INVESTIGATION ON THE DIAGNOSIS OF SIMPLE AND COMBINES MECHANICAL FAULTS IN ASYNCHRONOUS MOTOR BASED ELECTRIC DRIVES

In this study, the problems of mechanical unbalance , parallel and angular misalignments and their combinations are analyzed experimentally. Such freq uent defects in the drives mainly in the major powe rs are also responsible for the bearings degradation. H wever, they have not raised the attention of rese archers, given the complexity of their modeling. The combina t on of the phasic current signal analysis and the neutral current by the FFT supplemented by visual i nterpretation of patterns models these defects resu lting from the 3D representation. The results obtained by using the proposed method show the efficiency to provide an accurate diagnosis of the state of the e lectric drive undergoing to isolated and combined mechanical defaults to a maintenance staff not nece ssarily expert of mechanical failure. The innovativ e approach validated experimentally on a 5.37 KW moto r, offers an efficiency to provide an accurate diagnosis to a maintenance staff not necessarily co mposed of experts in this field.


INTRODUCTION
The monitoring of electrical drives has interested many researchers so far (Sethom and Ghedamsi, 2012;Li and Meshefske, 2006;Bindus and Vinod, 2014;Pandey et al., 2012). As provided in Thorsen and Dalva (1995), Bonnett and Yung (2008), Thorsen and Dalva (1998), the repartition of many older publications on the defects of high power asynchronous machines has changed due to the motors production conditions. The unbalance, misalignment or their fusion that affects rotating machines, particularly those that are subject to considerable mechanical stress, generate mechanical vibration (Xu and Marangoni, 1994;Scheffer and Girdhar, 2004). They are considered as the main causes of other mechanical and electrical defects. The extensive studies that have been carried out by researchers using vibration analysis for the study of unbalance and misalignment have shown the complexity of diagnosis with vibration analysis. As reported in Thomson and Fenger (2001), Martınez-Morales et al. (2010), the high sensitivity of the current towards the torque variations sensed by the asynchronous motor and consequently towards simple and multiple mechanical defects that induce them, makes from its analysis an extremely powerful investigation tool. This paper tends toward an experimental approach for the diagnosis and detection of the aforementioned mechanical anomalies. Using signal processing, this approach is based on the knowledge of the healthy system's behavior which is then compared with the signals measured during different tests of the machine degradation (Concari et al., 2010;Medoued et al., 2009). Compared to previous works, this experimental research uses a combination of techniques by analyzing the phasic current (Kazzaz and Singh, 2003); Oumaamar et al. (2009)

insufficiently developed when it comes to
Science Publications AJAS unbalance, misalignment and especially their combinations. To reduce the overlapping frequencies that can coexist in the spectra when it comes to these deficiencies, a content analysis of the signal information of the current flow in the neutral conductor is conducted (Oumaamar et al., 2007). Then, to distinguish between the defects signatures, this technique is supported by a 3D representation of the square of the intensity of the motor supply current which, hitherto, has been subjected only to the treatment of the short circuits stator windings and rotor bars breaks (Martins et al., 2011;Pires et al., 2010). The results obtained are satisfactory. They can witness the robustness and effectiveness of this technique without a physical contact and through a remote monitoring of unique and multiple mechanical defects.

The Effects of the Mechanical Faults on the Spectrum of the Current
The results mentioned in several articles have shown that the imbalance and misalignment can be detected from the motor's vibration (Patel and Darpe, 2009;Sekhar and Prabhu, 1995;Wongsuwan et al., 2006) and electric measurements (Cameron et al., 1986).
These single or combined mechanical defects generate an eccentricity in the air gap affecting a variation in the motor's inductance. Consequently, a variation of the magnetic flux that contributes in modifying the supply current spectrum (Dorrell et al., 1997;Chaudhury et al., 2013;Sahraoui et al., 2008) compared to that of the healthy drive motor Equation 1: The induced tension V i (T) corresponding with this flux is Equation 2: Consequently, the stator current modulated in phase i t0 (T) for an arbitrary phase in the presence of an oscillating torque is expressed by Equation 3: So: Where: φ A = Denotes the phase angle of the modulation. This shows that the fundamental component of current to is(t) the sum of two components: The term (t) results of the stator magneto motive force and it is not modulated. The Term ir (t), which is a direct consequence of the rotor MMF shows the phase modulation due to the oscillations of torque and speed. Healthy case is obtained for m = 0.

