Online Diagnostics in Inverter-Fed Induction Machines ... - IEEE Xplore

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 40, NO. 4, JULY/AUGUST 2004

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Online Diagnostics in Inverter-Fed Induction Machines Using High-Frequency Signal Injection Fernando Briz, Member, IEEE, Michael W. Degner, Member, IEEE, Alberto B. Diez, Member, IEEE, and Juan Manuel Guerrero, Student Member, IEEE

Abstract—Fault diagnostics for induction machines using an injected high-frequency carrier signal is presented and analyzed in this paper. Both stator winding fault and broken rotor bar detection is covered. Measurement of the resulting high-frequency negative-sequence current is shown to be capable of detecting both types of faults at their incipient stage. Though sharing similar physical principles to techniques applied to line-connected machines, the use of a high-frequency signal is shown to provide important advantages for inverter-fed machines, such as providing the same performance and drastically reduced sensitivity to the working condition of the machine, i.e., torque and flux levels, and fundamental excitation frequency. Index Terms—Fault diagnosis, high-frequency signal injection, induction motor drives, stator winding fault detection.

NOMENCLATURE Superscript “ ” Superscript “ ”

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Variables shown in a stationary reference frame. Variables shown in a negative-sequence carrier-signal reference frame (i.e., ro); tating at Injected carrier-signal voltage. Carrier-signal voltage magnitude. Positive- and negative-sequence components of the carrier-signal current. Magnitude of the positive- and negative-sequence components of the carrier-signal current. Components at dc and , in a negativesequence carrier-signal reference frame, of the negative-sequence carrier-signal current.

Paper IPCSD-04-031, presented at the 2003 Industry Applications Society Annual Meeting, Salt Lake City, UT, October 12–16, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Industrial Drives Committee of the IEEE Industry Applications Society. Manuscript submitted for review October 1, 2003 and released for publication April 26, 2004. This work was supported in part by the Research, Technological Development, and Innovation Programs of the Principado of Asturias-ERDF under Grant PB-EXP01-24 and Grant PB02-055, and in part by the Spanish Ministry of Science and Technology-ERDF under Grant DPI2001-3815. F. Briz, A. B. Diez, and J. M. Guerrero are with the Department of Electrical, Computer and Systems Engineering, University of Oviedo, E-33204 Gijón, Spain (e-mail: [email protected]; [email protected]; [email protected]). M. W. Degner is with Sustainable Mobility Technologies, Ford Motor Company, Dearborn, MI 48121-2053 USA (e-mail: [email protected]). Digital Object Identifier 10.1109/TIA.2004.830792

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Stator transient inductance and resistance. Rotor, fundamental, and carrier-signal excitation frequencies. Angular position in electrical radians and harmonic number of the saliency. Sampling frequency. Number of samples. I. INTRODUCTION

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HE development of diagnostic techniques for electric machines has been an item of interest almost since the first use of electric machines, with the goal of preventing unexpected equipment downtime or severe equipment damage by detecting faults/failures in the electric machine at their incipient stage. Although offline diagnostic methods have been developed, online methods that do not interfere with the regular operation of the machine are preferred and have received increased attention [1]–[9]. While some of these online method require additional sensors, e.g., to measure the axial flux [8] or vibrations [9], more attractive are the methods that do not require any additional sensors and cabling [4]–[7]. These methods usually detect the presence of a fault in the machine by using terminal measurements, i.e., voltages or currents. Many of these methods have been developed and tested solely for the case of line-connected machines [4]–[7]. Because the diagnostic techniques initially developed to work with line-connected machines often assume or require a constant fundamental excitation (both frequency and magnitude), many of them are not applicable to inverter-driven adjustable-speed drives (ASDs), where both the excitation frequency and magnitude are changed based on the machine’s operating speed and load. In addition, ASDs introduce additional mechanisms for the creation of faults, especially in the stator windings [1]–[3]. High rates of voltage change have an adverse effect on the machine insulation, often worsened by long cable lengths [11]–[14]. Degradation of winding insulation can lead to turn-to-turn faults, starting a process that can progress to severe phase-to-phase or turn-to-ground faults. Despite these issues, new possibilities are created for the online detection of faults when a machine is operated using an inverter under torque or other forms of control (e.g., volts/Hz, etc.). First, the use of a variable excitation source, like an inverter, allows alternative forms of excitations to be used without

0093-9994/04$20.00 © 2004 IEEE

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forcing the disruption of the fundamental excitation. Second, most inverter-fed drives include current sensors in some form, whether they are used for current control, torque control, or for overcurrent protection. Third, a digital processor is usually present allowing some additional digital signal processing to be added at relatively no cost. This paper presents methods using an injected high-frequency carrier signal for the online detection of stator and rotor faults in induction machines. The physical principles of these techniques are similar to those based on the measurement of the negative-sequence impedance [4]–[6] or the negative-sequence component of the fundamental current [7]. The measurement of the negative-sequence carrier-signal current, using a low-magnitude high-frequency voltage superimposed on the fundamental excitation voltage, will be shown to reliably detect faults in the stator windings and rotor cage (broken rotor bars) at their incipient stage, independent of the working condition of the machine. In addition, using a high-frequency carrier-signal voltage will noticeably reduce the influence that the current regulator has on fault detection in inverter-fed current-regulated machines [10].

