Experimental Study of Neutral Configuration Effects on Internal and External Fault Detection in Induction Motors

In electrical systems, the configuration of the neutral system plays a vital role in ensuring protection, safety, and operational performance. The neutral system determines how the neutral point is connected to the earth and directly influences the connection and operation of electrical machines, including IM. Two key scenarios arise for asynchronous motors, one where the neutral is connected to the star point of the windings, and another where the neutral is not connected, either linked to the motor frame (yoke) or excluded entirely. Table 1 summarizes their impact on the IM.

Table 1. Comparison of the two configurations

2.1 Neutral connected to the star point of the windings

In this configuration, the motor’s stator windings are arranged in a star (Y) formation, with the star point connected to the system's neutral. This setup helps balance phase voltages during system asymmetries, thereby reducing unbalance. Additionally, it simplifies motor starting by lowering the voltage across each winding (1/√3of the line voltage), which reduces the starting inrush current caused by resistive torque. This configuration is particularly well-suited to TT and TN-S networks, where a neutral conductor is readily available. It is widely used in small to medium-sized installations, including residential, commercial, and industrial applications, where the neutral connection is easily accessible.

2.2 Neutral not connected to the star point (linked to the motor frame)

In this configuration, the star point of the motor windings remains isolated from the network’s neutral, or the stator phases are connected in a delta (Δ) arrangement. Instead, the motor frame (yoke) is connected to the protective earth (PE). This design allows the motor to operate without a direct connection to the network neutral, offering several advantages. It enhances insulation by preventing direct fault currents through the neutral, which increases system robustness. This setup is particularly compatible with isolated or impedance-earthed neutral systems (IT networks), as it minimizes the impact of ground faults. Furthermore, it is highly suited for industrial environments and applications involving power electronics, such as variable frequency drives (VFDs), soft starters, or frequency converters, where a neutral connection is typically unnecessary.

The choice of IM configuration depends on the neutral regime of the electrical network and the specific requirements of the application (Table 1). Connecting the neutral to the star point is ideal for balanced systems with accessible neutral conductors, while isolating the neutral is more suitable for industrial setups prioritizing insulation and robustness. A thorough understanding of these configurations ensures optimal performance, reliability, and adaptability in IM operation.

The neutral point configuration plays a critical role in determining the electromagnetic field distribution and current harmonics in the motor. In a three-phase system, the neutral point can be isolated, grounded, or connected in various ways, each influencing the motor's performance differently. For instance, a grounded neutral point configuration tends to reduce zero-sequence harmonics, as it provides a path for these currents to flow. However, this configuration may also lead to increased electromagnetic interference due to the grounding path. Conversely, an isolated neutral point configuration minimizes electromagnetic interference but can result in higher harmonic distortion due to the absence of a zero-sequence current path.

The influence of neutral point configuration on flux distribution and machine behavior has been extensively investigated in recent studies to provide a well-rounded assessment. For instance, they demonstrated that floating neutral point systems in induction machines exhibit heightened thermal stresses under unbalanced voltage conditions, emphasizing the sensitivity of flux distribution to voltage imbalances [17]. Similarly, other works analyzed the impact of neutral point current control, showing that floating neutral configurations can limit copper losses and fault currents, though they introduce complexity in monitoring [19]. On the other hand, Previous work highlighted the advantages of bonded neutral points in stabilizing the neutral voltage, which aids in maintaining balanced flux distribution and facilitates fault detection [20]. Complementary findings stressed that small-resistance grounding at the neutral point reduces voltage fluctuations, improving system stability [16]. Others further supported the role of optimized neutral grounding in mitigating geomagnetically induced current effects, reinforcing the safety and voltage control benefits of bonded neutral configurations [16]. This comparative analysis underscores the trade-offs: while floating neutral systems offer benefits in reducing fault current magnitudes and losses, bonded neutral configurations remain preferred for voltage stability and simplified fault management in practical applications.

