• Title/Summary/Keyword: three-phase faults

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A UML-based Approach towards Test Case Generation and Optimization

  • Shahid Saleem;Saif U. R. Malik;Bilal Mehboob;Roobaea Alroobaea;Sultan Algarni;Abdullah M. Baqasah;Naveed Ahmad;Muhammad Hasnain
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.3
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    • pp.633-652
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    • 2024
  • Software testing is an important phase as it ensures the software quality. The software testing process comprises of three steps: generation, execution, and evaluation of test cases. Literature claims the usage of single and multiple 'Unified Modeling Language' (UML) diagrams to generate test cases. Using multiple UML diagrams increases test case coverage. However, the existing approaches show limitations in test case generation from UML diagrams. Therefore, in this research study, we propose an approach to generate the test cases using UML State Chart Diagram (SCD), Activity Diagram (AD), and Sequence Diagram (SD). The proposed approach transforms UML diagrams into intermediate forms: SCD Graph, AD Graph, and SD Graph respectively. Furthermore, by integrating these three graphs, a System Testing Graph (STG) is formed. Finally, test cases are identified from STG by using a traversal algorithm such as Depth First Search (DFS) that is an optimization method. The results show that the proposed approach is better compared to existing approaches in terms of coverage and performance. Moreover, the generated test cases have the ability to detect faults at the unit level, integration, and system level testing.

Diagnosis Method for Stator-Faults in Induction Motor using Park's Vector Pattern and Convolution Neural Network (Park's Vector 패턴과 CNN을 이용한 유도전동기 고정자 고장진단방법)

  • Goh, Yeong-Jin;Kim, Gwi-Nam;Kim, YongHyeon;Lee, Buhm;Kim, Kyoung-Min
    • Journal of IKEEE
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    • v.24 no.3
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    • pp.883-889
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    • 2020
  • In this paper, we propose a method to use PV(Park's Vector) pattern for inductive motor stator fault diagnosis using CNN(Convolution Neural Network). The conventional CNN based fault diagnosis method was performed by imaging three-phase currents, but this method was troublesome to perform normalization by artificially setting the starting point and phase of current. However, when using PV pattern, the problem of normalization could be solved because the 3-phase current shows a certain circular pattern. In addition, the proposed method is proved to be superior in the accuracy of CNN by 18.18[%] compared to the previous current data image due to the autonomic normalization.

Fault Diagnosis for 3-Phase Diode Rectifier using Harmonic Ripples of DC Link Voltage (직류단 전압의 고조파 맥동 검출을 이용한 3상 다이오드 정류기의 고장 진단)

  • Park, Je-Wook;Baek, Seong-Won;Kim, Jang-Mok;Lee, Dong-Choon;Lee, Kyo-Beum
    • The Transactions of the Korean Institute of Power Electronics
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    • v.16 no.5
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    • pp.457-465
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    • 2011
  • The fault analysis and detecting algorithm for a 3 phase diode rectifier is proposed. The 3 phase dioderectifier is used for the AC power rectifier of the PWM inverter. The input power or diode faults cause theripples of the DC voltage, degradation of the control performance and life shortening of the DC link capacitor.In this paper, the ripple of the DC voltage is mathematically analyzed for the earth fault of input power andopen circuit fault of the diode, respectively. The fault detection and type of fault can be obtained by comparingthe average DC voltage and the instant DC voltage which is sampled with 6 times of grid frequency. Theproposed method can be easily applicable and doesn't require additional circuit. The experimental and simulationresults are presented to verify the validity of the proposed method.

Damping Analysis using IEEEST PSS and PSS2A PSS

  • Lee Sang-Seung;Kang Sang-Hee;Jang Gwang-Soo;Li Shan-Ying;Park Jong-Keun;Moon Seung-Il;Yoon Yong-Tae
    • Journal of Electrical Engineering and Technology
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    • v.1 no.3
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    • pp.271-278
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    • 2006
  • This paper scrutinized the damping effects of installing the prototype PSSs by a transient analysis for eight buses of faults in the South Korean power system. The PSSs used have the co-PSS blocks for IEEEST model with a single input and the co+power PSS blocks for PSS2A model with dual inputs. The simulation tool was a TSAT(Transient Security Assessment Tool) developed by Powertech Labs Inc. The voltages of the transmission line for simulations were 765kV and 345kV, and the faults for eight cases were sequenced by considering the open state and the close state of the lines. In the simulations, the three-phase line to ground (L-G) fault generated different points for each region. The simulations were compared to the cases of no PSS, partial IEEEST and PSS2A, absolute IEEEST, and absolute PSS2A to show that the power system oscillation can be effectively damped by PSS modules. Simulations were conducted to confirm the effectiveness for the KEPCO (Korea Electric Power Corporation) power system.

