Electrical Signature Analysis: what it is and how it works in predictive maintenance

Electrical signature analysis (ESA) is a predictive maintenance technique that evaluates the behavior of electrical assets based on signals such as current and voltage. Rather than relying only on visual inspections or physical interventions on the equipment, this approach identifies changes in the operation of motors, generators and transformers non-invasively, with the asset energized and, in many cases, in operation.

In this article, we cover what electrical signature analysis is, how it works in practice, which faults it can help identify and where its application makes the most sense in industry. We also look at how this approach integrates with other predictive techniques and how it supports safer, more precise and data-driven decisions in asset management.

What is Electrical Signature Analysis?

Electrical signature analysis (ESA) evaluates current and voltage to identify changes in the behavior of energized assets. In turn, these measurements convert electrical signals into indicators that support condition analysis of the equipment.

This approach can be applied to motors, generators and transformers, enabling diagnosis with the asset energized and, in many cases, in operation. In practice, to really understand what is electrical signature analysis: every electrical machine has its own operating signature. When that pattern changes, it can point to anomalies or developing faults.

Importantly, the technique also goes beyond isolated electrical readings. Since the asset’s behavior directly influences the measured signals, the analysis also captures effects tied to the electromechanical operation of the system.

Why does Electrical Signature Analysis matter in industry?

Electrical signature analysis matters because it tracks critical assets through current and voltage measurements without stopping the process. Since measurements can be taken with the asset energized, the technique reflects real operating conditions and extends monitoring capability in day-to-day industrial routines.

Key advantages of this technique include:

• No need to stop the process, supporting continuous monitoring
• Reflects the asset’s real operating condition
• Covers the motor, the power supply system and the production process
• Detects dynamic and intermittent faults
• Suits trend-based predictive maintenance
• Helps reduce unexpected downtime
• Increases operational predictability
• Adds safety to interventions
• Improves electrical asset management
• Requires no equipment disassembly, since monitoring is done on the power cables and can be performed at the electrical panels
• Shows that mechanical problems can also be detected through electrical analysis

Beyond these advantages, electrical and mechanical problems leave measurable marks on the equipment’s electrical signal. Abnormalities in the motor’s electrical or mechanical components, or in the process the motor drives, can alter current behavior and/or the electromagnetic field.

How does Electrical Signature Analysis work in practice?

Electrical signature analysis observes how the asset behaves over time and under different operating conditions. Electrical signals can be assessed both through the waveform and through parameter trends, considering variations, tendencies and changes relative to expected behavior. This allows the analysis to detect deviations in equipment condition.

Here’s how:

Current, voltage and frequency as a diagnostic source

Understanding the electrical signature starts with the system’s basic quantities: current, voltage and frequency.

• Current: the electrical flow that powers the equipment (Amperes, A)
• Voltage: the potential difference that drives this flow (Volts, V)
• Frequency: the number of cycles per second in the power grid (Hertz, Hz)

In addition, from these signals, other parameters that are fundamental to the analysis can be calculated, such as power, phase shift, mechanical imbalance, voltage and current unbalance, power factor, active and reactive energy, peak-to-peak values, RMS values and crest factor, among others.

The motor as an electromechanical system

A central point of this technique is understanding that the motor should not be evaluated as an isolated electrical component. It is an electromechanical system, in which the electrical and mechanical sides are directly connected. Changes in load, torque and mechanical behavior all influence the measured electrical signal.

This broadens the scope of the analysis, since the electrical signature is not limited to identifying strictly electrical faults. Air gap variations, misalignment, load changes and other mechanical problems can also modify the electromagnetic field and, as a result, alter current behavior. Likewise, turn, winding, connection, insulation and rotor bar faults also leave marks on the electrical signals.

Time-Domain and Frequency-Domain analysis

After collection, the electrical signal can be analyzed in the time domain or the frequency domain. In the time domain, the reading looks at the waveform and the evolution of electrical parameters, identifying trends, variations, oscillations and phase shifts in the asset’s behavior. In the frequency domain, the goal is to reveal patterns that are not clearly visible in the original waveform.