II. MEASUREMENT OF SPATIAL SALIENCIES USING HIGH-FREQUENCY SIGNAL INJECTION

TABLE I INDUCTION MOTOR PARAMETERS

Fig. 1. Schematic diagram of the experimental machine.

High-frequency signal-injection techniques have been proven to be effective in detecting spatial saliencies, i.e., asymmetries in ac machines [15], [16], and its use for diagnosis purposes has previously been suggested [16]–[18]. When a balanced, polyphase, high-frequency carrier-signal voltage (1) is applied to a machine, modeling the machine using only the stator transient inductance is a good approximation, if the frequency of the carrier-signal excitation, , is chosen so that it is substantially faster than the stator dynamics, usually being in the range of several hundred hertz [15], [16]. In this case, the high-frequency machine model can be written as (2) Fig. 2. Experimentally measured q - and d-axes currents.

(1) (2) When there is an asymmetry or saliency in a machine’s stator transient inductance, the interaction between the carrier-signal voltage, (1), and the saliency will produce a carrier-signal current consisting of both positive- and negative-sequence compois the angular position of the saliency in nents, (3), where electrical radians, is the harmonic number of the saliency, and is the carrier frequency in radians per second

(3) While the positive-sequence carrier-signal current contains no saliency spatial information, the negative-sequence carrier-signal current magnitude depends on the magnitude of the saliency, i.e., the level of asymmetry, and contains saliency spatial location information in its phase.

III. STATOR WINDING FAULT DIAGNOSIS USING HIGH-FREQUENCY SIGNAL INJECTION An imbalance in the stator winding due to a turn-to-turn fault will result in different inductances in the three phases of the machine, and therefore, to different - and -axes stator transient inductances in a stationary reference frame. Since the stator windings are fixed in space, this imbalance gives rise to a stationary saliency, i.e., an asymmetry in the machine that is fixed in space. To verify this behavior, a specially prepared machine with the ability to short adjacent turns was used for testing. The parameters of the machine are shown in Table I. Fig. 1 shows the stator winding design schematically, including how the turn-to-turn faults, ranging from 1 to 11 turns, were created. Fig. 2 shows the – -axes stator currents under a rated current condition, both with and without the high-frequency carriersignal voltage present. A magnitude for the positive-sequence mA (peak), corresponding to carrier-signal current of 2.5% of the rated current, was obtained using a carrier-signal V (peak) Hz, voltage and frequency of

BRIZ et al.: ONLINE DIAGNOSTICS IN INVERTER-FED INDUCTION MACHINES

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Fig. 3. Experimentally measured negative-sequence carrier-signal current trajectory in the negative-sequence carrier-signal reference frame for the cases of a healthy motor and four-turn fault, for a no-load (! = ! = 1 Hz), rated flux condition, and the complex vector spectrum for the case of a four-turn fault. The spectrum for the case of a healthy motor is the same except for the dc component, whose value is superimposed in white in the figure.

respectively. This level of carrier-signal voltage and frequency will be used throughout the rest of the paper. The switching frequency of the inverter was 15 kHz. The carrier-signal frequency was chosen to be an integer submultiple of the switching frequency. For that case, a lookup table can be used both for generating the carrier-signal voltage and for the coordinate transformation to the negative-sequence synchronous reference frame, avoiding the online use of trigonometric functions. Fig. 3 shows the trajectory of the negative-sequence carriersignal current and the corresponding frequency spectrum for the case of a healthy machine and a machine with a four-turn fault. The machines were current regulated and controlled using indirect field orientation. The different components seen in the spectrum can be explained as follows [16], [20]. • The dc component of the spectrum corresponds to a stationary saliency. Asymmetries in the machine windings or small imbalances in the current feedback paths, caused by unequal current sensor or amplifier gains, are likely sources for such saliencies for the case of healthy motors. • Fundamental-excitation-dependent harmonics at 2, 4, 8, Hz, i.e., components of the negative-sequence carrier-signal current at frequencies defined by (4) in the negative-sequence carrier-signal reference frame, are mainly caused by saturation of the machine iron with

(4)

