Gerald Burt Kliman

Interior Permanent-Magnet Synchronous Motors for Adjustable-Speed Drives

Interior permanent-magnet (IPM) synchronous motors possess special features for adjustable-speed operation which distinguish them from other classes of ac machines. They are robust high powerdensity machines capable of operating at high motor and inverter efficiencies over wide speed ranges, including considerable ranges of constant-power operation. The magnet cost is minimized by the low magnet weight requirements of the IPM design. The impact of the buried-magnet configuration on the motors electromagnetic characteristics is discussed. The rotor magnetic circuit saliency preferentially increases the quadrature-axis inductance and introduces a reluctance torque term into the IPM motors torque equation. The electrical excitation requirements for the IPM synchronous motor are also discussed. The control of the sinusoidal phase currents in magnitude and phase angle with respect to the rotor orientation provides a means for achieving smooth responsive torque control. A basic feedforward algorithm for executing this type of current vector torque control is discussed, including the implications of current regulator saturation at high speeds. The key results are illustrated using a combination of simulation and prototype IPM drive measurements.

Noninvasive detection of broken rotor bars in operating induction motors

A description is given of a computer-based noninvasive broken bar fault detector for squirrel-cage rotors of induction motors. The detector can be applied to existing motors without disassembly or shutdown and has the sensitivity to diagnose the presence of a single broken bar or an open end ring. It is suitable for monitoring the trend of the motor signature, or it can be used as a one-time diagnostic tool. >

Quantitative evaluation of induction motor broken bars by means of electrical signature analysis

The paper reports the comparison and performance evaluation of different diagnostic procedures that use input electric signals to detect and quantify rotor breakage in induction machines supplied by the mains. Besides the traditional current signature analysis based on one-phase current spectrum lines at frequencies (1/spl plusmn/2s)f, the procedures based on analysis of the line at frequency 2sf in the spectrum respectively of electromagnetic torque, space vector current modulus and instantaneous power are considered. These last procedures have similar features and the comparison is developed on the basis of instantaneous torque. It is shown that the speed ripple introduces two further terms in the instantaneous torque, decreasing the accuracy of the diagnosis. It is shown that there is a link between the angular displacement of the current sideband components at frequencies (1/spl plusmn/2s)f. This allows a more correct quantitative evaluation of the fault and to show the superiority of the sideband current components diagnostic procedure over the other proposed methods.

Methods of Motor Current Signature Analysis

ABSTRACT Recently a technique for monitoring and diagnosing mechanical problems, associated with rotating machines driven by electric motors, has been proposed and is now being offered by several commercial suppliers. This technique, known as “Motor Current Signature Analysis” or MCSA, seeks to apply much of the long experience in vibration signature analysis to the analysis of motor current in effect using the motor as a sensor akin to an acceleromeier This paper explores some of the history of the technique, presents several examples, and demonstrates a first order approach to the theory with associated cautions.

An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current

It is well known that motor current is a nonstationary signal, the properties of which vary with respect to the time-varying normal operating conditions of the motor. As a result, Fourier analysis makes it difficult to recognize fault conditions from the normal operating conditions of the motor. Time-frequency analysis, on the other hand, unambiguously represents the motor current which makes signal properties related to fault detection more evident in the transform domain. In this paper, the authors present an adaptive, statistical, time-frequency method for the detection of broken bars and bearing faults. Due to the time-varying normal operating conditions of the motor and the effect of motor geometry on the current, they employ a training-based approach in which the algorithm is trained to recognize the normal operating modes of the motor before the actual testing starts. During the training stage, features which are relevant to fault detection are estimated using the torque and mechanical speed estimation. These features are then statistically analyzed and segmented into normal operating modes of the motor. For each mode, a representative and a threshold are computed and stored in a database to be used as a baseline during the testing stage. In the testing stage, the distance of the test features to the mode representatives are computed and compared with the thresholds. If it is larger than all the thresholds, the measurement is tagged as a potential fault signal. In the postprocessing stage, the testing is repeated for multiple measurements to improve the accuracy of the detection. The experimental results from their study suggest that the proposed method provides a powerful and a general approach to the motor-current-based fault detection.

A Survey of Methods for Detection of Stator-Related Faults in Induction Machines

As evidenced by industrial surveys, stator-related failures account for a large percentage of faults in induction machines. The objective of this paper is to provide a survey of existing techniques for detection of stator-related faults, which include stator winding turn faults, stator core faults, temperature monitoring and thermal protection, and stator winding insulation testing. The root causes of fault inception, available techniques for detection, and recommendations for further research are presented. Although the primary focus is online and sensorless methods that use machine voltages and currents to extract fault signatures, offline techniques such as partial discharge detection are also examined. Condition monitoring, fault diagnostics, insulation testing, interlaminar core faults, partial discharge (PD), temperature monitoring, turn faults.

A new approach to on-line turn fault detection in AC motors

Turn fault detection is based on the principal that symmetrical (unfaulted) motors powered by symmetrical multiphase voltage sources will have no negative sequence currents flowing in the leads. A turn-to-turn fault will break that symmetry and give rise to a negative sequence current which may then be used as a measure of fault severity or to initiate protective action such as a circuit breaker trip. A new way of looking at the effects of turn faults has been developed that improves sensitivity and speed while reducing the probability of misdetection, taking into account voltage balance, load or voltage variation and instrument errors. The method has been implemented on a PC and tested, in real time, on a specially prepared small motor. Reliable detection of one shorted turn out of 648 turns per phase (in a Y connected motor) was demonstrated with the fault indicator becoming fully developed in two cycles of line frequency after initiation of the fault.

Insulation failure prediction in AC machines using line-neutral voltages

This paper presents a novel technique to detect insulation failure in polyphase AC machines. The machine must be star connected and have the neutral accessible. The mathematical theory of the technique is provided and supported by an experimental validation-turn faults in the stator of an induction machine are detected from the algebraic sum of the three instantaneous line-neutral voltages. However, this voltage sum contains undesirable frequencies that decrease the sensitivity of the scheme. Bandpass filtering the voltage sum (around the fundamental) optimizes sensitivity by removing the harmonics that arise from core saturation, slot harmonics, etc. The design of the scheme makes it practically immune to false alarms attributable to varying load conditions, operating temperatures and source voltage perturbations. It is shown that this technique is simpler in both theory and practice than other techniques based upon accurate calculations of sequence voltages and currents. The simplicity of this technique permits a low-cost implementation to flag a turn fault within a few cycles of the fundamental machine excitation.

Stator current harmonics and their causal vibrations: a preliminary investigation of sensorless vibration monitoring applications

This paper presents an initial study into the relationship between vibration and current harmonics of electric motors, including the effect of externally induced vibrations. This relationship was investigated experimentally on both new motors, on a vibration stand, and a motor with bearing wear. Both theory and experimental results show that a change in the RMS value of the stator current is directly related to the change in vibration magnitude, for a known vibration frequency. The paper shows this result both for a new motor with an externally induced vibration and for a motor with vibration caused by progressive bearing wear.

A survey of methods for detection of stator related faults in induction machines

As evidenced by industrial surveys, stator related failures account for a large percentage of faults in induction machines. The objective of this paper is to provide a survey of existing techniques for detection of stator related faults, which include stator winding turn faults, stator core faults, temperature monitoring and thermal protection, and stator winding insulation testing. The root causes of fault inception, available techniques for detection and recommendations for further research are presented. Although the primary focus is on-line, sensorless methods that use machine voltages and currents to extract fault signatures, off-line techniques such as partial discharge detection are also examined.