• 제목/요약/키워드: motor current signature analysis

검색결과 33건 처리시간 0.039초

MCSA를 이용한 BLDC 전동기의 고정자 권선 고장 진단 (Winding Fault Diagnosis for BLDC Motor using MCSA)

  • 이대성;양철오;김준영;김대홍;문용선;박규남;송명현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.1876-1877
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    • 2011
  • In this paper, a winding fault diagnosis method base on MCSA(Motor Current Signature Analysis) for BLDC motor is proposed. This method is programmed by LabVIEW for winding fault diagnosis. For winding fault diagnosis, two types of winding fault(shorted turn at one pole, shorted turn at two pole in same phase) are put intentionally in on phase. The motor current is collected by hole sensor, and transformed by the Park's transform, and then the Park's Vector Pattern are obtained, Usually this pattern is formed an ellipse, so a proper threshold value of distortion ratio(the ratio of the shortest axis and longest axis of ellipse) is suggested for winding faults diagnosis.

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인공신경망을 이용한 유도전동기고장진단 (Fault diagnosis system of induction motor using artificial neural network)

  • 변윤섭;왕종배;김종기
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 D
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    • pp.2222-2224
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    • 2002
  • Induction motors are critical components of many industrial machines and are frequently integrated in commercial equipment. The heavy economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motors supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the artificial neural network, and the diagnosis system is programmed by using LabVIEW and MATLAB.

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고정자전류 모니터링에 의한 유도전동기 베어링고장 검출에 관한 연구 (Induction Motor Bearing Damage Detection Using Stator Current Monitoring)

  • 윤충섭;홍원표
    • 조명전기설비학회논문지
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    • 제19권6호
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    • pp.36-45
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    • 2005
  • 이 논문은 다른 종류의 유도전동기 구름베어링 손상을 유도전동기 고정자 전류신호해석을 통하여 검출하고 실시간으로 손상을 진단하는 알고리즘을 개발하였다. 유도전동기 구름베어링의 손상을 검출하기 위하여 정상적인 베어링을 갖는 유도전동기, 측정열에 불량을 가지고 있는 전동기와 베어링 외륜에 구멍을 가지고 있는 2가지 종류의 비정상 베어링을 갖는 유도전동기 3set를 실험시스템을 구축하였다. 또한 유도전동기의 구름베어링시스템의 비정상적인 상태에서 고정자전류을 검출하기 위하여 TMS320F2407 DSP 칩을 이용하여 데이터 획득보드를 개발하였다. 이 고정자전류신호를 해석을 통하여 베어링 손상을 검출하기 위한 방법으로 FFT, 웨이브렛 분석 및 내적에 의한 평균 신호패던에 의한 분석결과를 제시하였다. 특히 내적에 의한 신호분석 온 통하여 베어링 손상 여부를 실시간으로 진단할 수 있는 새로운 알고리즘과 분석방법을 제시하였다.

Oxidation Models of Rotor Bar and End Ring Segment to Simulate Induction Motor Faults in Progress

  • Jung, Jee-Hoon
    • Journal of Power Electronics
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    • 제11권2호
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    • pp.163-172
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    • 2011
  • Oxidation models of a rotor bar and end ring segment in an induction motor are presented to simulate the behavior of an induction machine working with oxidized rotor parts which are modeled as rotor faults in progress. The leakage inductance and resistance of the rotor parts arc different from normal values because of the oxidation process. The impedance variations modify the current density and magnetic flux which pass through the oxidized parts. Consequently, it causes the rotor asymmetry which induces abnormal harmonics in the stator current spectra of the faulty machine. The leakage inductances of the oxidation models are derived by the Ampere's law. Using the proposed oxidation models, the rotor bar and end ring faults in progress can be modeled and simulated with the motor current signature analysis (MCSA). In addition, the oxidation process of the rotor bar and end ring segment can motivate the rotor asymmetry, which is induced by electromagnetic imbalances, and it is one of the major motor faults. Results of simulations and experiments are compared to each other to verify the accuracy of the proposed models. Experiments are achieved using 3.7 kW, 3-phase, and squirrel cage induction motors with a motor drive inverter.

유도전동기의 고정자 권선고장 진단을 위한 팍스벡터 패턴의 왜곡률 연산에 대한 연구 (Study on Distortion Ratio Calculation of Park's Vector Pattern for Diagnosis of Stator Winding Fault of Induction Motor)

  • 양철오;박규남;송명현
    • 전기학회논문지
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    • 제61권4호
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    • pp.643-649
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    • 2012
  • The diagnosis technique of stator winding faults based on Motor Current Signature Analysis(MCSA) was suggested. Park's vector pattern, the circle that is drawn by d-q transformed currents($i_d$, $i_q$), is widely used for stator winding faults detection. The current Distortion Ratio(DR), defined by the ratio of max axis and min axis of ellipse of Park's vector's pattern, was more simple and powerful method than the Park's vector pattern. In this study, a calculation method of distortion ratio of Park's vector pattern was suggested for auto diagnosis of stator winding short fault and usefulness of suggested calculation method of distortion ratio was verified through simulation using LabVIEW program.

