Bram Corne
Technical Services Committee Member
Orbits
Kor trijk, Belgium
Without exaggeration, electric motor systems play a pivotal role in our industrial operations, serving as the heartbeat of numerous processes. Pumps, compressors, fans and other types of mechanical movement are crucial to our industrial activities. Consequently, the health of these motors directly influences the operational reliability and longevity of the broader industrial ecosystem. In a culture that values reliability, the predictability of downtime, the availability of spare parts, the employability of technicians, and the limitation of consequential damage are paramount. Acknowledging this underscores the necessity for performing online health assessments of electric motors. Mirroring the medical field, we aim to proactively predict catastrophic failures before they occur. By doing so, it is feasible to prevent failures from occurring or progressing. Hence, integrating the appropriate measurements and diagnostics for electric motors can significantly enhance overall asset performance.
Asset Health Assessment goes beyond traditional maintenance approaches by offering a holistic perspective on an electric motor’s condition. This method employs a comprehensive suite of diagnostic tools and methodologies, beginning with the creation of an exhaustive overview of the entire system. This is achieved by gathering information, briefing operators and conducting visual inspections. Beyond these fundamentals, technologies such as Electrical Signature Analysis (ESA), Vibration Analysis, Ultrasound Analysis, Thermal Analysis, among others, can furnish deeper insights into the condition of the electric motor (Figure 1). This article primarily focuses on the benefits of incorporating ESA into the existing diagnostic toolkit.
The Stress Electrocardiogram of the Motor
In the realm of industrial maintenance, it is a standard practice for many companies and repair shops to conduct offline analysis on electric motors. This usually occurs periodically or following a motor overhaul, employing tools such as surge testers and winding analyzers. Such tests are instrumental in assessing the insulation quality, impedance of the phases, and at times the mechanical quality of the motor. While these tests are essential and offer critical insights, they provide a limited perspective, focusing solely on the motor as an individual component. This can be likened to an electrocardiogram (EKG) conducted on a person at rest — valuable but not entirely comprehensive. Just as additional tests like a stress EKG are necessary to fully evaluate human heart health, a complete health assessment of an electric motor requires more extensive evaluation (Figure 2). This includes measuring the motor's electrical performance during its operational state or when it is online. One robust technique employed for such an in-depth analysis is known as Electrical Signature Analysis (ESA).
ESA sets itself apart from Motor Circuit Analysis (MCA) and Motor Current Signature Analysis (MCSA) as it facilitates a comprehensive and real-time assessment of the motor by measuring voltage and current during its operation. Table 1
shows a comparison of the techniques. The broadband frequency content of the voltage, accessible even during direct online operation, and the corresponding current response—when analyzed with appropriate processing and analytical techniques—yield a detailed and comprehensive understanding of motor health. Essentially, ESA conducts a system identification of the electric motor system. With a well-chosen array of sensors and a data acquisition system, ESA can detect any erratic behavior.
Motor Circuit Analysis (MCA): Conducted offline during overhauls, MCA evaluates insulation quality and impedance phases of the motor.
Motor Current Signature Analysis (MCSA): Performed online during operation, MCSA focuses on current to detect erratic behavior and electrical conditions.
Electrical Signature Analysis (ESA): Provides a comprehensive, real time assessment of motor health by measuring both voltage and current, detecting both electrical and mechanical issues.
Typically, electrical issues manifest through impedance and field distortions, while mechanical issues are discernible through variations in airgap and reluctance distortions. However, this distinction is somewhat oversimplified, as electrical and mechanical issues are often interlinked. For instance, a mechanical problem such as an uneven airgap can lead to reluctance distortions, which subsequently cause field distortions. These field distortions can then manifest as electrical anomalies.
The strength of ESA lies in its advanced algorithms, which can detect these subtle and interrelated changes. By analyzing the voltage and current signatures in detail, ESA can identify and differentiate between mechanical and electrical issues, even when they are closely connected. This comprehensive diagnostic capability ensures that both types of problems can be effectively monitored and addressed, maintaining the overall health and efficiency of the motor system.
ESA is thus capable of fully assessing the power quality of the grid or Variable Frequency Drive (VFD), providing a detailed examination of the electrical condition of the machine, evaluating the mechanical state of the machine and even approximating the mechanical condition of the drivetrain. The latter assessment is feasible only when issues within the drive train manifest as airgap and reluctance distortions within the electric motor.
