1,721,057 research outputs found
TIME HARMONIC INVESTIGATION OF FLUX DENSITY IN THE STATOR AND ROTOR FRAME ORIENTED TO DIAGNOSTICS OF CAGE INDUCTION MOTORS
No full text
Monitoring of induction machines by maximum covariance method for frequency tracking
No full textMotor Current Signature Analysis (MCSA) has been widely investigated in order to monitor fault conditions of induction machines. On the other hand several solutions were proposed for the detection of rotor speed of induction motor for sensorless control. Another deeply investigated field of research is the detection of supply frequency of power lines, for the diagnosis of the distribution network. A common root of these three key topics is the need of accurately stating specific spectrum frequencies. Several techniques were presented in the literature in order to perform accurate tracking of frequencies for different purposes. They are modified versions of the traditional Discrete Fourier Transformation (DFT), or novel spectrum estimation techniques. This paper presents a novel procedure based on the statistical analysis of the current signal in the time domain, referred to as Maximum Covariance Method for Frequency Tracking (MCMFT), that allows to obtain high frequency resolution accuracy independently of the sampling frequency and of the time acquisition period. Therefore those spectrum lines related to supply frequency or to slip can be detected with extreme accuracy within a wide range of sampled data conditions. Then either an accurate diagnosis of the machine electric faults or sensorless control, or distribution network diagnosis can be performed. Comparison between the proposed method and the literature are reported, in order to critically analyze its performances. An induction machine with two artificially broken bars was used for the experiments
SYNTHESIS OF ARTIFICIAL INTELLIGENCE AND NEURAL NETWORK TECHNOLOGIES IN POWER ELECTRIC SYSTEM DIAGNOSTICS
No full textDifferential diagnosis based on multivariable monitoring to assess induction machine rotor conditions
No full textMultivariable supervision systems for online monitoring of induction motors allow large versatility and diagnosis robustness. As regards rotor faults, the diagnostic procedure based on sideband current components may fail due to the presence of interbar currents that reduce the degree of rotor asymmetry and, thus, the amplitude of these spectral components. On the other hand, the interbar currents produce core vibrations in the axial direction; these vibrations can be detected using a suitable vibration sensor. In this paper, a differential fault analysis based on traditional motor current signature analysis (MCSA) and on radial and axial vibration monitoring is proposed to discern cases in which the presence of interbar currents decreases the sensitivity of MCSA. The features of stator currents and of radial and axial core vibration signals are investigated in order to increase the reliability of the diagnostic system. Moreover, to explore the possibility of obtaining further information, stray flux signals are taken into account. © 2008 IEEE
DIAGNOSI DELLA ROTTURA DELLE SBARRE DI MACCHINE ELETTRICHE ASINCRONE, ESEGUITA UTILIZZANDO COMPONENTI SPETTRALI ANOMALE DELLA CORRENTE DI STATORE
No full textA COMPARATIVE STUDY OF EFFECTS DUE TO ECCENTRICITY AND EXTERNAL STATOR AND ROTOR ASYMMETRIES BY MONOHARMONIC MODEL
No full text- …
