Bilal Akin

Low Order PWM Inverter Harmonics Contributions to the Inverter-Fed Induction Machine Fault Diagnosis

In this paper, the effects of inverter harmonics on motor current fault signatures are studied in detail. It is theoretically and experimentally shown that the fault signatures caused by the inverter harmonics are similar and comparable to those generated by the fundamental harmonic on the line current. Theoretically-derived extended relations including bearing fault, eccentricity, and broken rotor bar relations are found to match experimental results. Furthermore, it is observed and reported that the asymmetries on the rotor caused by broken rotor bars increase the amplitude of even harmonics. To confirm these claims, bearing, eccentricity, and broken rotor bar faults are tested and the line current spectrum of each faulty motor is compared with the healthy one. The proposed additional fault data are expected to contribute positively to the inverter-fed motor fault decision making algorithms.

Finite-Element Transient Analysis of Induction Motors Under Mixed Eccentricity Fault

In a three-phase squirrel-cage induction motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. We have developed a time-stepping finite-element method (FEM) that identifies mixed eccentricity (a combination of static and dynamic) by analysis, without direct access to the motor. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates the spectrum of the line current of a production-line motor and compares it to the spectrum of a known healthy motor to detect eccentricity. Agreement between the simulation and actual measurements of eccentricity is good.Protection and fault diagnosis are integral to sound application of three-phase squirrel-cage induction motors in industry. Eccentricity is a common fault in induction motors that might force the motor to be removed from the production line. However, diagnosis of this fault due to inaccessibility to the rotor is not easy. Performance analysis, investigation and diagnosis of static, dynamic and mixed eccentricities at steady-state and during transient modes have already been published using analytical methods. However, study of static and dynamic eccentricities only at steady-state using finite element method (FEM) has been previously reported. This paper uses time stepping FE (TSFE) method with voltage-fed source for performance analysis and diagnosis of mixed eccentricity in induction motor at start up. The method used here overcomes the difficulty of FE application which makes it possible to analyze the transient behavior of a faulty induction motor. Spectra of line current of healthy motor and motor under mixed eccentricity conditions are predicted by simulation and then compared with the experimental results. This comparison shows a very good agreement between the simulation and test results.

A Simple Real-Time Fault Signature Monitoring Tool for Motor-Drive-Embedded Fault Diagnosis Systems

The reference frame theory constitutes an essential aspect of electric machine analysis and control. In this study, apart from the conventional applications, it is reported that the reference frame theory approach can successfully be applied to real-time fault diagnosis of electric machinery systems as a powerful toolbox to find the magnitude and phase quantities of fault signatures with good precision as well. The basic idea is to convert the associated fault signature to a dc quantity, followed by the computation of the signals average in the fault reference frame to filter out the rest of the signal harmonics, i.e., its ac components. As a natural consequence of this, neither a notch filter nor a low-pass filter is required to eliminate fundamental component or noise content. Since the incipient fault mechanisms have been studied for a long time, the motor fault signature frequencies and fault models are very well-known. Therefore, ignoring all other components, the proposed method focuses only on certain fault signatures in the current spectrum depending on the examined motor fault. Broken rotor bar and eccentricity faults are experimentally tested online using a TMS320F2812 digital signal processor (DSP) to prove the effectiveness of the proposed method. In this application, only the readily available drive hardware is used without employing additional components such as analog filters, signal conditioning board, external sensors, etc. As the motor drive processing unit, the DSP is utilized both for motor control and fault detection purposes, providing instantaneous fault information. The proposed algorithm processes the measured data in real time to avoid buffering and large-size memory needed in order to enhance the practicability of this method. Due to the short-time convergence capability of the algorithm, the fault status is updated in each second. The immunity of the algorithm against non-ideal cases such as measurement offset errors and phase unbalance is theoretically and experimentally verified. Being a model-independent fault analyzer, this method can be applied to all multiphase and single-phase motors.

Implementation of a Fault-Diagnosis Algorithm for Induction Machines Based on Advanced Digital-Signal-Processing Techniques

In this paper, a complete cross-correlation-based fault-diagnostic method is proposed for real-time digital-signal-processor (DSP) applications that cover both the fault-monitoring and decision-making stages. In practice, a motor driven by an inverter or utility line is run at various operating points where the frequency, amplitude, and phase of the fault signatures vary unexpectedly. These changes are considered to be one of the common factors that yield erroneous fault tracking and unstable fault detection. In this paper, the proposed algorithms deal with the ambiguities of line-current noise or sensor-resolution errors and operating-point-dependent threshold issues. It is theoretically and experimentally verified that a motor fault can be continuously tracked when the sensor errors are within a limited range through the adaptively determined threshold definition of noise conditions. The offline experiments are performed via Matlab using actual line-current data obtained by a data-acquisition system. These results are verified on a DSP-based motor drive in real time where drive sensors and a digital signal processor are employed both for motor-control and fault-diagnostic purposes.

