3-Phase induction motors are widely used as a source of mechanical power for effective operation and low costs. The abnormalities have to be detected in advance to avoid the motor breakdown and the cost associated restrain of plant production. This work discusses current and flux leakage spectral analysis techniques for the diagnosis of broken rotor bars and shortcircuited turns in induction motor fed from different AC sources.
In spite of recent development of various types of models toward motor faults diagnosis and examining different problems associated with 3-phase induction motors the signal spectral analysis is considered as one of most important approaches. Most of the models from simple equivalent circuit to more complex d-q and a-b-c models and lastly developed hybrid models are provided for the integration of different forms of current and/or voltage unbalance. Generally, techniques that relate to asymmetry identify asymmetrical motor faults.
Frequency converters in many applications feed induction motors. Such applications, which play a major role in industry, are growing at a high rate, allow to use 3-phase induction motor as variable speed applications. This paper proposes application of spectral signature analysis for the detection and diagnosis of abnormal electrical and mechanical conditions, which indicates chosen faults in induction motor fed by frequency converter.
Contents
Abstract
Thesis objectives
1. Introduction
Thesis plan
2. Literature review
Electrical and mechanical monitoring using MCSA techniques
Asymmetry Based Techniques
Other Condition Monitoring Techniques
Literature Review Summary
3. COMMON MOTOR FAULTS
Rotor Faults
Short Turn Faults
Effect of current component on the motor faults caused by varying inductance
Test Circuit for Faults Simmulation
4. Motor Fault Diagnosis Using Signal Signature Analysis
Motor Current Signature Analysis Using FFT
Detection of Broken Rotor Bars in Three-Phase Induction Motor Using Fast Fourier Transform
Rotor Slot Harmonics
Motor harmonics of Broken Bars Fault
Detection of stator in-turn short circuit using FFT analyses of current
Detection of Air Gap Eccentricity Using FFT Signature Analysis
5. EXPERIMENTAL STUDY OF STATOR AND ROTOR FAULTS DIAGNOSIS OF A THREE-PHASE INDUCTION
MOTOR
Current Spectral Analysis
Steps Involved In Motor Fault Diagnosis Using FFT Technique
6. DETECTION OF BROKEN ROTOR BAR FAULTS USING FAST FOURIER TRANSFORM (FFT) and LabVIEW
program
Experimental Setup
System Representation Using LabVIEW Program
Data Acquisition Parameters
7. ANALYSIS AND DISCUSSIONS OF BROKEN BARS FAULT
No-load Healthy Rotor Fed by an Induction Regulator at 50 Hz
No-Load Faulty Rotor Fed by an Induction Regulator at 50 Hz
Loaded Healthy Rotor Fed by an Induction Regulator at 50 Hz
Loaded faulty rotor from an induction regulator at 50 Hz
No-Load Healthy Rotor Fed by a Frequency Converter at 40 Hz
No-Load Faulty Rotor Fed by a Frequency Converter at 40 Hz
Loaded Healthy Rotor Fed by a Frequency Converter at 40 Hz
Loaded Faulty Rotor Fed by a Frequency Converter at 40 Hz
No-Load Healthy Rotor Fed by a Frequency Converter at 50 Hz
No-Load Faulty Rotor Fed from a Frequency Converter at 50
Loaded Healthy Rotor Fed by a Frequency Converter at 50 Hz
Loaded Faulty Rotor Fed by a Frequency Converter at 50 Hz
No-Load Healthy Rotor Fed from a Frequency Converter at 60 Hz
No-load faulty rotor fed by a frequency converter at 60 Hz
Loaded healthy rotor fed by a frequency converter at 60 Hz
Loaded faulty rotor fed by a frequency converter at 60 Hz
7.1 Discussion of Rotor Fault Analysis
Motor fed from a voltage regulator at 50 Hz
Rotor fed from frequency converter 40 Hz
Rotor fed from frequency converter 50 Hz
Rotor fed from frequency converter 60 Hz
Summary
8. DIAGNOSIS OF SHORT-CIRCUITED TURNS FAULT IN STATOR WINDINGS USING FFT TECHNIQUE
ANALYSIS AND DISCUSSIONS SHORT CIRCUIT STATOR FAULT
No-load healthy stator fed by an induction regulator at 50 Hz
No-load faulty stator fed by an induction regulator at 50 Hz
Loaded healthy Stator fed by a Induction regulator at 50 Hz
Loaded faulty Stator fed by a Induction regulator at 50 Hz
No-load healthy Stator fed by a frequency converter at 40 Hz
No-load faulty Stator fed by a frequency converter at 40 Hz
Loaded healthy Stator fed by a frequency converter at 40 Hz
Loaded faulty Stator fed by a frequency converter at 40 Hz
No-load healthy Stator fed by a frequency converter at 50 Hz
No-load faulty Stator fed by a frequency converter at 50 Hz
Loaded healthy Stator fed by a frequency converter at 50 Hz
Loaded faulty Stator fed by a frequency converter at 50 Hz
No-load healthy Stator fed by a frequency converter at 60 Hz
No-load faulty Stator fed by a frequency converter at 60 Hz
Loaded healthy Stator fed by a frequency converter at 60 Hz
