• Title/Summary/Keyword: Fault signal

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Method for High-visibility of Online Monitoring and Fault Diagnosis System for Industrial Motor using PVA (PVA를 이용한 산업용 모터 고장진단 모니터링 시스템의 가시성을 높이는 방법)

  • Goh, Yeong-Jin;Kang, In-Won
    • Journal of the Korea Safety Management & Science
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    • v.22 no.1
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    • pp.15-21
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    • 2020
  • Industrial Motors diagnostic equipment is highly dependent on the automation system, so if there are defects in the automation equipment, it can only rely on the operator's intuitive judgment.To help with intuitive judgment, Park's Vactor Approach(PVA) represents the current signal as a pattern of circles, so it can tell if a fault occurs when the circle is distorted. However, the failure to judge the degree of distortion of the circle pattern is the basis of the fault, so it will face difficulties. In this paper, in order to compare the faults of PVA, the period of d-axis current of PVA pulsation was mastered, so that two phase differences occurred in the same signal source. Through experiments, it is confirmed that this is a 90 degree cross formation of PVA, which is convenient for judging from the vision that there is no fault, thus helping the operator to make intuitive judgment.

Fault Diagnosis of Transformer Based on Self-powered RFID Sensor Tag and Improved HHT

  • Wang, Tao;He, Yigang;Li, Bing;Shi, Tiancheng
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.2134-2143
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    • 2018
  • This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

Detection of Stator Winding Inter-Turn Short Circuit Faults in Permanent Magnet Synchronous Motors and Automatic Classification of Fault Severity via a Pattern Recognition System

  • CIRA, Ferhat;ARKAN, Muslum;GUMUS, Bilal
    • Journal of Electrical Engineering and Technology
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    • v.11 no.2
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    • pp.416-424
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    • 2016
  • In this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.

A Study on the Algorithm for Fault Discrimination in Transmission Lines using Advanced Computational Intelligence(ACI) (ACI 기법을 이용한 송전선로 고장 종류 판별에 관한 연구)

  • Park Jae Hong;Lee Jong Beom
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.619-621
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    • 2004
  • This paper presents the rapid and accurate algorithm for fault discrimination in transmission lines. When faults occur in transmission lines, fault discrimination is very important. If high impedance faults occur in transmission lines, it cannot be detected by overcurrent relays. The method using current and voltage cannot discriminate high impedance fault. Because of this reason this paper uses voltage and zero sequence current, and the proposed algorithm uses fuzzy logic method. This algorithm uses voltage and zero sequence current per period in case of faults. Single line ground fault and three-phase fault can be detective using voltage. Two-line ground fault and line to line fault and high impedance can be detected using zero sequence current. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

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Development of Fault Location Method Using SWT and Travelling Wave on Underground Power Cable Systems (SWT와 진행파를 이용한 지중송전계통 고장점 추정 기법 개발)

  • Jung, Chae-Kyun;Lee, Jong-Beom
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.2
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    • pp.184-190
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    • 2008
  • The fault location algorithm based on stationary wavelet transform was developed to locate the fault point more accurately. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. In previous paper, noise cancellation technique based on the correlation of wavelet coefficients at multi-scales was introduced, and the efficiency was also proved in full. In this paper, fault section discrimination and fault location algorithm using noise cancellation technique were tested by ATP simulation on real power cable systems. From these results, the fault can be located even in very difficult and complicated situations such as different inception angle and fault resistance.

Auto-Detection of Stator Winding Fault of Small Induction Motor using LabVIEW (LabVIEW를 이용한 소형 유도전동기의 권선고장 자동진단)

  • Song, Myung-Hyun;Park, Kyu-Nam;Han, Dong-Gi;Woo, Hyeok-Jae
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.55 no.4
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    • pp.202-206
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    • 2006
  • In this paper, an auto detection method of stator winding fault of small induction motor is suggested. The Park's vector pattern which is obtained from 3-phase current signal by d-q transforming, is very good to detect winding fault. Comparing the Park's vector pattern of testing motor with its of healthy motor, the Park's vector pattern of fault motor is became an ellipse and the asymmetry is increased by the winding fault series. So for detecting the dis-symmetry, id-filtered function, Min-value, and Max-value are suggested for auto detecting. Using LabVIEW programing, 3-phase healthy motor and several kind of winding fault motors are tested and the test results are shown that the suggested method can gives us a possibility of an auto detecting winding fault.

Interturn Fault Diagnosis in Interior Permanent Magnet Synchronous Motors Using Negative-Sequence Impedance (역상 임피던스를 이용한 매립형 영구자석 동기전동기의 권선간 고장진단)

  • Jeong, Hyeyun;Kim, Sang Woo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.2
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    • pp.394-401
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    • 2017
  • Fault diagnosis is important due to the increasing demand of using interior permanent magnet synchronous machines (IPMSMs). In particular, an interturn fault is one of the most frequent electrical faults in IPMSMs. This paper proposes a fault indicator for diagnosis of interturn faults in IPMSMs. The fault indicator is developed by negative-sequence impedance. The effectiveness of the fault indicator to diagnose interturn faults was verified through various fault conditions.

Fault Detection of Gantry Crane System By using Observation Technique (관측기법을 이용한 갠트리 크레인의 고장 진단)

  • 김환성;김명규;유삼상
    • Journal of Advanced Marine Engineering and Technology
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    • v.25 no.4
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    • pp.880-888
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    • 2001
  • This paper presents a fault detection asnd isolation algorithm for highly reliable gantry crane system. The algorithm is constructed by multiple PI observer technique, and the magnitude of actuator fault can be estimated by using integrated estimated output error. Also, the complex actuator and /or sensor fault can be detected and isolated by monitoring the integrated error and the estimated state error. Considering the actuator and/or the sensor fault, we verify that these fault can be detected and isolated through simulation. Lastly, we show a simple reliable control method by using the detected fault signal and an added observer.

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Vibration Characteristic Analysis using Acoustic Emission Signal (AE신호를 이용한 기어 정렬불량의 진동 특성 분석)

  • Gu, Dong-Sik;Kim, Byeong-Su;Lee, Jeong-Hwan;Yang, Bo-Suk;Choi, Byeong-Keun
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.11a
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    • pp.43-48
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    • 2008
  • Gear system has been widely used in industrial applications and unexpected failures of gears are not only extremely damaging but also lead to economic losses. So, early detection of fault is important for diagnosis machine condition. And acoustic emission is an efficient non destructive testing technique for the diagnosis of machine health and is useful technique for early detection of fault because it can find low-amplitude and high-frequency signal on account of high sensibility. Therefore, in this paper, the AE signal was measured and preprocessed using envelop analysis for gearbox with misalignment between pinion and gear. And then the vibration characteristic of gear misalignment was analyzed.

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Arc Detection Method using RSSI Signal to High Frequency Noise (고주파 노이즈의 RSSI신호를 이용한 Arc검출방법)

  • Yang, Seung Kook;Lee, Ju
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.29 no.3
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    • pp.102-106
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    • 2015
  • In order to avoid the electrical fire, AFCI(Arc Fault Cirruit Interrupter) has been obligated to be adopted in the United States of America since 2002. A study was carried out on how to detect Arc. In this paper, The propose is high-frequency signal detection methods and RSSI(Received Signal Strength Indication) signal processing algorithm for Arc detection. and the electrical characteristics were verifying.