The nonideal behavior of the inverter has also been reported to influence these components [19], [20]. • Although not present for this machine design, stator–rotor slotting saliencies may produce harmonics in the negative-sequence carrier-signal current that are a function of the rotor speed. Such harmonics are most often found for the case of open and semi-closed-rotor-slot induction machines [16], [20]. From Fig. 3 some interesting conclusions are apparent. It is seen that turn-to-turn faults in the stator windings produce rather noticeable variations of the stationary saliency, and consequently of the dc component of the negative-sequence carrier-signal current spectrum. The magnitude of the dc component of the negative-sequence carrier-signal current spectrum is large enough, even for a relatively small number of turn-to-turn faults, that it is distinguishable from parasitic components of the negative-sequence carrier-signal current, i.e., those that exist even in a healthy machine. Also, not only can the presence of a

Fig. 4. Experimentally measured dc component of the negative-sequence carrier-signal current for a motor with zero-, two-, and four-turn faults in phase v under different operating conditions.

fault be detected, but also the phase in which it is located due to the difference in the phase angle of the dc component complex vector. It is also observed that saturation-induced saliencies, as well as rotor–stator slotting saliencies, if they are present, can easily be separated from the stationary saliency since they are forced to rotate during most operating modes of the electric machine. A. Influence of the Operating Condition The experiments shown in Fig. 3 were performed under a rated flux, no-load condition. Fig. 4 shows the dc component of the negative-sequence carrier-signal current (in the form of real and imaginary parts) for different numbers of turn-to-turn faults in phase and for different operating conditions of the electric machine (different levels of current, torque, and different excitation frequencies). From Fig. 4 it can be seen that the stationary saliency caused by the fault, and its associated dc component in the negative-sequence carrier-signal current, is barely affected by the working condition of the machine. B. Influence of Imbalances in the Stator Resistance Resistive imbalances between the stator phases can also produce a negative-sequence carrier-signal current. The turn-to-turn faults discussed previously are a special form of this type of imbalance, since the fault also produces a resistive imbalance in addition to the phase inductance imbalance. Resistive imbalances, without an associated imbalance in the phase inductances, have many potential sources, including manufacturing variability between phase windings, poor connections, or different lengths in the cables feeding the motor. The magnitude of the dc component of the negative-sequence carrier-signal current caused by an imbalance in a phase resiscan be approximated by (5), assuming a simplitance of fied high-frequency model of the induction machine consisting only of the stator transient impedance (see Fig. 5(a), that and ). The phase angle of this dc component depends on the phase in which the imbalance exists (5)

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Fig. 5. (a) Simplified high-frequency model using the stator transient impedance. (b) Schematic diagram of the experimental machine including the external resistance connected in series with phase u of the stator windings.

Fig. 7. Experimentally measured dc component of the negative-sequence carrier-signal current as a function of the stator winding temperature for a machine with zero- (healthy) and four-turn faults, operated at rated flux-rated load.

Fig. 6. Experimentally measured dc component of the negative-sequence carrier-signal current for a motor with zero- and four-turn faults and different values of the imbalance in the stator resistance R . The machine was Hz. operated under rated flux-rated load !

=4

1

To verify this, experiments were performed using an external added in series to one phase of the stator windresistance ings, as shown in Fig. 5(b). Fig. 6 is a plot of the negative-sequence carrier-signal current dc component (in a negative-sequence carrier-signal synchronous reference frame) for a machine with and without a turn-to-turn fault and using different magnitudes for the external resistance. The magnitude of the external resistance was normalized using the stator resistance as . From the figure some concluthe base value, sions can be reached. • As predicted by (5), an almost linear relationship is observed between the magnitude of the resistive imbalance and the magnitude of the resulting dc component of the negative-sequence carrier-signal current. The phase in which the imbalance occurs can readily be detected from the phase angle of the resulting dc component of the negative-sequence carrier-signal current. • Although the behavior of the dc component of the negative-sequence carrier-signal current caused by resistive imbalances is similar to that produced by a turn-to-turn fault, the magnitude of the behavior is significantly smaller. As shown in Fig. 6, an external resistance did not produce as large a magnitude of change in the dc component of the negative-sequence carrier-signal current as that produced by a four-turn-to-turn fault.