Loaded faulty Stator fed by a frequency converter at 60 Hz
8.1. Discussion of stator diagnosis analysis
Stator fed from induction regulator 50 Hz
Stator fed from frequency converter 40 Hz
Stator fed from frequency converter 50 Hz
Stator fed from frequency converter 60 Hz
Summary
9. Conclusion
Reference List
Abstract
3-Phase induction motors are widely used as a source of mechanical power for effective operation and low costs. The abnormalities have to be detected in advance to avoid the motor breakdown and the cost associated restrain of plant production. This work discusses current and flux leakage spectral analysis techniques for the diagnosis of broken rotor bars and short- circuited turns in induction motor fed from different AC sources. In spite of recent development of various types of models toward motor faults diagnosis and examining different problems associated with 3-phase induction motors the signal spectral analysis is considered as one of most important approaches. Most of the models from simple equivalent circuit to more complex d-q and a-b-c models and lastly developed hybrid models are provided for the integration of different forms of current and/or voltage unbalance. Generally, techniques that relate to asymmetry identify asymmetrical motor faults.
Frequency converters in many applications feed induction motors. Such applications, which play a major role in industry, are growing at a high rate, allow to use 3-phase induction motor as variable speed applications. This paper proposes application of spectral signature analysis for the detection and diagnosis of abnormal electrical and mechanical conditions, which indicates chosen faults in induction motor fed by frequency converter.
Keywords; Induction Motor Faults, Frequency Converter, Diagnosis Techniques
Thesis objectives
The main objective of this paper is to diagnose the common faults that results from current and voltage related conditions with suitable signal processing techniques. Different signals in a motor contain unique fault frequency components associated with motor faults. Hence, the second aim is to investigate how the presence of common faults, such as rotor bar fault and short winding fault affect current signals when fed from an induction regulator and a frequency converter. The third aim is to formulate necessary signal collection conditions and the signal-processing techniques (Fast Fourier Transform - FFT) for effective broken rotor and short- circuited turns in stator winding fault detection. Finally, the aim of the thesis is to make use of the Matlab program to process the data collected from the LabVIEW virtual measurement instrument.
1. Introduction
A 3-phase induction motor is an asynchronous machine with alternating current with power supplied to the rotor by electromagnetic induction. It comprises of a magnetic circuit, which inter-links with two electric circuits, rotating with respect to each other by means of electromagnetic induction. There are two types of rotor windings a in a 3-phase induction motor: squirrel cage and wound rotor type. Squirrel cage type motors consist of conducting copper, aluminum, or alloy bars embedded in slots in the rotor and short-circuited at their ends by a conducting ring. Wound rotors consist of three phase windings and its ends connected to slip rings mounted on the rotor shaft. 3-phase induction motors frequently experience various faults due to harmful operating conditions such as inadequate cooling, insufficient lubrication,
misalignment of the shaft overloading etc. Major induction motor faults fall under two categories, electrical and mechanical faults. Electrical faults rise due to stator faults that result in short-circuiting one or more windings in the motor. Broken rotor bars can be also associated with the shorted turns in the stator windings. Once the broken bars hits to the end of winding or stator core, which is of high voltage motor at high velocity, they cause extreme mechanical damage to the insulation leading to shorted turns in the stator. In addition, they may result from abnormal connection of stator windings. Mechanical faults may arise as result of broken rotor bars or connecting ring, static and dynamic air-gap irregularities, bent shaft resulting to friction between the rotor and stator that cause massive damage to stator core and windings and lastly due to bearing and gearbox failures. Frequency converter also plays a major role in 3-phase induction motor, as it is responsible for feeding the 3-phase induction motor with the 3-phase power supply. Estimations show that rotor related faults account for 8-10% of motor faults while that of stator windings accounts for 26-37%. Furthermore, the frequency at which different types of motor faults occur are shown below in figure 1.