This is also where concepts like FFT, spectrum and characteristic frequencies come in. Shaft rotation generates a characteristic frequency, while defects produce repetitive patterns that can appear as peaks in the spectrum. Identifying these frequencies helps connect signal changes to possible anomalies in the asset.

In practice, the analysis turns electrical signals into diagnostic information. Instead of looking only at the instantaneous value of current or voltage, the technique interprets how the equipment’s electrical behavior evolves and links those changes to possible developing faults.

What failure modes can be identified with Electrical Signature Analysis?

In general, failure modes can be organized into three main groups to make analysis easier: 1. Stator and rotor failure modes; 2. Mechanical problems that affect the electrical signal; 3. Power supply and power quality disturbances.

Here’s what can be observed in each of them.

Stator and Rotor Failure Modes

This group covers internal anomalies in the electrical equipment that directly affect current and voltage behavior. Key examples include:

• Inter-turn short circuits
• Broken rotor bars
• Air gap eccentricity

These faults change the asset’s electrical signature and point to deviations from the machine’s expected behavior.

Mechanical problems that affect the electrical signal

Electrical signature analysis also detects mechanical changes that affect the equipment’s electromechanical behavior. The most relevant examples include:

• Misalignment
• Imbalance
• Bearing-related mechanical problems
• Load variations

In these cases, the defect is not necessarily on the electrical side. Even so, it changes how the asset operates and leaves measurable marks on the electrical signal.

Power supply and power quality disturbances

Beyond internal faults and mechanical effects, the technique also helps identify anomalies related to the system’s power supply. For example:

• Phase loss
• Voltage unbalance
• Current unbalance
• Power quality disturbances
• Stator circuit aging

This type of analysis helps determine whether the observed change is related to the asset itself or to the electrical conditions of the power supply.

This breakdown matters because it broadens the reading of equipment condition. It shows that electrical signature analysis is not limited to strictly electrical faults, and also helps detect mechanical changes and power supply disturbances that impact asset performance.

Where is the measurement taken and how is the technique applied?

So, electrical signature analysis does not require direct access to the machine body to generate diagnostic information. In practice, this answers a common question: data can be collected without disassembling the equipment and, in many cases, with the asset in operation.

Here’s how the measurement is carried out:

Measurement at the electrical panel

Measurement is generally taken at the electrical panel, where the signals needed for analysis are available. This means the sensor does not need to be installed on the machine itself, which reduces physical interventions on the asset and avoids unnecessary exposure of the team to operational risks.

This is an important feature of ESA, as it makes the methodology non-invasive. Since data collection happens on the power supply system, there is no need to disassemble the equipment to obtain the data. The asset can also remain energized during measurement and keep operating normally.

Sensors on the supply phases

Data collection uses sensors installed on the asset’s supply phases. These measurements record the electrical signals and convert them into analysis parameters.

This setup captures the electrical signature without directly interfering with the machine’s mechanical parts. The technique observes asset behavior through the electrical system, which reinforces its practical application in industrial environments where access, safety and operational continuity are critical factors.

Periodic or continuous monitoring

This is why the technique can be applied periodically or continuously, depending on asset criticality and the goal of the analysis.

With periodic collection, measurements are taken at set intervals, which suits assets where trend monitoring can happen through campaigns or inspection routines.

Continuous monitoring, on the other hand, is better suited to critical assets, where tracking signal evolution over time increases the ability to spot deviations and improves maintenance predictability.

Choosing between periodic collection and continuous monitoring should take into account the impact a failure could have on operations, availability and plant safety.

What is the difference between ESA and other related analyses?

When talking about electrical signature analysis (ESA), it’s important to understand that the term works as an umbrella for different analysis approaches based on electrical signals.

The image below helps visualize how some techniques overlap, others have a narrower focus, but all belong to the same universe of monitoring through current, voltage and power.

Here are the main acronyms:

In short, the circle diagram shows exactly this relationship between the techniques. CSA occupies an important space within ESA because current carries information about motor and load behavior. VSA looks at voltage and helps analyze aspects tied to the power supply. Between these two, PSA appears as an overlap zone, since power results from combining electrical quantities (current and voltage) and broadens the system reading.

