電流分析을 利用한 誘導電動機의 缺陷 檢出에 關한 硏究
(A) Study on the Fault Detection of the Induction Motors Using Input Current Analysis
전류분석 유도전동기 결함검출;
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The unexpected failure of the induction motor makes the downtime of production, and the cost of the process cessation enormous. To reduce the downtime and increase the reliability of the motor, the vibration measurements for the fault detection have been used previously. Recently motor current signature analysis(MCSA) has been adapted for the faultdetection and diagnosis of the motors. MCSA provides a powerful analysis tool for detecting the presence of mechanical and electrical faults in both the motor and driven equipment. The motor current signature provides an important source of the information for the faults diagnosis of three-phase induction motor. The theoretical principles behind the generation of unique signal characteristics, which are indicative of failure mechanisms, are presented. The fault detection techniques that can be used to diagnose mechanical problems, stator and rotor winding failure mechanisms, and air-gap eccentricity are described. A theoretical analysis is presented which predicts the presence of unique signature patterns in the current that are only characteristics of the motor fault. The predictions are verified by experimental results from a special fault producing test rig and on-site tests. In this paper, the fault severity of the rotor bar has been derived in terms of the resistance change which is calculated from the equivalent circuit model. The results show that the fault of the rotor can be easily detected and the measured value of the resistance change is verified by the detected fault from on-site tests using MCSA for the induction motors. Stator winding fault is analyzed on the base of the rotating wave which accounts for all the stator and rotor MMF(magnetomotive force) harmonics, stator and rotor slot harmonics and harmonics due to saturation. The test shows that the most reliable indicators of the presence of the fault are the lower sideband of field rotational frequency with respect to the fundamental components that are related to slotting. In the present investigation, the frequency signature of some asymmetrical motor faults are well identified using advanced signal processing techniques, such as high-resolution spectral analysis. This technique leads to a better interpretation for the motor current spectra. In fact, experimental results clearly illustrate that stator current high-resolution spectral analysis is very sensitive to induction motor faults modifying main spectral components, such as voltage unbalance and single-phasing effects. And this study have made new diagnostic algorithm for the operating induction motors with the test results. These developments are including the use of monitoring and analysis of electric current to diagnose mechanical and electrical problems and gave the precise test results automatically.