• Imbalances in the stator resistance and turn-to-turn faults produce different phase angles in the dc component of the negative-sequence carrier-signal current, which can be used to aid in determining the source of the dc component. However, the phase angle difference is not deterministic since different sources for the dc component can occur simultaneously. As an example, the dc component of the negative-sequence carrier-signal current for the case of a added to phase four-turn fault in phase and shown in Fig. 6 is similar to the case of a two-turn-to-turn fault in phase and no imbalance in the stator resistance shown in Fig. 4. C. Influence of Temperature The temperature of the stator windings has also been reported to influence the negative-sequence impedance for the case of line-connected machines [21]. Fig. 7 shows the dc component of the negative-sequence carrier-signal current as a function of the temperature for the case of a machine with a healthy and a four-turn fault winding. It can be seen that while the temperature does influence the dc component of the negative-sequence carrier-signal current, the variations are relatively minor and would not prevent reliable detection of the fault. IV. ROTOR FAULT DIAGNOSIS USING HIGH-FREQUENCY SIGNAL INJECTION Detection of saliencies (asymmetries) in the rotor using high-frequency signal injection has been widely investigated as a viable means for rotor position detection. This suggests that rotor-related failures, including cracked or broken rotor bars and eccentricities, would also be detectable [16], [17]. For these types of failures to be detectable using an injected high-frequency signal, they must cause variations in the equivalent inductance or resistance, as seen from the stator windings. To verify the viability of such a technique, a rotor was modified to emulate a broken rotor bar by drilling the end-ring, as shown in Fig. 8. The rotor was modified so that the continuity of the end-ring was maintained and the rotor laminations were


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Fig. 11. Experimentally measured negative-sequence carrier-signal current complex vector spectrum in the negative-sequence carrier-signal reference frame for the case of a machine with closed rotor slots and (a) a healthy rotor or (b) a broken rotor bar, at rated flux, and 80% of rated load, ! = 4 Hz, ! = 1:5 Hz. Fig. 8. Rotor modified to break a rotor bar by drilling the end-ring (shown with the rotor slots opened).

Fig. 9. Experimentally measured negative-sequence carrier-signal current complex vector spectrum in the negative-sequence carrier-signal reference frame for the case of a motor with semi-open rotor slots and a broken rotor bar, operated at rated flux-rated load (! = 4 Hz, ! = 1 Hz).

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Fig. 10. Experimentally measured components of the negative-sequence carrier-signal current at 2! ( ) and 2! for the case of a motor with semi-open rotor slots and a healthy rotor ( ), or a rotor with a broken rotor bar ( ). The machine was operated at rated flux, and the load level varied according to the slip.

not affected. The rotor originally had closed rotor slots. After carrying out extensive tests, the rotor slots were opened. From the testing conducted on this rotor, the following conclusions were reached. • A broken rotor bar in machines with semi-open rotor slots causes a measurable rotor-position-dependent comin the negative-sequence carrier-signal ponent at in the stationary current reference frame (at reference frame). The presence of this signal, as well as other components of the negative-sequence carrier-signal current can be seen in the spectrum shown in Fig. 9. The component is barely affected by the magnitude of the operating condition of the machine, as shown in Fig. 10. component is a function of a • The magnitude of the number of parameters, including ones related to the machine design (skewed or unskewed rotor bars, inter-bar currents, number of poles, etc.) as well as the fault con-

dition (the number of rotor bars with faults (completely or partially broken), the location of the broken rotor bars, the effect of the fault on the rotor laminations, etc.). • Fundamental-excitation-dependent harmonics (compoand in Fig. 9), which are almost always nents at present in the negative-sequence carrier-signal current when fundamental excitation exists, have a noticeable magnitude, requiring them to be spectrally separated in order to make from the frequency component at reliable diagnosis of the broken rotor bar. Consequently, no-load operation, with flux present in the machine, is not suitable for diagnostic purposes since the major harmonic coincides with the rotor fault related harmonic at at . However, this is not considered a relevant restriction in practice, as rotor related faults usually develop slowly, and in general, electric motors do not work at no-load for extended periods of time. • Broken rotor bar detection using high-frequency signal injection was found to be more difficult for the case of closed-rotor-slot machines (Fig. 11). In this figure, the , caused by a broken rotor bar, has a component at reduced magnitude with respect to other components in the spectrum and, therefore, would be difficult to be reliably isolated. In addition, it barely changes with respect to the case of a healthy machine. The component at for the case of a healthy machine could be due to small imbalances of the rotor due to the manufacturing process. for the The reduced magnitude of the component at case of closed rotor slots is believed to be due mainly to two reasons. First, a broken rotor bar would typically prevent or limit current from traveling in that bar. The flux encircling the broken rotor bar through the rotor yoke would then be considered a leakage flux, since no current is generated in the bar to interact with it. This effect is more relevant in open-rotor-slot machines since the rotor leakage flux in closed-rotor-slot machines has an alternative path through the rotor slot bridges, which dominates the additional leakage flux path produced by a broken rotor bar (assuming that the laminations have not been damaged). Second, because of the deep saturation of the rotor slot bridges, saturation-induced harmonics are much larger in closed-rotor-slot machines, making it more difficult to separate the rotor position related components of the negative-sequence carrier-signal current.

