 25%, 50%, 100%에 대하여 부하변동에 따른 각각의 단락고장의 경우와 정상 전동기의 Park's Vector Pattern 비교하였으며 그 유용성을 확인하였다.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.559-568
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• 2014

Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The studies of induction motor behavior during abnormal conditions and the possibility to diagnose different types of faults have been a challenging topic for many electrical machine researchers. In this regard, an efficient and new method to detect the induction motor-fault may be the application of the Time Synchronous Averaging (TSA) to the stator current Park's Vector. The aim of this paper is to present a methodology by which defects in a three-phase wound rotor induction motor can be diagnosed. By exploiting the cyclostationarity characteristics of electrical signals, the TSA method is applied to the stator current Park's Vector, allowing the monitoring of the induction motor operation. Simulation and experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the hybrid Park's Vector-TSA approach.

• 전기전자학회논문지
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• 제26권1호
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• pp.104-110
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• 2022

본 논문에서는 UAV의 BLDC 모터 진단방법과 AI진단을 위한 새로운 데이터 셋을 제안하였다. BLDC모터 진단에 있어서 PVA(Park's Vector Approach)는 주파수 성분의 많은 리플로 인해 적용이 어려움이 따르나, 리플의 성분이 3조파를 띄고 있음에 따라 3조파에 뛰어난 SG(Savitzky-Golay)필터를 적용하여 Circle fitting으로 PVA를 활용하는 방법을 제안하였다. 한편, 3상에서 2상으로 변환시키는 기법인 PVA는 변환과정 중 항상 원점을 기준으로 두게 된다. 이에 Circle fitting의 적용과정에서 원점과 측정된 중심점의 오차를 측정하여 고장진단이 가능하도록 하였다. 또한, 이때 측정된 오차의 offset 데이터 기반으로 AI기술의 새로운 데이터 셋으로 활용 가능함을 실험을 통해 입증하였다.

• 한국생산제조학회지
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• 제19권5호
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• pp.589-595
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

• 한국생산제조학회지
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• 제19권4호
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• pp.469-475
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• 2010

The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

• 산업기술연구
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• 제21권A호
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• pp.167-179
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• 2001

This paper discusses an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, we suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multi-dimensional index using a feature vector as indexing attributes. For query precessing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verily the superiority of our method, we perform extensive experiments. The results reseal that our method achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Asia pacific journal of information systems
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• 제21권2호
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• pp.43-58
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• 2011

Support vector machines (SVMs), a machine learning technique, has been applied to not only binary classification problems such as bankruptcy prediction but also multi-class problems such as corporate credit ratings. However, in general, the performance of SVMs can be easily worse than the best alternative model to SVMs according to the selection of predictors, even though SVMs has the distinguishing feature of successfully classifying and predicting in a lot of dichotomous or multi-class problems. For overcoming the weakness of SVMs, this study has proposed an approach for selecting features for multi-class SVMs that utilize the impurity measures of classification trees. For the selection of the input features, we employed the C4.5 and CART algorithms, including the stepwise method of discriminant analysis, which is a well-known method for selecting features. We have built a multi-class SVMs model for credit rating using the above method and presented experimental results with data regarding S&P 500 companies.