The objective of this study is to investigate the impact of different neutral configurations (bonded vs. un-bonded neutral) on the detection and monitoring of internal and external unbalances in IM. Through a series of supervised experiments, we will compare the motor’s performance under both configurations, focusing on the motor's ability to detect and respond to unbalances, its efficiency, stability, and longevity. The experimental methodology involves measuring key machine parameters at different points and identifying voltage and current unbalances across different neutral configurations.

Additional performance-related variables are also monitored. The experimental setup, as illustrated in Figure 1, consists of a three-phase squirrel-cage induction motor (model: FIMIT, 1.1 kW, 400 V, 50 Hz, 2-pole) and a dSPACE 1104 real-time control board for data acquisition and control. Current measurements are performed using five current transducers (model: LA 25-P, accuracy: ±0.9%), and voltage measurements are taken using four voltage transducers (model: LV 25-P, accuracy: ±0.9%). Motor speed is monitored using a Cheap GHS38 Motor Speed Sensor (360/500/1024 pulse incremental encoder, NPN open collector type).

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Figure 1. Experimental setup for unbalanced supply voltage study

The motor is powered by two alternating current sources: one supplying the motor and the other dedicated to the sensors to ensure stable and isolated measurements. External unbalances are simulated by adjusting the power supply voltage levels variable resistance control (Figure 2), while internal unbalances are introduced by creating one or more broken rotor bars to assess their impact on motor performance. The experiments are conducted under two scenarios: external unbalance (voltage unbalance in the power supply) and internal unbalance (broken bar fault). The specified accuracy and sensitivity of the measurement equipment ensure reliable detection of unbalance conditions, while any limitations of the sensors are considered when interpreting the experimental results.

The experimental results presented in this study are subject to various sources of error, which were carefully considered and mitigated. Key sources include measurement inaccuracies, environmental factors, systematic biases, random noise, and human errors. For instance, current and voltage measurements were performed using high-precision sensors Lp 25-p and Lv 25-p respectively, with an accuracy level of 0.9%, as specified by the manufacturer. Environmental influences, such as temperature fluctuations, were minimized by conducting experiments in a controlled laboratory setting. Systematic errors, like sensor misalignment, were addressed through careful calibration, while random noise was reduced by averaging multiple measurements. Human errors were mitigated by automating data acquisition and validating results against theoretical predictions. These measures ensure the reliability and accuracy of the experimental findings, though some residual errors may remain.

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Figure 2. Simulated unbalanced supply using variable resistance control

4.1 Experimental methodology for studying voltage unbalance

Voltage unbalance in a three-phase system occurs when the voltages of the three phases differ in magnitude or phase, leading to non-ideal operating conditions for connected equipment, including IM [21]. Causes of voltage unbalance include uneven load distribution, phase failures, transformer faults, the use of non-linear equipment like frequency converters, and variations in cable lengths or sizes. This unbalance negatively impacts motor performance by increasing phase currents, reducing torque, causing vibrations and noise, lowering efficiency, and potentially damaging motor components [22]. These effects can result in overheating, reduced motor lifespan, and higher maintenance costs. The voltage unbalance factor, which measures the difference between the phases, is expressed as a percentage and helps quantify the extent of the unbalance. According to IEC 60034-1 [2], a voltage unbalance factor of less than 1% indicates relatively balanced voltages. A high unbalance factor, however, can cause efficiency losses, increased energy consumption, premature equipment wear, and a shorter motor lifespan. Therefore, maintaining voltage unbalance limits is critical for ensuring the optimal performance of electrical installations and avoiding additional maintenance and energy costs. The equation for the Voltage Unbalance according to the IEC 60034-1 standard can be expressed as follows:

$\begin{aligned} & { Voltage~Unbalance }(\%)= \frac{\max \left(V_1, V_2, V_3\right)-\min \left(V_1, V_2, V_3\right)}{1 / 3\left(V_1+V_2+V_3\right)} \times 100\end{aligned}$       (9)

(1) $V_1, V_2, V_3$: Are the line-to-line (or line-to-neutral) voltages of the three phases.