Statistical distribution of motor faults
- Bearing Faults
- stator faults
- Broken rotor bars
- Eccentricities
Figure 1. (Cusidu p.2011, stastical distribution of motor faults).
An induction motor that operates under these faults may express various uncertainties such as increased torque pulsations, unbalanced air-gap voltages and line currents, decrease in recommended torque, excessive heating, and increase in losses that decreases the motors’ efficiency. Fault diagnosis and protection of 3-phase induction motor has a history that can be traced back to the beginning of introduction machines. Various condition-monitoring and diagnosis motor faults methods are developed to improve the efficiency of a motor driven plant. They include radio frequency emissions monitoring, vibration monitoring, current monitoring, Motor Current Signature Analysis, thermal monitoring, acoustic emission monitoring, and chemical monitoring which require expensive sensors to work effectively. Failure to detect motor faults can lead to zero output of the entire plant or even a disaster. Most proposed analyses aim motor current analysis as it has proven to be a non-invasive technique in industries.
Motors faults have necessitated the need to develop experimental fault diagnosis for practical application in industries. The main faults from motor statistics shows that rotor and the stator compromise the larger percentage thus effective methods are implemented with the help of computer programs such as LabVIEW and Matlab. One of them is signal processing analysis accompanies with spectral analysis of the frequency components. This paper used the fast Fourier Transform (FFT) signal processing technique.
illustration not visible in this excerpt
Figure 2. Thesis plan
2. Literature review
Electrical and mechanical monitoring using MCSA techniques Many different techniques are used for the fault diagnostics of an induction motor rotor. Most of these techniques have their merits and demerits accordingly. Fast Fourier analysis is a key condition monitoring technique for most industrial applications where the signals are stationary such as the diagnostic of rotor broken bar and short turns in stator winding faults of motor driven electrical machines. Its purpose is to monitor a single-phase stator current. This possibility is achieved by removing the excitation frequency component through the low-pass filtering and sampling of the resulting signal. A current transformer that is sent to a 50 Hz notch filter where the fundamental component is decreased senses the single-phase current. The amplification of the signal then takes place along with the low-pass filtering. The aim of filtering is to remove the unnecessary high-frequency components responsible for producing the aliasing of the sampled signal. The purpose of amplification is to maximize the use of the analog-to-digital converter input range.
(Aderiano & Silva, 2006) acknowledged that spectral signature analysis that uses the spectrum of the stator current to detect fault from broken rotor bars is one of the most effective method that deals with the physical phenomenon of the motor. Broken bars in a motor results in variations of motor supply current. This technique uses generally the principle of frequency component magnitudes of stator currents and particularly on the magnitude of certain frequency components of the stator currents. First spectral that is less than the fundamental is referred to as sideband which is measured and compared to the threshold frequency. The obtained results compared the two frequencies that help to determine if a 3-phase induction motor has broken rotor bars. This work verified the feasibility of current spectral analysis. In addition, current signature analysis technique in 3-phase induction motor detects faults such as damaged bearing, and eccentricity of the rotor axis.
(Albizu & A. Mazon, 2006) proposed an online induction motor analysis. This majorly applies to low voltage induction motors where the inter-turn short circuit appearance indicate the presence of motor fault. This method depends on the level of input voltage and involves a programmed pattern that monitors the motor. This leads to monitoring of the partial discharge. This method provides high diagnostic efficiency on techniques such as negative-sequence current and sequence impedances but low efficiency on other faults diagnosis methods.
(Khalaf & Hew, 2011) applied the wavelet transform to diagnose the rotor faults. Motor was analyzed when healthy and with chosen faults. The difference signal at the 11th level of onedimensional discrete wavelet analysis-wavelet decomposition with the motor tree is used to detect motor fault. RMS of this 11th dll wavelet coefficient and those that are obtained from off-line diagnosis techniques are observed and a comparison of the two is made to detect the motor faults.