Mechanical Defects Signatures in the Current Phase
Imbalance and misalignment Defects are detectable by appropriate frequency monitoring of the stator current phase (Blodt et al., 2010;Ibrahim et al., 2008;Blodt et al., 2005) Equation 4: The unbalance leads to the increase of the frequencies amplitude defined by n = 1 Equation 5: Most misalignments are a combination of angular and parallel ones. They generate additive amplitudes and frequencies modulated in the stator current Equation 6: dés.
S r f = f + nf (6) With n = 2, 3,4 Where: f d = The carrier frequency of the mechanical failure f s , f r = The power supply frequency and the rotation frequency respectively

Mechanical Defects Signatures in the Neutral Current
The change of the neutral current spectrum in the vicinity of the third order harmonic and its multiples is revealing valuable information about the state of the motor. These information are comparable with those of the phase current or even better Equation 7 and 8: With : h = 3,5,7,… et k = 1, 2,3,4,…..

The Combined Defects Detection by the Analysis of the Currents and Neutral Phase
When it comes to the combination of unbalance and misalignments, all the frequency characteristics of these defects appear in the spectra of the currents and neutral phases, with a prominent increase in amplitudes of the concerned lines.

Defects Signatures by Analyzing the Square of the Intensity of the Phase Currents (Pires et al., 2010)
IA, IB and IC = The three stator currents Im = Maximum value of the supply phase current ω = Supply frequency ϕ = The phase angle T = Time variable In the 3D stator current pattern, also we denote a circle centered at the origin of the coordinates, for ideal condition where its radius R is Equation 9: The obtained orbits have ellipsoidal, polygonal or hypocycloidal shapes according on the nature of the defect that occur on the drive. Thus, a visual interpretation of the patterns is affiliated for every type of fault.

DESCRIPTION OF THE EXPERIMENTAL SETUP AND TESTING CAMPAIGNS
A test rig was required for the experimental study of imbalance, parallel and angular misalignment mechanical defects whether simple or combined that could affect asynchronous motor based electrical drives during their functioning.
It consists essentially of an aggregate of electrical machines (Fig. 1) consisting of an asynchronous motor (4.05 kW, 1430 r/min, 220 V/380 V, 7.5/13A; 50 Hz). Coupled to a DC generator (4 kW, 220 V; 14A; 1500 trs/mn) filler material. The data processing is done using MATLAB software for signal analysis. Unbalanced mechanical defects, parallel misalignment, angular misalignment and their combination were created artificially. A mass of 50 grams fixed on the motor shaft has been used for the intentional creation of the unbalance. The parallel and angular misalignments were exercised virtually lifting the induction motor using plates 2 mm under the four brackets for parallel and only under the two front legs or back for angular misalignment. Then we proceeded to the combination unbalanced faults with axial and angular misalignments on aggregate. This latter was subjected to load variations (in vacuum then 50 and 75%). Only half load tests have been shown to avoid cluttering the document.

DISCUSSION OF THE TEST CAMPAIGN RESULTS
During the operation of the machine aggregate, in the lack of the defects targeted by our study, no significant alteration was observed in the content of the current spectrum of the stator phase. Only sidebands around the prominent harmonics are found even when the machine is healthy. This is due to the ideal theoretical conditions which are not met and manufacturing imperfections. When the motor operates in degraded mode due to an unbalance of 50 g, the presence of lines at 26.17 and 73.83 Hz frequency reflects this fault and verifies the relation (4) with 1f r = 23.83 Hz.