(2) $max \left(V_1, V_2, V_3\right)$: Is the highest voltage among the three phases.

(3) $min \left(V_1, V_2, V_3\right)$: Is the lowest voltage among the three phases.

(4) $\frac{1}{3}\left(V_1+V_2+V_3\right)$: Is the average voltage of the three phases.

The Eq. (9) calculates the voltage unbalance percentage, which measures the degree of imperfection in a three-phase system. A voltage unbalance exceeding 2-3% is typically considered problematic for the proper functioning of IM and other sensitive equipment. The study is conducted in two parts: first, evaluating the behavior of the machine without faults, and second, assessing its performance with varying degrees of voltage unbalance under different neutral configurations. Using the MCSA method as previous studies [3, 4], the fault-specific frequencies will be identified. The experimental methodology for studying voltage unbalance is carried out by introducing a variable resistance upstream of the motor. Motor performance is then evaluated under these unbalanced conditions. These experiments aim to identify the impact of voltage unbalance on the motor's operational characteristics.

4.1.1 Bound neutral point condition for unbalance supply fault

Figure 3 illustrates two distinct operating conditions of the currents in an induction machine (IM). The first scenario depicts the machine's currents under healthy conditions, where all three phase currents are nearly equal in magnitude, indicating stable operation. A slight deviation is observed due to a minor disturbance in the mains supply, but this does not significantly impact the machine's overall performance. The second scenario represents the currents when one phase (specifically, the second phase) experiences a supply unbalance. In this case, the unbalance predominantly affects the current in the disturbed phase, while the currents in the remaining two phases remain relatively unaffected. This behavior is attributed to the use of an earthed neutral configuration, which helps contain the unbalance within the affected phase, preventing its propagation to the others.

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(a) Balanced supply

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(b) Unbalanced supply

Figure 3. Stator currents under both balanced and unbalanced supply voltage conditions

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(a) Balanced supply

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(b) 15% of unbalanced supply

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(c) 20% of unbalanced supply

Figure 4. Stator current spectrum under healthy and unbalanced voltage conditions (15% and 20%)

Figure 4 illustrates the spectral analysis of stator currents in an induction machine under various operating conditions. Under healthy operating conditions (blue curve), the stator current spectrum is dominated by the fundamental supply frequency (fs), consistent with normal machine operation. The harmonic content is minimal, indicating a balanced power supply and optimal machine performance. In contrast, under unbalanced supply conditions (red and green curves), where the unbalance is deliberately introduced to the second phase, the spectra reveal significant deviations from the healthy state. Distinct frequencies associated with the supply unbalance clearly emerge and become more pronounced as the severity of the disturbance increases. These unbalance-related frequencies are typically characterized by the following relationship:

${{f}_{unbalance}}={{f}_{s}}+2*k*{{f}_{s}}$    (10)

where, “f_s” is the main supply frequency and “k” is a positive integer.

The magnitude of these characteristic frequencies exhibits a direct correlation with the severity of the unbalance, showing a clear variation as the fault level increases. The presence and amplification of these frequencies provide clear diagnostic indicators of supply disturbances and their impact on machine performance. The identification of these frequencies plays a pivotal role in diagnosing anomalies within electrical systems. Detecting these frequencies facilitates the implementation of corrective measures to restore system balance and mitigate potential long-term damage to the machine. Moreover, the emergence and amplification of such frequencies may signal more profound underlying issues, including potential faults in the stator windings. Consequently, continuous monitoring of these spectral signatures is indispensable for ensuring the operational integrity and reliability of induction machines. This relationship enhances diagnostic precision and supports timely intervention, thereby safeguarding machine performance and longevity.