Asymmetry Based Techniques
Motor asymmetry based methods is another approach, which are object/motor parts- oriented technique. Park’s vector approach is effective in diagnostic process, as it does not require the neutral line terminal. The other method is the Negative sequential components of the stator current technique based on detections of asymmetries produced by faults and is used to detect inter-turn short circuits of the rotor. This usually causes magnetic field distortions. The asymmetries generate a negative sequence current that is used in fault detection. A negative sequence is derived from vector analysis of unbalanced 3-phase currents or voltages that feed the motor (Aderiano M. & Silva B., 2006).
In Negative-Sequence Current, short turns in the stator windings results in asymmetry between the three phases hence altering the negative -sequence component in the line current. There is an increase in negative-sequence current whenever a shorted turns are present. Negative-sequence current la2 is calculated from the measurements of the three line currents. Hence,
illustration not visible in this excerpt
Where; a = e~ i.e. exponential of inductance/slip, la2 - Negative-sequence current, lac- Short-circuit current.
The inherent motor asymmetries may differ from the instrumentation considering that the unbalanced supply voltages produce a similar effect. This necessitates the consideration of these non-idealities in fault detection strategy as results have shown that negative-sequence appears even in a healthy motor due to these factors. Short turns occurrences increase the asymmetry that already exist. When the motor is not symmetric, the positive and negative sequences become interdependent. Hence, there will be negative-sequence current even if the supply voltage is symmetrical and has no negative-sequence component.
illustration not visible in this excerpt
Fig 3. Diagrammatically representation of different causes of negative-sequence current
Therefore, the negative-sequence la2 is a contribution of the tree components. To determine the current due to faults Isca2 , current due to voltage imbalance (Iva2) and the inherent current (Ta2) subtracted from the measured negative sequence current(/a2). An increase la2 in indicates short circuit.
illustration not visible in this excerpt
This method has a limit such that the fault severity cannot be determined. In addition, the motor and sensors asymmetries decrease considerably the sensitivity of the indicator. This is because equation is true only if the motor is perfectly symmetric. If this is not the case, there is an interaction between the sequence components.
Zero-sequence voltage approach applies to the star connected induction motors with the neutral accessible. In this case, the three instantaneous line-neutral voltages (phase voltages) indicate motor faults. When the motor is ideal, the sum of these voltages is zero. The presence of in-turn short circuit or broken a bar increases the phase voltages indicating the faults. This method has shortcomings such as need to access the neutral. In addition, in an actual healthy machine the fault indicator is not zero due to machine inherent imbalance and instrumentation asymmetry. Despite the load and voltage imbalance not presented, this approach depends on symmetrical machine impedance. Therefore, method's sensitivity is decreased with non- symmetrical of inductive impedances (Albizu & A. Mazon , 2006) .
Other Condition Monitoring Techniques
There are other condition monitoring techniques such as thermal, torque, noise, vibration and electrical diagnoses in the case of stator windings that are used to detect motor fault , which are specific to particular motor fault diagnosis. Praiseworthyprize.com [2010] proposed two techniques to diagnose induction motors i.e. Power Spectrum Density estimation (PSD) and Support Vector Machines (SVMs) to diagnose and detect any broken-rotor-bar faults loaded with different loads. The fault controller operates between the measured stator current of a healthy motor and the estimated current of a faulty motor condition. Welch and multiple signal classification spectral decomposition methods are applied to the stator current for analysis. From these methods, it is noted that frequency resolution along with detection reliability differs from each other depending on the parameters involved. Multiclass approach of SVMs-based classification is used to diagnose any faults. Choice of kernel function determines the
classification process performance showing the excellence of applying it in detecting faults in stator current signals.
Current Park’s vector uses a two dimensional representation hence suitable for describing three phase induction motor phenomena. The current park’s vectors components (id & iq) are a function of the main phase currents ia, ib, ic as indicated in the following equations.
illustration not visible in this excerpt
/ - maximum value of the supply phase current, m - supply frequency, t - time variable.
In order to determine the motor faults the current park’s component from the three phase variables are compared to those from the ideal conditions.
