Detection Of Air-gap Eccentricity Research Articles

Motor Current Signature Analysis for the Air Gap Eccentricity Detection In the Squirrel Cage Induction Machines

The classical diagnosis approaches, deeply spread in the industrial environment, are based on the Fourier analysis of the steady-state current, the basis of the proposed methodology consist of analysing the current demanded by the machine during the connection process (startup transient); the objective is to extract the characteristic evolution during the transient of some harmonic components created by the fault; this evolution is caused by the dependence of these components on the slip (s). In this paper the induction motor under dynamic and mixed eccentricity type is modeled with high precision using (CMC) approach.

Detection of air-gap eccentricity in induction machines using multi-position magnetic field measurement approach

This paper presents a multi-position magnetic field measurement approach to detect air-gap eccentricity in induction machines, including static, dynamic and mixed eccentricity. Using this method, the position of minimum air gap of static eccentricity also can be detected. The sideband components around the fundamental frequency of magnetic flux leakage in stator yoke is particularly analyzed based on magnetic circuit. The magnitudes of induced voltage harmonics in search coils are also investigated by finite element method. The algorithm is implemented for a 4-pole three-phase cage induction machine with static, dynamic and mixed eccentricity. It is highlighted that dynamic eccentricity can be detected by any one of the search coils, static eccentricity and the position of minimum air gap can be detected by the magnitudes of induced voltages in all the search coils. The theoretical results have been validated by finite element method.

Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions

Fast Fourier transform (FFT) analysis has been successfully used for fault diagnosis in induction machines. However, this method does not always provide good results for the cases of load torque, speed and voltages variation, leading to a variation of the motor-slip and the consequent FFT problems that appear due to the non-stationary nature of the involved signals. In this paper, the discrete wavelet transform (DWT) of the apparent-power signal for the airgap-eccentricity fault detection in three-phase induction motors is presented in order to overcome the above FFT problems. The proposed method is based on the decomposition of the apparent-power signal from which wavelet approximation and detail coefficients are extracted. The energy evaluation of a known bandwidth permits to define a fault severity factor (FSF). Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method presented even for the case of load torque variations.

Detection of Airgap Eccentricity for Permanent Magnet Synchronous Motors Based on the d-Axis Inductance

The majority of the work performed for detecting eccentricity faults for permanent magnet synchronous motors (PMSM) focus on motor current signature analysis (MCSA), as it provides continuous online monitoring with existing current sensors. However, MCSA cannot be applied under nonstationary conditions and cannot distinguish faults with load torque oscillations, which are limitations for many PMSM drive applications. In this paper, it is shown that the d-axis inductance L decreases with an increase in the severity of eccentricity due to the change in the degree of magnetic saturation, and it is proposed as a new fault indicator. The inverter can be used to perform a standstill test automatically whenever the motor is stopped to measure L for eccentricity testing independent of load variations or oscillations, which is not possible with MCSA. An finite element and experimental study on a 10-hp PMSM verifies that eccentricity can be detected independent of the load with high sensitivity and reliability.

Experimental investigation on detection of air gap eccentricity in induction motors by current and vibration signature analysis using non-invasive sensors

The contents of this paper reports an experimental investigation carried out to detect the air gap eccentricity faults under varying load conditions using non-invasive transducers to monitor the current and vibration signals as a diagnostic medium. Experimental results of vibration signature analysis using Micro-Electro-Mechanical Systems (MEMS) accelerometer and Motor Current Signature Analysis (MCSA) using Hall Effect current transducers are compared and found nearly common signatures. Spectral analysis is carried out using decimation in time Fast Fourier Transform algorithm using FFT analyzer. This study also examines the usefulness of vibration signature analysis using MEMS to detect the eccentricity faults in developing a compact, miniaturized and cost effective instrument.

A Survey of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors

Medium-voltage (MV) induction motors are widely used in the industry and are essential to industrial processes. The breakdown of these MV motors not only leads to high repair expenses but also causes extraordinary financial losses due to unexpected downtime. To provide reliable condition monitoring and protection for MV motors, this paper presents a comprehensive survey of the existing condition monitoring and protection methods in the following five areas: thermal protection and temperature estimation, stator insulation monitoring and fault detection, bearing fault detection, broken rotor bar/end-ring detection, and air gap eccentricity detection. For each category, the related features of MV motors are discussed; the effectiveness of the existing methods are discussed in terms of their robustness, accuracy, and implementation complexity. Recommendations for the future research in these areas are also presented.

Detection of air-gap eccentricity and broken-rotor bar conditions in a squirrel-cage induction motor using the radial flux sensor

A new method for detecting eccentricity and broken rotor bar conditions in a squirrel-cage induction motor is proposed. Air-gap flux variation analysis is done using search coils, which are inserted at stator slots. Using this method, the leakage flux in radial direction can be directly detected. Using finite element method, the air-gap flux variation is accurately modeled and analyzed. From the results of the simulation, a motor under normal condition shows maximum magnetic flux density of 1.3T. On the other hand, the eccentric air-gap condition displays about 1.1T at 60° and 1.6T at 240°. A difference of flux density is 0.5T in the abnormal condition, whereas no difference is detected in the normal motor. In the broken rotor bar conditions, the flux densities at 65° and 155° are about 0.4 T and 0.8T, respectively. These simulation results are coincided with those of experiment. Consequently, the measurement of the magnetic flux at air gap is one of effective ways to discriminate the faulted conditions of the eccentricity and broken rotor bars.

Detection of airgap eccentricity using line current spectrum of induction motors

In this study, the machine with offset (eccentric) rotor has been studied. This study is of interest because rotor eccentricity can result in large forces applied to the rotor as well as some force harmonics with the potential to produce noise and vibrations. The current spectrum analysis is an accepted strategy for the monitoring and detection of airgap eccentricity in induction machines. M.m.f.-permeance wave approach has been used for simulating the machine under healthy and eccentric rotor conditions. A specially constructed eccentricity producing mechanism has been used to introduce static eccentricity by controlling the movement of the rotor core. The theoretical results have been compared with the experimental results. The simulation results are in close agreement with the experimental results.

Determination of air-gap eccentricity in electric motors using coherence analysis

This study addresses the detection of air-gap eccentricity based on hearing damage in 5 hp induction machines. The faulty condition of the bearing is caused by accelerated aging processes in seven aging cycles. For the faulty case, the spectra of vibration signals are computed for initial and final aging processes under 100% load condition. Subsequently, the spectra of the current signals for a single phase are also obtained for the initial and aged cases and cross-power spectral coherences between the vibration and current signals are computed.

Computer-aided detection of airgap eccentricity in operating three-phase induction motors by Park's vector approach

The subject of online detection of airgap eccentricity in three-phase induction motors is discussed, and a noninvasive approach, based on the computer-aided monitoring of the stator current Park's vector, is introduced. Experimental results, obtained by using a special fault producing test rig, demonstrate the effectiveness of the proposed technique, for detecting the presence of airgap eccentricity in operating three-phase induction machines. >