AJAS
In the case of misalignment, a clear emergence appears on line at f dés. = 50+2 f r of 97.76 Hz with an more attenuated prominent amplitude for angular misalignment. We should note that the lines with frequencies f unb. = f S ±f r however, are attenuated, they still exist in the current spectrum, but they are overlapped by those of misalignments. When the machine aggregate is subjected to the combination of unbalance and misalignment defects, the frequency signatures 50±f r and 50+2 f r appear together in the spectrum of the phase current with a significant arithmetic addition of their magnitudes.
Regarding the spectrum of the neutral current (Fig.  5), a weakening of the amplitude of the fundamental (50 Hz), the preponderance of the 3rd harmonic (150 Hz) and the 5th harmonic (250 Hz) is observed. In the presence of imbalance defects (Fig. 5b), sidebands are noticed around the relevant harmonics of order 3,5,7,9 with the emergence of frequencies 226, 274, 374 and 326 Hz. It should be noted that more apparent sidebands are induced by the unbalance defect at 5f s ±f r et 7f s +f r . Due to a misalignment in the drive, the spectrum of neutral current (Fig. 6a) reveals the prominent emergence of lateral lines at frequencies 5f s ±2f r , as well as the frequency 5f s ±f r , but with a slight increase in their amplitudes. The frequencies 3f s ±2f r , 5f s ±f r , 5f s ±2f r and 7f s ±f r are introduced into the spectrum of the neutral current as a result of the combined fault of unbalance and misalignment (Fig. 6b).
A significant arithmetic addition of the amplitudes of the frequencies that correspond to unbalance and misalignment is noted. It is worth mentioning that the effect of the load variation had no significant effect on all failures. The faults signatures can even be hidden through the increase in the load by using the noise damping.
The faults signatures can even be hidden through the increase in the load by using the noise damping. When the drive via the motor is not subject to any defect (healthy), the pattern obtained by the 3D representation of the square of the vector resulting from (I A 2 + I B 2 + I C 2 ) takes the form of an orbit not completely circular (Fig.  7), but rather ellipsoidal. This is explained by the absence of ideal operating conditions and manufacturing imperfections of the machine aggregate. This ellipsoid is strongly narrowed when the motor functioning is degraded by the presence of imbalance (Fig. 8). The pattern interpreting the default tends toward a hypocycloid shape (Fig. 9) if a misalignment affects the electric drive. This hypocycloidal geometry narrows enormously if the unbalance merges with the misalignment (Fig. 10) and gives the impression that the imbalance tends to hide the misalignment. These visual signatures in patterns accompanied by spectral analysis to help decide on the type and nature. Figure 2 shows the temporal characteristic and the current spectrum for healthy case. In Fig. 3, the three spectra of the stator current phase are shown (Fig. 3a) on the left, with the spectral content when the motor is subject to an imbalance. At the middle (Fig. 3b) and the left (Fig. 3c), spectral contents are respectively exposed when the motor faces a parallel misalignment and then an angular misalignment. Fig. 4a and 4b show the spectra and the emergence of the characteristic frequencies of the combination of the unbalance with parallel misalignment and angular misalignment respectivel.  Figure 5a shows the spectrum in the case of nondegraded machine, where the preponderance of the third harmonic followed by the fifth harmonic and the fundamental mitigation are noticed. The Figure 5b shows the spectrum of the neutral current in the case of faulty asynchronous motor in the presence of unbalance on its mechanical transmission shaft. Figure 6a illustrates the spectrum of neutral current for the defectiveness of the alignment. Figure  6b is about the frequencies introduced by the combined defects of unbalance and misalignment in the spectrum of the neutral current. Figure 7 shows the pattern obtained by the 3Dspatial representation of the model when the drive, via the motor, is not subject to any defect (healthy). Figure 8-10 show the representation of the patterns during the operation of the drive system, in the presence of an unbalance, misalignment and then a combination of these two defects.

CONCLUSION
In this experimental investigation, the diagnosis of isolated and combined mechanical failures have been discussed. Diagnostic capacities and remote detection without physical contact with the faulty machine components have become more robust. The experimental results confirm that the studied mechanical defects generate additional amplitudes and frequencies in the supply current signal. These simple and combined mechanical defects are easily detectable and identifiable through the analysis of the phase current and neutral current (FFT) supplemented by a visual reading of the patterns that correspond to each type of anomaly. The implementation of this simple and low-cost methodology characterized by an easily accessible interpretation of results can benefit from a wide range of use. It can contribute to the development of an expert systems for the diagnosis of single and multiple mechanical failures affecting the electric drives.