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• Isolation of the component of the negative-sequence carrier-signal current caused by a broken rotor bar requires relatively precise knowledge of the rotor speed. V. DIGITAL SIGNAL PROCESSING The digital filtering necessary for the separation of the components of the negative-sequence carrier-signal current containing fault-related information (i.e., the components at and in the stationary reference frame) from the overall stator current can be performed in many different ways. Two of the most important aspects that need to be considered for the selection of the most suitable filtering algorithms are the following: 1) minimizing the memory and computational requirements and 2) reducing the influence caused by other components in the stator current. Specifically, the fundamental current and the saturation-induced components of the negative-sequence carrier-signal current (see Figs. 3 and 9) can cause noticeable distortion in the components containing the fault-related information. While offline fast Fourier transform (FFT) algorithms were used to obtain the experimental frequency spectrums shown in Figs. 3 and 9, they are not the most efficient method for real-time implementation. This is mainly due to their computational and memory requirements when processing large sequences of data. Instead, more suitable alternatives for real-time implementation such as the discrete Fourier transform (DFT) and the Goertzel algorithm can be used. Both algorithms are less efficient than the FFT when the whole frequency spectrum is needed, but have an advantage when determining a reduced number of components in the frequency spectrum. Both techniques are also easily implemented recursively, with their computational and memory requirements being almost independent of the number of samples that are processed. A. Separation of the Negative-Sequence Carrier-Signal Current While both the DFT and the Goertzel algorithm can operate directly on the stator current vector to separate the desired components of the negative-sequence carrier-signal current, spectral leakage caused by the fundamental current makes it desirable to use additional digital filtering. The spectral leakage is an artifact of both techniques operating in a discrete rather than a continuous fashion, which means they process a finite number of samples . Although no problem would exist if were chosen to provide enough spectral resolution, i.e., all the components present in the sampled signal correspond exactly to a frequency in the discrete spectrum, such an assumption is not realistic in practice. The spectral leakage caused by the fundamental current is especially important due to its magnitude: in the range of several hundred times the magnitude of the fault related components of the negative-sequence carrier-signal current. Due to this, the interference caused by the spectral leakage of fundamental current can still be an issue even with a relatively large spectral separation from the carrier-signal frequency. To assess the distortion caused by the fundamental current on the negative-sequence carrier-signal current, numerical simulations were conducted. Fig. 12 (top) shows the spec-

Fig. 12. Numerically calculated spectral leakage caused by the fundamental current (at its rated value) at the negative-sequence carrier-signal frequency as a function of the number of samples N , with (top) and without (bottom) a low-pass filter for isolating the negative-sequence carrier-signal current. The magnitudes are normalized to the value of the 2! component of the negative-sequence carrier-signal current shown in Fig. 9.

Fig. 13. a) Continuous equivalent of the coordinate transformation and second-order low-pass filter used to separate the negative-sequence carrier-signal current from the overall stator current, and (b) magnitude of its frequency response function, shown in a stationary reference frame. ! = 535:7 Hz, ! corresponding to a cutoff frequency of 10 Hz, = 0:707.

tral distortion caused by the fundamental current (when it is at its rated value) at the negative-sequence carrier-signal frequency as a function of the number of samples . From the figure, it can be seen that, even for large values of , the spectral leakage is in the range of several times the magnitude of the signal caused by the turn-to-turn or broken rotor bars faults (see Figs. 3 and 9), which could make the technique very unreliable if not addressed. In order to reduce the magnitude of the spectral leakage of the fundamental current, a digital, synchronous bandpass filter was used to isolate the negative-sequence carrier-signal current from the overall stator current before the signal processing of the DFT or Goertzel algorithm. The filter was obtained by discretizing a second-order low-pass filter, implemented in the negative-sequence carrier-signal synchronous reference frame. Its block diagram is shown in Fig. 13(a), and its frequency response function can be seen in Fig. 13(b). The improvement when the filter is used can be seen in Fig. 12 (bottom), where the spectral leakage caused by the fundamental current is reduced enough that it no longer compromises the reliability of the technique. B. Calculation of the Components of the Negative-Sequence Carrier-Signal Current Using the Goertzel Algorithm As already mentioned, both the DFT and the Goertzel algorithm can efficiently calculate the fault-related components


2! component of the negative-sequence 0 + 2! component in s stationary reference frame)

Fig. 14. Separation of the carrier-signal current ( ! using the Goertzel algorithm.