Literature Review Summary
There are many proposed motor diagnostic methods, which differ in the diagnosis efficiency and effectiveness. Fast Fourier Transform technique (FFT) for the analyses of motor faults is a technique that allow to detect faults using motor phase currentr, axial flux leakage, electromagnetic torque, and mechanical vibrations of the motor. It is a common method established due to the need to generate signals related to the physical phenomenon of the induction motor as opposed to the asymmetry approach that is based on the internal operations of an induction motor.
3. COMMON MOTOR FAULTS
Industrial motor faults can be internal or those that are associated with the physical phenomenon of the motor. The internal faults are categorized into mechanical and electrical faults. Electrical faults are due to short turns in the stator, which arise from heavy connecting rings connected to the rotor bars and consequently, large centrifugal forces may cause stress on the bars.
Rotor Faults
There several factors that result to broken rotor bars or the connecting ring are such as direct-line starting duty cycles not designed for the motor, pulsating mechanical loads, and poorly manufactured rotor cage as well as thermal stresses imposed upon it during starting of the machine. The photo below shows a broken rotor bar.
illustration not visible in this excerpt
Figure 4. (Gerg.S, Edward.A & Hussein.D , P.2004 broken rotor bars in induction motors)
Short Turn Faults
Insulation failures cause large percentages of motor failure in the stator turns. This causes a large circulating current in a symmetrical three-phase induction motor, generating of heat in the short-circuited turns. The insulation degradation may be because of mechanical problems. There are four types of stator short circuit faults, turn-turn within a coil, and short circuits between coils of the same phase, phase-to-phase and phase to earth short circuits as shown in fig below
illustration not visible in this excerpt
Figure 5. (Mehala P. 2010, various type of short windings faults)
Effect of current component on the motor faults caused by varying inductance
The construction of a motor consists of two magnetically connected systems, which are the stator and the rotor. This is similar to a transformer system, which contains the primary and secondary windings, but the secondary is usually short-circuited. Consequently, an equivalent circuit of the induction motor can be draw as shown below by (a) and (b)
illustration not visible in this excerpt
Figure 6. Equivalent circuit of the Induction motor.
Where; R1: stator resistance, XI: stator leakage reactance, Rc : core loss resistance,, Xm : magnetizing reactance, R2 : rotor resistance referred to stator, X2 : rotor leakage reactance known as to stator, and Xeq : equivalent leakage reactance {XI + X2).
The rotor circuit is represented as shown by fig. 6
illustration not visible in this excerpt
Figure 7. Rotor circuit current.
Where:
Er - Rotor voltage, R2- Rotor resistance, Jx2 - Rotor inductance.
The motor has a fixed value of resistance. Consequently, the rotor current depends majorly on the inductance of the motor. An increase of inductance will increase the rotor current whereas a decrease in inductance decreases the rotor current.
Test Circuit for Faults Simmulation
illustration not visible in this excerpt
Figure 8. test circuit for faults simulation.
This diagram shows a voltage regulator fed from a 3-phase voltage supply. The output is the regulated voltage, which becomes the input voltage to the induction motor. The frequency
converter gives a stabilized supply frequency (/l) to the induction motor. Data to diagnose the motor is collected by the LabVIEW program.
4. Motor Fault Diagnosis Using Signal Signature Analysis
Various diagnostic methods applied in SSA include current, electromagnetic torque, axial leakage flux and vibration signature analysis. This paper proposes to use current signature analysis using the Fast Fourier transform (FFT) technique for fault diagnosis.
Motor Current Signature Analysis Using FFT
Fast Fourier transform is applied to transform the signal from the time domain to frequency domain making it possible to analyze signal frequency components. Three line currents that are preferred to detect and diagnose motor faults. This is because current monitoring is a non- invasive method owing to the fact that it mostly uses the stator current analyses. Consequently, various experiments and studies have been undertaken to study current signature changes with rotor and stator windings faults. These experiments and studies show that some frequency components change their amplitudes or some few frequencies appear. However, the theoretical frequency values, which are function of fault, differ from one study or experiment to the other. Furthermore, among the frequencies predicted to change, some show a higher sensitivity to the fault than others do. Through experiments, the exact values for changes in current signature are obtained by use of signal signature analysis technique.
[...]
- Arbeit zitieren
- Hussain Mahdi (Autor:in), 2013, Fault diagnosis of induction motor fed by frequency converter. The signal signature analysis technique, München, GRIN Verlag, https://www.grin.com/document/337221
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