Development and Application of Pre/Post-processor to EMTP for Sequence Impedance Analysis of Underground Transmission Cables (지중 송전선로 대칭분 임피던스 해석을 위한 EMTP 전후처리기 개발과 활용)

  • Choi, Jong-Kee;Jang, Byung-Tae;An, Yong-Ho;Choi, Sang-Kyu;Lee, Myoung-Hee
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.10
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    • pp.1364-1370
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    • 2014
  • Power system fault analysis has been based on symmetrical component method, which describes power system elements by positive, negative and zero sequence impedance. Obtaining accurate line impedances as possible are very important for estimating fault current magnitude and setting distance relay accurately. Especially, accurate calculation of zero sequence impedance is important because most of transmission line faults are line-to-ground faults, not balanced three-phase fault. Since KEPCO has started measuring of transmission line impedance at 2005, it has been revealed that the measured and calculated line impedances are well agreed within reasonable accuracy. In case of underground transmission lines, however, large discrepancies in zero sequence impedance were observed occasionally. Since zero sequence impedance is an important input data for distance relay to locate faulted point correctly, it is urgently required to analyze, detect and consider countermeasures to the source of these discrepancies. In this paper, development of pre/post processor to ATP (Alternative Transient Program) version of EMTP (Electro-Magnetic Transient Program) for sequence impedance calculation was described. With the developed processor ATP-cable, effects of ground resistance and ECC (Earth Continuity Conductor) on sequence impedance were analyzed.

Fault Modeling and Diagnosis using Wavelet Decomposition in Squirrel-Cage Induction Motor Under Mixed Fault Condition (복합고장을 가지는 농형유도전동기의 모델링과 웨이블릿 분해를 이용한 고장진단)

  • Kim, Youn-Tae;Bae, Hyeon;Park, Jin-Su;Kim, Sung-Shin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.6
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    • pp.691-697
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    • 2006
  • Induction motors are critical components in industrial process. So there are many research in the condition based maintenance, online monitoring system, and fault detection. This paper presents a scheme on the detection and diagnosis of the three-phase squirrel induction motor under unbalanced voltage, broken rotor bar, and a combination of these two faults. Actually one fault happen in operation, it influence other component in motor or cause another faults. Accordingly it is useful to diagnose and detect a combination fault in induction motor as well as each fault. The proposed fault detection and diagnosis algorithm is based on the stator currents from the squirrel induction motor and simulated with the aid of Matlab Simulink.

Real-time Fault Diagnosis of Induction Motor Using Clustering and Radial Basis Function (클러스터링과 방사기저함수 네트워크를 이용한 실시간 유도전동기 고장진단)

  • Park, Jang-Hwan;Lee, Dae-Jong;Chun, Myung-Geun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.20 no.6
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    • pp.55-62
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    • 2006
  • For the fault diagnosis of three-phase induction motors, we construct a experimental unit and then develop a diagnosis algorithm based on pattern recognition. The experimental unit consists of machinery module for induction motor drive and data acquisition module to obtain the fault signal. As the first step for diagnosis procedure, preprocessing is performed to make the acquired current simplified and normalized. To simplify the data, three-phase current is transformed into the magnitude of Concordia vector. As the next step, feature extraction is performed by kernel principal component analysis(KPCA) and linear discriminant analysis(LDA). Finally, we used the classifier based on radial basis function(RBF) network. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

Grid faults characteristics simulation of inverter-fed induction generator (인버터 부착형 농형 유도발전기의 계통고장특성 모의)

  • Hong, Jitae;Kwon, Soonman;Kim, Chunkyung;Lee, Jongmoo;Cheon, Jongmin;Kim, Hong-Ju;Kim, Heeje
    • 한국신재생에너지학회:학술대회논문집
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    • 2011.11a
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    • pp.43.1-43.1
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    • 2011
  • The detail simulation modeling of fully-fed induction generator is investigated through PC based MATLAB/Simulink environment. Generator's stator currents are controlled by indirect vector control method. In this method, generator side converter controls the maximum excitation (air gap flux) by stator d-axis current and controls generator torque by stator q-axis current. Induction generator speed is controlled by tip speed ratio (TSR) upon the wind speed variations in order to generate the maximum output power. The generator torque model is specified as a 3-blade wind turbine with rating, then, the model is simulated under normal operating condition and three different fault conditions. The matlab model designed for fully-fed induction generator based wind farm provides good performance under normal and grid fault conditions. It provides good results for different pwm techniques and fault conditions except the single-phase line to ground fault, which should be verified with real time data from wind farms.

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Development of Induction Motor Diagnosis Method by Variance Based Feature Selection and PCA-ELM (분산정보를 이용한 특징 선택과 PCA-ELM 기반의 유도전동기 고장진단 기법 개발)

  • Lee, Dae-Jong;Chun, Myung-Geun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.24 no.8
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    • pp.55-61
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    • 2010
  • In this paper, we proposed selective extraction method of frequency information and PCA-ELM based diagnosis system for three-phase induction motors. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by variance As the next step, feature extraction is performed by principal component analysis (PCA). Finally, we used the classifier based on Extreme Learning Machine (ELM) with fast learning procedure. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

A New Hybrid "Park's Vector - Time Synchronous Averaging" Approach to the Induction Motor-fault Monitoring and Diagnosis

  • Ngote, Nabil;Guedira, Said;Cherkaoui, Mohamed;Ouassaid, Mohammed
    • Journal of Electrical Engineering and Technology
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    • v.9 no.2
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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.