of the negative-sequence carrier-signal current frequency spectrum. For the case of the dc component (stator turn-to-turn faults) the algorithms can be shown to be equivalent, but for the case of rotor faults (frequency varying components), the Goertzel provides a simpler implementation and will be used. The Goertzel algorithm calculates a single component in the frequency spectrum of a signal by passing it through a recursive linear filter [22]. Equations (6) and (7) show the resulting and the implementations for isolating the dc component component of the negative-sequence carrier-signal current, respectively. Fig. 14 shows the implementation of (7) (6) (7) The Goertzel algorithm, as for any other DFT-based technique, does not operate in a continuous fashion but on a finite iternumber of samples , the results being obtained after ations of (6) or (7). It is also noted that results obtained from (6) and (7) are usually normalized by dividing by the number of samples . C. Influence of Fundamental-Frequency-Dependent Components of the Negative-Sequence Carrier-Signal Current As already mentioned, the selection of the number of samples to be processed is not totally arbitrary since its value determines the spectrum resolution, i.e., the separation between consecutive components that can be distinguished. Poor selection of will produce more spectral leakage, i.e., interference between different frequency components. The fundamental current is not the only source for spectral leakage. Similar problems can arise due to other components in the negative-sequence carrier-signal current, especially those caused by saturation-induced saliencies. While bandpass filters could also be used to separate saturation-induced harmonics from fault-related harmonics, they would require very narrow bandwidths for the filters due to the closeness, spectrally, of the negative-sequence components (see Figs. 3 and 9). These very narrow bandwidths, with associated long time constants, would result in excessively long fault detection times. These issues can be avoided through careful spectrum analysis and sample number selection. Turn-to-Turn Fault Detection: The criteria for optimally selecting the number of samples to be used for turn-to-turn detection when saturation-induced harmonics are present is shown in (8), where “round” converts the answer to the nearest integer and is a positive integer: round

(8)

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Choosing a value of different from that calculated using (8) will result in spectral leakage [22], which may cause errors in the isolation of the dc component. Since (8) is dependent on the fundamental frequency , it is important that the number of samples be dynamically calculated. Preventing spectral leakage from causing unreliable measurements for turn-to-turn fault detection, through this dynamic calculation of , was shown in [18] to be relatively easy. In addition, it was shown in [18] that , of a very short durations (a few secsampled times, onds) were enough to prevent spectral leakage from seriously influencing the measurements. Finally, it should be noted that and, therefore, , does not mean bigger comincreasing putational or memory requirements due to the recursive nature of the algorithm used to extract the dc component of the negative-sequence carrier-signal current. Rotor Fault Diagnosis: Rotor fault diagnostics using high-frequency voltage injection present important complications when compared to turn-to-turn fault detection. As already noted, no-load operation, with flux present in the machine, is not suitable for diagnostic purposes since the harmonic at spectrally coincides with the rotor-fault-related harmonic . Assuming that the machine operates under a loaded at component of the condition, accurate estimation of the negative-sequence carrier-signal current requires to be selected to simultaneously meet two conditions. First, to component of the prevent the energy associated with the negative-sequence carrier-signal current, which contains the rotor fault information, from being spread over a wide range of frequencies, i.e., to ensure that its energy is concentrated into a single frequency component (see in Fig. 9), (9) must be met. Second, to prevent the fundamental-frequency-dependent components of the negative-sequence carrier-signal current from spectrally leaking, and causing distortion of the component, (10) must be met. and in (9) and (10) are positive integer numbers round

(9)

round

(10)

and cannot be guaranSince synchronization between and teed to exist in general, finding the integer constants for the simultaneous verification of (9) and (10) is not easy, unless a large number of samples is used. In the limit, a number of samples calculated using (11) would be required (11) However, for low fundamental frequencies (11) can result in several hundreds of thousands of samples being required and, in the range of teens of seconds. Since consequently, the machine is assumed to be operating in the steady state during , increase the test, such large values for the sampled times, the risk of transients, resulting in incorrect measurements. To better understand the influence that spectral leakage from component can have on the measurement of the rotorthe

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component of the negative-sequence carrier-signal current are plotted as a function of the slip for two different sampled time periods, . There is good agreement between Figs. 15 and 16. VI. CONCLUSION

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Fig. 15. Numerically calculated regions for the magnitude of the ! component of the negative-sequence carrier-signal current, as a function of the slip (! kept constant, ! varied according to the slip) for two different lengths of the sampled data t.

1

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Fig. 16. Experimentally measured magnitude of the ! component of the negative-sequence carrier-signal current, as a function of the slip (! kept constant, ! varied according to the slip) for two different lengths of the sampled data t.

