Motor Current Signature Analysis

Many condition monitoring methods including vibration monitoring, thermal monitoring, chemical monitoring require expensive sensors or specialised tools whereas current monitoring out of all does not require additional sensors - Ankush N Bahale

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Motor Current Signature Analysis

Induction motors are widely used in industrial drives because they are rugged, reliable and economical. They became an industry workhorse and play a pivotal role in industry for conversion of electrical energy into mechanical energy. Online fault diagnostics of these machines are very important to ensure safe operation, timely maintenance, increased operation reliability. There are many published techniques and commercially available tools to monitor induction motors to ensure a high degree of reliability. In spite of these tools, many companies are still faced with unexpected system failures and reduced motor lifetime. There are many condition monitoring methods including vibration monitoring, thermal monitoring, chemical monitoring, but all these monitoring methods require expensive sensors or specialised tools whereas current monitoring out of all does not require additional sensors.

Basics of Motor Current Signature Analysis

Motor Current Signature Analysis (MCSA) is a technique used to determine the operating condition of induction motors without interrupting production. Motor current signature analysis is that it is sensing an electrical signal that contains current components. MCSA detect the faults at an early stage and avoid the damage and complete failure of the motor. Proper analysis of MCSA results assists in identifying:

  1. Rotor bar damage
  2. Misalignment/ unbalance
  3. Foundation looseness
  4. Static eccentricity
  5. Dynamic eccentricity
  6. Stator mechanical /electrical faults
  7. Defective bearings
  8. Coupling health, including direct, belted and geared systems
  9. Load issues
    Figure (a) & (b) Basic System for MCSA

    Figure (c) Idealised current spectrum

The current signal is acquired from one phase of the motor supply (at motor terminal box, or at local electric panel) without interruption of the machine operation. In MCSA, the current signal is processed to obtain the frequency spectrum usually referred to as current signature. The MCSA uses this current spectrum of the machine for locating fault frequencies. When fault present, the frequency spectrum of the current becomes different from healthy motor.

The signal processing techniques are used for condition monitoring and fault detection of induction motor. The signal processing techniques have advantages that these are not computationally expensive, and these are simple to implement. By using MCSA , accurate analysis of fault is possible. An idealised current spectrum is shown in Fig (C).

Figure 1: Current spectrum for bearing at faulty and healthy conditions
Figure 2: Schematic representation of Static, Dynamic and Mixed eccentricity

Usually a decibel (dB) versus frequency spectrum is used in order to give a wide dynamic range and to detect the exclusive current signature patterns that are characteristic of different faults. The most common faults are bearing faults, stator faults, rotor faults and eccentricity or any combination of these faults. When analysed statistically, about 40 per cent of the faults correspond to bearing faults, 30-40 per cent to stator faults, 10 per cent to rotors faults, while remaining 10 per cent belong to a variety of other faults. Frequencies induced by each fault depend on the particular characteristic data of the motor (like synchronous speed, slip frequency and pole-pass frequency) as well as operating conditions.

Types of Faults Detected using MCSA

Bearing Faults

Rolling element bearings generally consist of two rings, an inner and an outer, between which a set of balls or rollers rotate in raceways. Under normal operating conditions of balanced load and good alignment, fatigue failure begins with small fissure, located between the surface of the raceway and the rolling elements, which gradually propagate to the surface generating detectable vibrations and increasing noise levels. Motor bearings faults are more difficult to detect than rotor cage problems. Misalignments are common result of defective bearing installation. MCSA can detect bearing faults by detection of frequency components f 0 and f 1 that are for most bearings with between six and twelve balls , determined by following equations (a) and (b) respectively.
f0 = 0.4 frm (a)
f1 = 0.6 frm (b) where ,
f0 is lower frequency,
f1 is upper frequency,
n is the number of balls in the bearings frm is the rotor’s mechanical frequency.

Figure 3: Air Gap-Static eccentricity

Air-Gap EccentricityAir-gap eccentricity leads to an air-gap length that is no longer constant with respect to the stator circumference angle and/or time. Air-gap eccentricity represents a condition when air gap distance between the rotor and the stator is not uniform. In general, three types of air-gap eccentricity can be distinguished as shown in fig:2
(a) Static eccentricity: The rotor geometrical and rotational centers are identical, but different from the stator center. The point of minimal air-gap length is stationary with respect to the stator. In case of static eccentricity, the position of minimal radial air gap is fixed.
(b) Dynamic eccentricity: The rotor geometrical center differs from the rotational center. The rotational center is identical with the stator geometrical center. The point of minimal air-gap length is moving with respect to the stator. in case of dynamic eccentricity position of minimal air gap follows turning of the rotor.
(c) Mixed eccentricity: The two effects are combined. The rotor geometrical and rotational center as well as the stator geometrical center is different.
Air gap eccentricity may result from the assembly and manufacturing processes. For example, static eccentricity is caused by manufacturing tolerances between the center of the stator bore and bearing centers.