Figure 5 illustrates the behavior of the line-to-neutral current under both balanced and unbalanced supply conditions, with varying degrees of unbalance. In a balanced system, the neutral current remains minimal and stable, reflecting the symmetry of the phase currents, which effectively cancel each other out, resulting in near-zero neutral current. However, under unbalanced conditions, the neutral current exhibits a significant increase in magnitude, directly correlated with the severity of the unbalance. The waveform also displays pronounced oscillations and distortions as the unbalance intensifies, a consequence of the asymmetric distribution of currents across the phases. The neutral current compensates for the excess or deficit in the affected phase, while the currents in the unaffected phases remain largely unchanged. In a balanced configuration, the neutral current is negligible due to the cancellation of balanced phase currents. However, when an unbalance occurs, the affected phase draws either more or less current than usual, and this discrepancy is reflected in the neutral current. The unaffected phases continue to operate normally, while the neutral current rises to offset the unbalance in the affected phase. This behavior highlights the importance of monitoring neutral current as a diagnostic tool for identifying supply unbalances, enabling timely corrective actions to maintain system stability and prevent potential damage to electrical infrastructure.

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(a) Balanced supply

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(b) 15% of unbalanced supply

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(c) 20% of unbalanced supply

Figure 5. Neutral line current under healthy and unbalanced supply conditions (15% and 20%)

Figure 6 depicts the behavior of harmonic components (3f_s, 5f_s, 7f_s, 9f_s) as a function of unbalanced voltage severity and load torque variations. The blue curve represents the healthy operating condition, while the red, green, and magenta curves correspond to the first (F1), second (F2), and third (F3) degrees of unbalance voltage, respectively. The results indicate that the amplitudes of these harmonics fluctuate in response to changes in both load torque and fault severity. However, these fluctuations do not follow a clear or consistent pattern, making it difficult to establish a definitive correlation between harmonic behavior and the progression of fault or load variations. This lack of a systematic trend complicates the interpretation of harmonic data as a reliable indicator of supply voltage unbalance.

Upon closer examination of Figure 6, certain trends can still be identified despite the complexity. Specifically, the 3rd harmonic (3f_s) exhibits a clear decrease in amplitude as the unbalance severity rises, particularly under lower load conditions. This behavior can be attributed to the introduction of zero-sequence components caused by supply voltage asymmetry, which becomes more pronounced in the presence of a neutral connection. As the load increases, the harmonic amplitude decreases overall, but differences between healthy and unbalanced scenarios remain noticeable.

Similarly, the 5th harmonic (5f_s) shows a peak in amplitude at medium load levels (approximately 25% to 50%), with higher fault severity leading to a distinct increase. The presence of negative-sequence components under unbalanced conditions contributes to this increase, affecting the motor’s current waveform.

In contrast, the 7th harmonic (7fs) demonstrates a decreasing trend with increasing load, and the differences between healthy and faulty cases are less pronounced. This suggests that higher-order harmonics may be less sensitive to unbalance effects, likely influenced by nonlinear load interactions.

Lastly, the 9th harmonic (9fs) exhibits minimal variation and irregular behavior across different unbalance conditions and load levels, indicating limited diagnostic usefulness.

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(a) Harmonic 3*fs

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(b) Harmonic 5*fs

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(c) Harmonic 7*fs

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(d) Harmonic 9*fs

Figure 6. Harmonic amplitudes for varying percentages of unbalanced supply (15%, 20% and 30%)

4.1.2 Floating neutral point in case of unbalanced supply fault

Figure 7 demonstrates two distinct operational scenarios of the machine. The first scenario represents the machine under healthy operating conditions, where the three-phase currents demonstrate nearly identical magnitudes, consistent with balanced and normal operation.

The second scenario depicts the machine operating under a supply unbalance, specifically affecting one of the phases. In this case, the unbalance predominantly impacts the current of the affected phase, but it also induces secondary effects on the remaining phases.

This phenomenon is a direct consequence of the machine's isolated (unbonded) neutral connection configuration, which enforces the constraint that the sum of the three-phase currents must equal zero. Consequently, in an isolated neutral system, any unbalance in one phase is inherently compensated for by adjustments in the other phases to preserve the overall equilibrium of the system.

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(a) Balanced supply

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(b) Unbalanced supply

Figure 7. Stator currents under both balanced and unbalanced supply voltage conditions

This redistribution of current underscores the interconnected nature of phase currents in such systems and emphasizes the importance of considering neutral configuration when analyzing and diagnosing supply unbalances.