Phase-Sensitive Detection of Motor Fault Signatures in the Presence of Noise

In this paper, a digital signal processor-based phase-sensitive motor fault signature detection technique is presented. The implemented method has a powerful line current noise suppression capability while detecting the fault signatures. Because the line current of inverter-driven motors involve low-order harmonics, high-frequency switching disturbances, and the noise generated by harsh industrial environment, the real-time fault analyses yield erroneous or fluctuating fault signatures. This situation becomes a significant problem when the signal-to-noise ratio of the fault signature is quite low. It is theoretically and experimentally shown that the proposed method can determine the normalized magnitude and phase information of the fault signatures even in the presence of noise, where the noise amplitude is several times higher than the signal itself. Since it has low computational burden, the developed algorithm is embedded to the motor control program without degrading drive performance. Therefore, it is implemented without any additional cost using readily available drive processor and current sensors.

Comprehensive Eccentricity Fault Diagnosis in Induction Motors Using Finite Element Method

Load variation along with static and dynamic eccentricities degrees is one of the major factors directly affecting the dynamic behaviors of eccentricity signatures as observed in the current spectrum of induction motors. Without taking the effect of load variation into consideration precisely, the change in the static and dynamic related fault signature amplitudes provides misleading information where the eccentricity degree and the load level exhibit similar effects in the current spectrum. In this paper, we address all these factors in a unified framework by analyzing various combinations both theoretically and experimentally. For this purpose, the time-stepping finite element method (TSFEM)-based, load-level-independent method is proposed to determine the static and dynamic eccentricities degrees individually.

Simple Derivative-Free Nonlinear State Observer for Sensorless AC Drives

In this paper, a new Kalman filtering technique, unscented Kalman filter (UKF), is utilized both experimentally and theoretically as a state estimation tool in field-oriented control (FOC) of sensorless ac drives. Using the advantages of this recent derivative-free nonlinear estimation tool, rotor speed and dq-axis fluxes of an induction motor are estimated only with the sensed stator currents and voltages information. In order to compare the estimation performances of the extended Kalman filter (EKF) and UKF explicitly, both observers are designed for the same motor model and run with the same covariance matrices under the same conditions. In the simulation results, it is shown that UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, has more satisfactory rotor speed and flux estimates, which are the most critical states for FOC. These simulation results are supported with experimental results

DSP-Based Sensorless Electric Motor Fault Diagnosis Tools for Electric and Hybrid Electric Vehicle Powertrain Applications

The integrity of electric motors in work and passenger vehicles can best be maintained by frequently monitoring its condition. In this paper, a signal processing-based motor fault diagnosis scheme is presented in detail. The practicability and reliability of the proposed algorithm are tested on rotor asymmetry detection at zero speed, i.e., at startup and idle modes in the case of a vehicle. Regular rotor asymmetry tests are done when the motor is running at a certain speed under load with stationary current signal assumption. It is quite challenging to obtain these regular test conditions for long-enough periods of time during daily vehicle operations. In addition, automobile vibrations cause nonuniform air-gap motor operation, which directly affects the inductances of electric motors and results in a noisy current spectrum. Therefore, it is challenging to apply conventional rotor fault-detection methods while examining the condition of electric motors as part of the hybrid electric vehicle (HEV) powertrain. The proposed method overcomes the aforementioned problems by simply testing the rotor asymmetry at zero speed. This test can be achieved at startup or repeated during idle modes where the speed of the vehicle is zero. The proposed method can be implemented at no cost using the readily available electric motor inverter sensors and microprocessing unit. Induction motor fault signatures are experimentally tested online by employing the drive-embedded master processor (TMS320F2812 DSP) to prove the effectiveness of the proposed method.

Low-cost direct torque control of permanent magnet synchronous motor using Hall-effect sensors

In this paper, a direct torque control (DTC) scheme for permanent magnet (PM) synchronous motors (surface-mount type) using cost-effective Hall-effect sensors for constant torque region is presented. Unlike conventional DTC proposed method estimates necessary quantities in the rotor reference frame by obtaining continuous position and speed information from the Hall-effect sensors resembling expensive high resolution position sensors (encoder and resolver). Furthermore, this method requires no dc-link sensing and removes some common problems those conventional DTC drives suffer from such as the effect of resistance change, low speed operation integration drift, and the initial rotor position requirement. The proposed drive, considering the constant torque region operation, is applied to the agitation part of a laundry washing machine for speed and torque performance comparison with the existing low-cost agitation cycle speed control technique used by some washing machine companies around the world. Results of the tests clarify the effectiveness of the proposed DTC scheme over the commercial agitator speed control and even conventional DTC drive.

A comparative study on non-linear state estimators applied to sensorless AC drives: MRAS and Kalman filter

In this paper, two different nonlinear estimators applied to sensorless AC drives, Kalman filtering techniques (EKF and UKF) and model reference adaptive system (back emf and reactive power models), are discussed and compared to each other. Both of the observer types are studied and analyzed both experimentally and theoretically. In order to compare the observers precisely, the observers are tested under the identical conditions.