Within this set, MCSA is a more specific approach focused on motor current signature. It sits within the broader universe of current analysis. EPVA, in turn, is not a separately measured quantity but a way of processing electrical signals to extract patterns related to asset behavior.

This means these acronyms should not be seen as competing techniques. They are complementary ways of interpreting the same electrical signals. While one approach highlights current, another emphasizes voltage, power or the system’s vector behavior. Together, they expand diagnostic capability and help build a more complete picture of asset condition.

Limits and precautions of Electrical Signature Analysis

Electrical signature analysis is a valuable technique for diagnosing electrical assets, but it should not be treated as a standalone solution. For consistent interpretation, a few precautions should be kept in mind:

• Not every fault produces an easily identifiable signal, especially in very early stages
• Load conditions directly influence the analysis, requiring operational context to interpret the data correctly
• The process and the power supply also interfere with signal behavior, and can alter the reading
• Data quality directly impacts the diagnosis, since inconsistent measurements reduce analysis reliability
• ESA interpretation can become more complex, especially when several system variables influence the signal at the same time
• The technique should not be used in isolation, but as part of a condition-based maintenance strategy
• ESA complements other predictive techniques, such as vibration analysis, thermography and field inspections
• Signal readings should consider the asset’s actual behavior, not just isolated electrical values

Taken together, these precautions show that electrical signature analysis delivers more value when integrated with other information sources and a structured monitoring routine.

Practical applications of Electrical Signature Analysis in industry

How electrical signature analysis is applied can vary depending on the type of asset and the fault in development. In motors, transformers and motor pumps, for example, the technique helps detect electrical deviations linked to problems that are not always visible early on.

Here’s a practical example to illustrate the application:

Practical Example

Scenario In a distribution substation, a transformer starts showing signs of degradation in its on-load tap changer (OLTC), with no immediate visible impact on operation.

Detection Following this, the analysis identifies abnormal behavior associated with the changer’s operation between consecutive taps, indicating contact degradation and a deviation from normal condition.

Verification The anomaly flagged by the analysis is confirmed through visual inspection, validating the problem in the component.

Action With the deviation identified before a critical failure, the team replaces the OLTC oil, returns the changer to service and schedules replacement for a more convenient window.

Result As a result, electrical signature analysis helps anticipate degradation, adds predictability to maintenance and avoids an emergency intervention on a critical asset in this type of application.

How does Dynamox support the Application of Electrical Signature Analysis?

Dynamox ESA supports the application of electrical signature analysis by bringing sensing, data acquisition, algorithmic processing and remote monitoring together in a single solution. This turns the analysis from a simple reading of electrical signals into part of a structured routine for tracking asset condition.

In practice, the solution directs the analysis toward three main areas:

• Fault diagnosis: identifying anomalies in the stator, rotor, mechanical parts and load variations, based on electrical signal behavior
• Power quality: assessing power supply conditions, such as voltage unbalances and disturbances that can affect asset performance
• Energy efficiency: analyzing equipment consumption and performance to help identify losses and operational deviations

The platform also organizes the electrical signature reading into 5 fault indicators:

• Motor supply: voltage quality
• Stator: currents feeding the motor, cables, panels, contactors and current unbalance
• Rotor: broken bars
• Mechanics: 1x shaft rotational speed and bearings
• Load variation: oscillations in motor torque or current

It’s also worth noting that the solution presents overall signature values in a more intuitive way, making interpretation easier in day-to-day maintenance.

With Dynamox ESA, electrical signature analysis is applied continuously and in a structured way, with a direct impact on maintenance and asset performance indicators:

Dynamox ESA is part of Dynamox’s predictive solutions ecosystem, bringing vibration analysis, thermography and electrical signature analysis together in a single platform. This concentrates different techniques in one environment, extending visibility over assets and supporting analysts and managers in decision-making.

Want to understand how to apply electrical signature analysis in your operation? Discover Dynamox ESA and see how to turn electrical data into more precise maintenance decisions.

Frequently Asked Questions About Electrical Signature Analysis – FAQ