Figure 8 illustrates a spectral analysis of stator currents under various operating conditions in an unbounded neutral connection system. Under healthy operating conditions (blue), the stator current spectrum is predominantly characterized by the fundamental supply frequency (f_s), indicative of normal system behavior. However, under unbalanced supply conditions (red and green), distinct frequencies associated with the unbalance become evident, with their prominence increasing in proportion to the degree of unbalance. These frequencies are typically represented as $f_{\text {unbalance }}=f_s+2 * k * f_s$ where “k” is an integer. The emergence of these frequencies is a clear indicator of supply network unbalance, often resulting from voltage asymmetries.

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(a) Balanced supply

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(b) 15% of unbalanced supply

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(c) 20% of unbalanced supply

Figure 8. Stator current spectrum under healthy and unbalanced voltage conditions (15% and 20%)

The appearance of these unbalance-related harmonic components is a direct reflection of the asymmetry introduced in the supply network, and their amplitudes escalate with the severity of the unbalance. This behavior offers a clear diagnostic signal for identifying supply disturbances. However, it is important to note that the floating neutral configuration affects the distribution and intensity of these harmonics. Specifically, without a grounded neutral path, the imbalance-induced currents lack a low-impedance return path, leading to altered electromagnetic field distributions within the motor and affecting the visibility of certain harmonic components.

Moreover, the variation patterns observed in the harmonic amplitudes reveal valuable information about the system’s sensitivity to fault types. In the floating neutral setup, the reduced damping effect may cause the harmonic components to fluctuate more sharply, especially under higher fault severity levels. This characteristic makes the spectral signatures more sensitive to minor unbalances but may also result in higher susceptibility to measurement noise.

The amplitude of these characteristic frequencies escalates with the severity of the unbalance, providing critical diagnostic information. This relationship not only enhances the precision of fault detection but also supports proactive measures to mitigate potential system disruptions. Continuous spectral analysis allows operators to assess not only the existence of voltage asymmetries but also their progression over time. Understanding how these harmonic patterns behave under different neutral point configurations, such as the floating neutral in this case, enables more accurate fault classification and supports the implementation of targeted corrective actions. Consequently, the relationship between harmonic behavior, fault severity, and neutral configuration enhances diagnostic precision and contributes significantly to the maintenance and reliability of electrical systems.

Figure 9 depicts the phase-to-neutral voltages under healthy and fault conditions (15%, 20% and 30%), highlighting the impact of increasing fault severity. Under normal operation, the voltage exhibits a stable sinusoidal waveform with consistent amplitude, reflecting balanced system conditions.

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(a) Balanced supply

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 (b) 15% of unbalanced supply

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(c) 20% of unbalanced supply

Figure 9. Neutral line voltage under healthy and unbalanced supply conditions (15% and 20%)

However, as faults intensify, the waveform undergoes progressive distortion, characterized by pronounced oscillations and greater amplitude fluctuations. These deviations correlate directly with the severity of the unbalance, providing a visual representation of fault progression. This behavior aligns with the spectral analysis presented in Figure 8, where fault-induced unbalances manifest as distinct frequency components. Together, these observations underscore the relationship between waveform distortion and spectral anomalies, offering complementary diagnostic insights. The ability to correlate time-domain voltage deviations with frequency-domain characteristics enhances the precision of fault detection and supports the development of targeted mitigation strategies, ensuring system reliability under varying operational conditions.

Figure 10 demonstrates the relationship between harmonic amplitudes, load conditions, and fault severity. A particularly notable trend is observed in the amplitude of the 3f_s harmonic, which systematically increases with variations in torque or fault degree.