On-line Faults Signature Monitoring Tool for Induction Motor Diagnosis

  • Medoued, Ammar;Lebaroud, Abdesselem;Boukadoum, Ahcene;Clerc, Guy
    • Journal of Electrical Engineering and Technology
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    • 제5권1호
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    • pp.140-145
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    • 2010
  • The monitoring and the diagnosis of the faults in induction motors starting from the stator current are very interesting, since it is an accessible and measurable quantity. The spectral analysis of the stator current makes it possible to highlight the characteristic frequencies of the faults but in a wide frequency range depending on half the sampling frequency, making it very difficult to monitor on-line the faults. In order to facilitate the use of the relevant frequencies of machine faults we proposed the extraction of the frequency components using two methods, namely, the amplitude and the instantaneous frequency. The theoretical bases of these methods were presented and the results were validated on a test bench with an induction motor of 5.5 kw.

Fault detection and classification of permanent magnet synchronous machine using signal injection

  • Kim, Inhwan;Lee, Younghun;Oh, Jaewook;Kim, Namsu
    • Smart Structures and Systems
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    • 제29권6호
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    • pp.785-790
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    • 2022
  • Condition monitoring of permanent magnet synchronous motors (PMSMs) and detecting faults such as eccentricity and demagnetization are essential for ensuring system reliability. Motor current signal analysis is the most commonly used precursor for detecting faults in the PMSM drive system. However, the current signature responds sensitively to the load and temperature of the motor, thereby making it difficult to monitor faults in real- applications. Therefore, in this study, a condition monitoring methodology that detects motor faults, including their classification with standstill conditions, is proposed. The objective is to detect and classify faults of PMSMs by using programmable inverter without additional sensors and systems for detection. Both DC and AC were applied through the d-axis of a three-phase motor, and the change in incremental inductance was investigated to detect and classify faults. Simulation with finite element analysis and experiments were performed on PMSMs in healthy conditions as well as with eccentricity and demagnetization faults. Based on the results obtained from experiments, the proposed method was confirmed to detect and classify types of faults, including their severity.

Stator Current Processing-Based Technique for Bearing Damage Detection in Induction Motors

  • Hong, Won-Pyo;Yoon, Chung-Sup;Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1439-1444
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    • 2005
  • Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.

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유도전동기 Rotor Bar 손상에 따른 특성 변화 연구 (Study on characteristics of induction motor due to Rotor Bar crack)

  • 최진석;정진관;이은춘;김대근;안주훈;현리경
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2015년도 제46회 하계학술대회
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    • pp.713-714
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    • 2015
  • 유도전동기에서 회전자에 대한 진단은 소형, 저압전동기의 실험결과 위주의 논문이 주를 이루어 수도사업장의 용수 공급을 위한 고압 유도전동기의 회전자 진단에 대해서는 많은 관심을 갖지 않은 실정이다. 본 논문에서는 MCSA(Motor Current Signature Analysis) 방식을 이용한 장비를 이용하여 전류 스펙트럼과 기동전류 특성 통해 회전자의 건전성을 평가하는 방법을 기술하였다. 문제가 발생한 유도전동기를 대상으로 분해점검 후 실제 문제가 발생하였음을 확인하였고 문제 해결후 정상인 것을 확인하여 회전자 결함판정기준으로 전류 스펙트럼과 기동전류 특성이 타당함을 설명하였다.

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Design of Fault Diagnostic and Fault Tolerant System for Induction Motors with Redundant Controller Area Network

  • 홍원표;윤충섭;김동화
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2004년도 학술대회 논문집
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    • pp.371-374
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    • 2004
  • Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment. Safety, reliability, efficiency, and performance are some of the major concerns of induction motor applications. Preventive maintenance of induction motors has been a topic great interest to industry because of their wide range application of industry. Since the use of mechanical sensors, such as vibration probes, strain gauges, and accelerometers is often impractical, the motor current signature analysis (MACA) techniques have gained murk popularity as diagnostic tool. Fault tolerant control (FTC) strives to make the system stable and retain acceptable performance under the system faults. All present FTC method can be classified into two groups. The first group is based on fault detection and diagnostics (FDD). The second group is independent of FDD and includes methods such as integrity control, reliable stabilization and simultaneous stabilization. This paper presents the fundamental FDD-based FTC methods, which are capable of on-line detection and diagnose of the induction motors. Therefore, our group has developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. This paper presents its architecture. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module is checking stator current, voltage, temperatures, vibration and speed of the motor. The DSPs share information from each sensor or DSP through DPRAM with hardware implemented semaphore. And it communicates the motor status through field bus (CAN, RS485). From the designed system, we get primitive sensors data for the case of normal condition and two abnormal conditions of 3 phase induction motor control system is implemented. This paper is the first step to drive multi-motors with serial communication which can satisfy the real time operation using CAN protocol.

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