1

fault-dependent component at , when only (9) is met, a numerical analysis was performed. Similar analysis was used in [18] for the case of turn-to-turn faults. Fig. 15 shows the surcomponent faces containing all the potential values of the of the negative-sequence carrier-signal current frequency spectrum as a function of the slip, when only (9) is met, for two , of 1 and 4 different lengths of the sampled time, 15 000 and 60 000 respectively, using a 15-kHz sams( was considered. pling frequency). A single component at The magnitude of the rotor-fault-dependent component and the component of the negative-sequence carrier-signal current are the same as shown in Fig. 9. From Fig. 15 it can be seen that uncertainty in the measurecaused by spectral leakage of the compoment of the nent becomes more important for low values of slip, i.e., when the two components of the negative-sequence carrier-signal current are spectrally close. It is also seen that, as the sampled time, , increases, and as a consequence the spectral resolution increases, the distortion of the component decreases. Experimental results confirming this behavior are shown in Fig. 16, where different successive measurements of the

This paper has analyzed and discussed the use of high-frequency carrier-signal injection for online fault detection in induction machines. The injection of a low-magnitude high-frequency voltage, superimposed on the fundamental excitation, with the measurement of the resulting negative-sequence carrier-signal current has been shown to effectively detect faults at their incipient stages both in the stator and rotor. In addition, a reduced sensitivity to the working condition of the machine, i.e., to the flux level, load level, fundamental excitation frequency, and temperature, was also obtained. While broken rotor bar detection has been shown to be viable with a machine having semi-open rotor slots, the rotor-fault-rein the negative-sequence carrier-signal lated component at current spectrum was found to be too small for the case of closed-rotor-slot machines to allow reliable rotor fault detection. The technique can be easily implemented in standard torquecontrolled ac drives, with no additional hardware requirements, and requiring only very minor additional signal processing. Machine size is not expected to have a significant impact on the technique’s performance, provided that the switching frequency of the inverter feeding the machine is high enough to allow for the injection of a carrier-signal voltage in the range of several hundred hertz, i.e., spectral separation between the carrier signal and the switching frequencies. Supporting this, carrier frequencies as large as one-fourth of the switching frequency have successfully been used. ACKNOWLEDGMENT The authors wish to acknowledge the support and motivation provided by the University of Oviedo, Gijón, Spain, and the Ford Motor Company. REFERENCES [1] G. Stone and J. Kapler, “Stator winding monitoring,” IEEE Ind. Applicat. Mag., vol. 4, pp. 15–20, Sept./Oct. 1998. [2] A. H. Bonnett, “Available insulation systems for PWM inverter-fed motors,” IEEE Ind. Applicat. Mag., vol. 4, pp. 15–26, Jan./Feb. 1998. [3] W. T. Thomson and M. Fenger, “Current signature analysis to detect induction motor faults,” IEEE Ind. Applicat. Mag., vol. 7, pp. 26–34, May/June 2001. [4] J. Sottile, F. C. Trutt, and J. L. Kohler, “Experimental investigation of on-line methods for incipient fault detection,” in Conf. Rec. IEEE-IAS Annu. Meeting, Rome, Italy, Oct. 2000, pp. 1282–2687. [5] J. L. Kohler, J. Sottile, and F. C. Trutt, “Condition monitoring of stator windings in induction motors: Experimental investigation of the effective negative-sequence impedance detector,” IEEE Trans. Ind. Applicat., vol. 38, pp. 1447–1453, Sept./Oct. 2002. [6] S. B. Lee, R. M. Tallman, and T. G. Habetler, “A robust, on-line, turnfault detection technique for induction machines based on monitoring the sequence component impedance matrix,” IEEE Trans. Power Electron., vol. 18, pp. 865–872, May 2003. [7] S. M. A. Cruz and A. J. M. Cardoso, “Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended park’s vector approach,” IEEE Trans. Ind. Applicat., vol. 37, pp. 1227–1233, Sept./Oct. 2001.