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(a) Harmonic 3*fs

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(b) Harmonic 5*fs

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(c) Harmonic 7*fs

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(d) Harmonic 9*fs

Figure 10. Harmonic amplitudes for varying percentages of unbalanced supply (15%, 20% and 30%)

This behavior strongly suggests the presence of an unbalanced supply voltage, as the harmonic response amplifies in tandem with the severity of the unbalance. These findings complement the observations from Figures 8 and 9, where fault-induced unbalances were shown to distort phase-to-neutral voltages and introduce characteristic frequency components in the stator current spectrum. The consistent increase in harmonic amplitudes under fault conditions further reinforces the diagnostic value of monitoring such spectral features. Additionally, the use of an un-bonded neutral connection in industrial systems enhances the detecting capability of these unbalances, thereby improving the reliability of diagnostic approaches. However, this configuration (Table 2) necessitates meticulous design and maintenance to address potential operational challenges. Collectively, these results highlight the importance of integrating time-domain and frequency-domain analyses to achieve robust fault detection and ensure system stability.

Table 2. Comparison between bonded and floating neutral in the event of voltage unbalance

4.2 Experimental methodology for studying broken rotor bar fault

A Broken Rotor Bar Fault (BRBF) in an induction motor occurs when one or more rotor bars fail, leading to current unbalances and reduced motor performance [4, 23]. Common causes include mechanical fatigue, electrical overloads, design flaws, and electromagnetic disturbances. The experimental methodology employed to study BRBF involves a rigorous and systematic approach to assessing the fault's impact on motor performance.

Initially, the motor is operated under normal conditions to establish baseline performance metrics, including torque and speed. To simulate a BRBF, controlled damage is deliberately induced, typically by causing a mechanical break in one or more rotor bars (Figure 11). Furthermore, the experimental setup incorporates the Motor Current Signature Analysis (MCSA) diagnostic technique, which enables a detailed investigation into how broken rotor bars affect the operational characteristics and efficiency of the motor.

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Figure 11. Experimental setup for internal unbalance (broken rotor bar fault)

4.2.1 Bound neutral point condition for internal unbalance fault BRB

Figure 12 depicts three distinct operational states of the currents in an induction machine. Under normal operating conditions, the phase currents exhibit nearly identical amplitudes and waveforms, signifying healthy performance. However, when one or two rotor bars are damaged (represented by the second and third curves, respectively), the current magnitudes show slight deviations. These changes are primarily due to the increased slip associated with the rotor bar fault, which induces minor asymmetries in the current waveforms.

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(a) Healthy condition

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(b) 1 BRB fault

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(c) 2 BRB fault

Figure 12. Stator currents curves under healthy and internal unbalanced (BRB) conditions

Figure 13 presents the line-neutral current waveform both in the healthy state and under various broken rotor bar faults (BRBF). In the healthy condition, the current waveform is smooth and consistent, indicating balanced operation. In contrast, when the machine experiences broken rotor bars, the line-neutral current curve exhibits significant changes, such as an increase in amplitude and distortion of the waveform. These alterations are a result of the elevated slip and mechanical unbalances introduced by the rotor bar damage.

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(a) Healthy condition

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 (b) 1 BRB fault

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 (c) 2 BRB fault

Figure 13. Line neutral current curve in healthy and internal unbalanced (BRB) conditions

Figure 14 presents a spectral analysis of the stator currents in IM under healthy and BRBF conditions in both no-load and full-load scenarios. In the healthy state (blue), the stator current spectrum is dominated by a peak at the fundamental supply frequency (f_s), characteristic of normal operation without faults. The rotating frequency (f_r) is also visible, further confirming the machine's proper functioning.

The spectrum contents minimal harmonic, indicating balanced and efficient machine performance. In contrast, under BRBF (red and green) the stator current spectrum shows significant deviations from the healthy state. Characteristic fault frequencies, indicative of rotor asymmetry, become prominent, highlighting the unbalance caused by the rotor fault. These frequencies can be expressed by the formula:

${{f}_{BRB}}=\left( 1\pm 2g \right)*{{f}_{s}}$     (11)

where, “g” represents the slip of the machine.