fec is eccenticity frequency
fg is electrical supply (grid) frequency
R is the number of rotor bars
s = slip
p = pole-pairs nd = ±1
nws = 1, 3, 5, 7 …

The slip is determined from where, 
s is per unit slip
Nr is rotor speed
Ns is synchronous speed
Central frequency fc on Figures 3 and 4 is determined by
where R is the number of rotor bars.

When dynamic eccentricity is present, frequency components from static eccentricity are further modulated with the rotational frequency fr, as shown in Figure 4.

Figure 4: Air Gap-Dynamic eccentricity

Broken Rotor Bars

Broken rotor bars can be a serious problem with certain induction motors due to arduous duty cycles. Although broken rotor bars do not initially cause an induction motor to fail, there can be serious secondary effects. The fault mechanism can result in broken parts of the bar hitting the end winding or stator core of a high voltage motor at a high velocity. This can cause serious mechanical damage to the insulation and a consequential winding failure may follow, resulting in a costly repair and lost production. Broken rotor bars or end rings can be caused by the following:
• Direct-on-line starting duty cycles for which the rotor cage winding was not designed to withstand causes high thermal and mechanical stresses.
• Pulsating mechanical loads such as reciprocating compressors or coal crushers (etc.) can subject the rotor cage to high mechanical stresses.
• Imperfections in the manufacturing process of the rotor cage.

Figure 5: Motor Current Spectrum (a) Healthy Motor & (b) Motor with Air-gap Eccentricity

Figure 6: Motor with broken rotor barsDetection of Broken Rotor Bars

The location of the frequency components of the current due to broken rotor bars in the frequency spectrum is given by the formula:
fb = f1(1±2s) Hz
fb = frequency components of the current due to broken rotor bars, also known as sidebands
f1 = power supply frequency (Hz)
s = operating slip (per unit)
Figure 7 illustrates the current spectrum for broken rotor bar.

Figure 7: Current Signatures for broken rotor bars

Shorted Stator winding turns

Stator inter-turn fault is one of the most common faults occurring in the induction motor, not predicting it before it becomes severe, may lead to breakdown and loss of production. The stator current can be continuously monitored in order to predict any fault brewing in the stator windings

Figure 8: Healthy & faulty current spectrum for turn to turn short for single phase

The example in fig 8 shows a comparison between the spectrum of frequencies in a motor in normal conditions, and the spectrum of the same motor with one of its coils in short circuit. (The current in the loop in short circuit was limited to the same value as the nominal motor current). The main advantage of MCSA is to detect faults at an early stage. Most of stator faults start with inter-turn short circuits and then develop into open or short circuits depending on motor operation. Under inter-turn short circuit, the stator winding is unbalanced and draws unbalanced three phase currents. For stator faults, it is enough to detect peaks at higher than the twice of the supply frequency. Fig 9 shows the presence of harmonics in the motor current in case of short – circuited stator windings. For no load, the harmonics due to the faults occur at 25 Hz and 75 Hz.

Figure 9


Motor Current Signature Analysis is an electric machinery monitoring technology. It provides a highly sensitive, selective, and cost-effective means for online monitoring of a wide variety of heavy industrial machinery. It has been used as a test method to improve the motor bearing wear assessment for inaccessible motors during plant operation. This technique can be fairly simple, or complicated, depending on the system available for data collection and evaluation. MCSA technology can be used in conjunction with other technologies like Fast Fourier Transform (FFT), Fuzzy Logic, Park’s Vector, Wavelet Analysis etc in order to provide a complete overview of the motor circuit. The result of using MCSA as part of motor diagnostics program is a complete view of motor system health. Developing motor faults have its counterparts in waveform and harmonic content of the motor supply current. MCSA can be applied everywhere in industry where induction motors are used enabling non-intrusive on-line (even remote) analysis of motor supply current and detects faults while motor is still operational and without interrupting its service. It can be efficiently applied to detection and the localisation for variety of motor faults. As such, it is important contribution to tools for condition monitoring of induction motors.

Ankush N Bahale
Deputy Executive Engineer in
Maharashtra State Power Generation
Company Ltd (MAHAGENCO)


  1. Sir, how to determine side band frequency… Please brief in detail. And can a healthy motor can occurs a side band… Basically I want rotor bar damage… In detail…

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