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[8] M. F. Cabanas, M. G. Melero, G. A. Orcajo, F. Rodriguez, and J. Solares, “Experimental application of the axial leakage flux to the detection of rotor asymmetries, mechanical anomalies and inter-turn short-circuits in working induction motors,” in Proc. ICEM’98, Istanbul, Turkey, Sept. 1998, pp. 420–425. [9] N. Arhtur and J. Penman, “Induction machine condition monitoring with higher order spectra,” IEEE Trans. Ind. Electron., vol. 47, pp. 1031–1041, Oct. 2000. [10] R. M. Tallam, T. G. Habetler, and R. G. Harley, “Stator winding turnfault detection for closed-loop induction motor drives,” IEEE Trans. Ind. Applicat., vol. 39, pp. 720–724, May/June 2003. [11] A. V. Jouanne, P. Enjeti, and W. Gray, “Applications issues for PWM adjustable AC motor drives,” IEEE Ind. Applicat. Mag., vol. 2, pp. 11–18, Sept./Oct. 1996. [12] G. Stone, S. Campbell, and S. Tetreault, “Inverter-fed drives: Which motor stators are at risk?,” IEEE Ind. Applicat. Mag., vol. 6, pp. 17–22, Sept./Oct. 2000. [13] L. Manz, “Motor insulation system quality for IGBT drives,” IEEE Ind. Applicat. Mag., vol. 3, pp. 51–55, Jan./Feb. 1997. [14] A. H. Bonnett, “Analysis of the impact of pulse-width modulated inverter voltage waveforms on AC induction motors,” IEEE Trans. Ind. Applicat., vol. 32, pp. 386–392, Mar./Apr. 1996. [15] P. L. Jansen and R. D. Lorenz, “Transducerless position and velocity estimation in induction and salient AC machines,” IEEE Trans. Ind. Applicat., vol. 31, pp. 240–247, Mar./Apr. 1995. [16] M. W. Degner, “Flux, position and velocity estimation in ac machines using carrier frequency signal injection,” Ph.D. dissertation, Dept. Mech. Eng., Univ. Wisconsin, Madison, WI, 1998. [17] A. Bellini, G. Franceschini, N. Petrolini, C. Tassoni, and F. Filippetti, “Induction machine rotor position detection for diagnostiuc or control aims: Possibilities and problems,” presented at the EPE’01, Graz, Austria, Aug. 2001. [18] F. Briz, M. W. Degner, J. M. Guerrero, and Zamarron, “On-line stator winding fault diagnosis in inverter-fed AC machines using high frequency signal injection,” IEEE Trans. Ind. Applicat., vol. 39, pp. 1109–1117, July/Aug. 2003. [19] N. Teske, G. M. Asher, M. Sumner, and K. J. Bradley, “Analysis and suppression of high-frequency inverter modulation on sensorless position-controlled induction machine drives,” IEEE Trans. Ind. Applicat., vol. 39, pp. 10–18, Jan./Feb. 2003. [20] F. Briz, M. W. Degner, A. Diez, and R. D. Lorenz, “Implementation issues affecting the performance of carrier signal injection based sensorless controlled AC drives,” in Conf. Rec. IEEE-IAS Annu. Meeting, Chicago, IL, Sept. 30 –Oct. 5, 2001, CD-ROM. [21] M. F. Cabanas, M. G. Melero, G. A. Orcajo, J. M. Cano, and J. Solares, Maintenance and Diagnostic Techniques for Rotating Electric Machinery. Barcelona, Spain: Marcombo-ABB, Boixareu Ed., 1999, pp. 310–311. [22] A. V. Oppenheim and R. W. Schafer, Discrete Time Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.

Fernando Briz (A’96–M’99) received the M.S. and Ph.D. degrees from the University of Oviedo, Gijón, Spain, in 1990 and 1996, respectively. From June 1996 to March 1997, he was a Visiting Researcher at the University of Wisconsin, Madison. He is currently an Associate Professor in the Electrical Engineering Department, University of Oviedo. His topics of interest include control systems, high-performance ac drives control, sensorless control, and digital signal processing.

Michael W. Degner (S’95–A’98–M’99) received the B.S., M.S., and Ph.D. degrees in mechanical engineering from the University of Wisconsin, Madison, in 1991, 1993, and 1998, respectively, with a focus on electric machines, power electronics, and control systems. In 1998, he joined the Ford Research Laboratory of Ford Motor Company, Dearborn, MI, where his research focused on the use of power electronics in automotive applications. He is currently Project Leader of the Power Electronics and Electric Drives group in the Sustainable Mobility Technologies Laboratory of Ford Research and Advanced Engineering. His interests include control systems, electric machines and drives, power electronics, and mechatronics.

Alberto B. Diez (M’99) received the M.S. and Ph.D. degrees from the University of Oviedo, Gijón, Spain, in 1983 and 1988, respectively. He is currently an Associate Professor in the Electrical Engineering Department, University of Oviedo. His topics of interest include control systems, highperformance ac drives control, and industrial supervision processes. Dr. Diez was a Member of the Executive Committee D2 “Rolling-Flat Products” of the European Commission for the last six years.

Juan Manuel Guerrero (S’00) was born in Gijón, Spain, in 1973. He received the M.E. degree in industrial engineering and the Ph.D. degree in electrical and electronic engineering from the University of Oviedo, Gijón, Spain, in 1998 and 2003, respectively. Since 1999, he has been a Teaching Assistant in the Electrical Engineering Department, University of Oviedo. From February to October 2002, he was a Visiting Scholar at the University of Wisconsin, Madison. His research interests include parallel-connected motors fed by one inverter, sensorless control of induction motors, control systems, and digital signal processing. Mr. Guerrero received an award for his Masters thesis from the College of Industrial Engineers of Asturias and León, Spain, in 1999.