Furthermore, as the load increases, the fault frequencies shift further away from the fundamental frequency, reflecting the increased slip (g) under load conditions. This shift is accompanied by a proportional rise in the amplitude of these characteristic frequencies, signifying the severity and progression of the rotor fault. The amplitude increase becomes more pronounced with higher fault levels, offering a clear and quantifiable diagnostic marker for identifying BRBF. Additionally, the effect of load on these frequencies is evident, as they move further from the fundamental under full load due to the increased slip, highlighting the importance of considering load conditions in fault diagnosis.

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(a) Healthy condition

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(b) 1 BRB fault

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 (c) 2 BRB fault

Figure 14. Stator current spectrum in healthy and internal unbalanced (BRB) conditions

It is also noteworthy that the presence of broken bars leads to asymmetric flux distribution within the rotor, which further contributes to the generation of sideband frequencies around the fundamental. These sidebands are reliable indicators of rotor faults, and their magnitude and frequency displacement serve as essential parameters in assessing fault severity. However, vibrations can distort the spectrum signals, introducing noise that complicates the accurate identification of fault-related frequencies. Therefore, careful signal filtering and advanced spectral analysis techniques are required to minimize external disturbances and ensure accurate detection of the rotor fault signatures.

4.2.2 Floating neutral point condition for internal unbalance fault BRB

Figure 15 presents the stator current waveforms for a system with a floating neutral connection. In the healthy state, the currents are balanced and symmetrical, exhibiting nearly identical amplitudes and waveforms. However, under broken rotor bar fault (BRBF) conditions, subtle deformations in the current waveforms are observed, indicating rotor damage.

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(a) Healthy condition

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(b) 1 BRB fault

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(c) 2 BRB fault

Figure 15. Stator currents curves under healthy and internal unbalanced (BRB) conditions

Figure 16 shows the line-neutral voltage waveforms under both healthy and BRBF conditions. Following the fault, the voltage waveform displays slight distortions, asymmetries, and variations in amplitude. These changes are attributed to the increased slip and mechanical unbalances caused by the rotor damage.

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(a) Healthy condition

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(b) 1BRB fault

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(c) 2 BRB fault

Figure 16. Line neutral voltage curve in healthy and internal unbalanced (BRB) conditions

These observations highlight the importance of monitoring both current and voltage to reliably detect rotor bar faults, especially since subtle anomalies in the waveforms can serve as early indicators of mechanical failures.

Figure 17 illustrates notable deviations, with characteristic fault frequencies linked to rotor asymmetry becoming more pronounced. These variations serve as indicators of rotor damage, underscoring the critical role of spectral analysis in fault detection. As the degree of unbalance increases, the amplitude of these characteristic frequencies also rises. The identified frequencies are:

${{f}_{BRB}}=\left( 1\pm 2g \right)*{{f}_{s}}$     (12)

A closer examination reveals that these fault-related sideband frequencies become increasingly prominent with the worsening of rotor faults, enabling early-stage detection and precise severity assessment. The amplitude growth of these sidebands is particularly useful for distinguishing between minor rotor defects and severe broken rotor bar conditions.

Based on the interpretation of Figure 17, it is also observed that in the presence of an un-bonded (floating) neutral, the vibration levels are generally lower compared to a bonded neutral system.

This reduction in vibration noise enhances the clarity of fault indicators in the stator current spectrum. As a result, the fault-related frequencies become more distinct and easier to detect, making the un-bonded neutral configuration particularly advantageous for identifying broken rotor bar faults.

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(a) Healthy condition

17b.png

(b) 1 BRB fault

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(c) 2 BRB fault

Figure 17. Line neutral voltage curve in healthy and internal unbalanced (BRB) conditions

Furthermore, the reduced interference in the floating neutral system minimizes the risk of external noise masking the fault signatures, allowing for a cleaner spectral analysis. This highlights the importance of considering the neutral configuration when designing fault detection schemes, as it directly impacts the accuracy and reliability of the diagnostic process. Continuous monitoring of these frequencies, combined with proper neutral configuration (Table 3), supports predictive maintenance strategies and enhances the longevity of IM.

Table 3. Comparison between bonded and floating neutral in the event of a bar break