The ESA Procedure
The initial phase takes place onsite and is fundamental to the subsequent analysis. It begins with a visual inspection to identify any evident issues with the equipment. Technicians gather information such as part lists and drawings to under
stand the machine's specifications and history. The operator or maintenance team is briefed to gain operational insights and to ensure the correct procedures are followed during data collection. Finally, measurements are taken directly from the electric motors or associated equipment, which are then validated to ensure the accuracy and reliability of the data.
Measurements are preferably conducted within the motor control cabinet (MCC) for safety reasons. While theoretically, more accurate readings could be obtained directly at the motor terminal, this method is neither safe nor practical. It is crucial to emphasize that making connections with the power turned off is advisable, which necessitates pausing the process. For low voltage applications (up to 1 kV), voltages are measured directly on the lines, whereas for high voltage scenarios (above 1 kV), measurement transformers are used. Current measurement, contingent on the current's magnitude and the feasibility of the setup, is performed using current clamps, current transformers (CTs) or Rogowski coils. Figure 3 shows an example of a measurement configuration. The quality of data acquisition is vital for in-depth analysis and depends on factors such as sampling frequency, dynamic range and anti-aliasing, among others. The data quality required is comparable to the standards of best practices in vibration measurement.
Once the data has been gathered, the analysis phase typically takes place in an office setting, which is better suited for in-depth examination. Initially, the process involves the time-waveform analysis of the electrical signals to detect any anomalies. This is followed by a comprehensive Power Quality analysis, which evaluates key parameters such as Crest Factor (CF), Form Factor (FF), Root Mean Square (RMS) value, Power (P), Total Harmonic Distortion (THD) and Power Factor (PF). Subsequently, a detailed spectral analysis including various transformations is conducted. Figure 4 shows an example of a symmetrical spectrum used for analysis. When examining multiple measurements under identical conditions, the identification of trending characteristics becomes crucial. Monitoring for changes in patterns over time is an effective strategy to pinpoint potential emerging issues.
In the concluding phase of the health assessment, all collected data and analyses reach their culmination point. This phase is critical as it involves interpreting the data to diagnose present issues with electric motors and predicting future problems, which is a key aspect of ensuring reliability and longevity of the equipment. The analysis then merges with Failure Mode, Effects and Criticality Analysis (FMECA), leading to the creation of an exhaustive report detailing the asset's health.
Communication plays a vital role at this stage as findings are shared with the client. This dialogue is not just about presenting results but also involves discussing potential solutions and planning subsequent actions, ensuring that the client is fully informed and engaged in the decision-making process.
The process is brought to completion with confirmation and evaluation steps. The diagnostics are finalized by affirming the assessments and evaluating the overall condition of the electric motor or system. This comprehensive method provides a robust basis for maintenance strategies and proactive actions, which are essential in averting unexpected downtime and in prolonging the asset's operational lifespan.
The Imperative of Periodic ESA for Long-Term Asset Health
Just as individuals invest in annual health check-ups with a doctor to ensure well-being even in the absence of overt symptoms, so too should the industrial sector adopt a proactive stance on the health of its critical assets. Regularly scheduled Electrical Signature Analysis (ESA) serves as this essential health check for electric motors, acting as a preventive measure rather than a reactive one. This periodic
scrutiny allows for the identification of subtle changes or emerging issues that might not yet have manifested into visible problems but could lead to future failures. By adopting a consistent routine of ESA, organizations can ensure the optimal performance of their equipment, much like regular check-ups can help maintain a person's health and catch potential issues before they develop into serious conditions. This strategic approach is about maintaining an enduring state of operational readiness and safeguarding against the ripple effects of unplanned outages, thus securing both efficiency and longevity in the industrial landscape.
Conclusion
In conclusion, the adoption of Electrical Signature Analysis (ESA) within asset health management is not merely an enhancement of maintenance protocols but a transformative strategy toward predictive and proactive care. Embracing ESA parallels a commitment to the heart of industrial operations, ensuring ongoing vigilance and maximizing the lifecycle of electric motors. This proactive measure is an investment in the future—a future where operational continuity is the norm, and unexpected downtime becomes a relic of the past. As we integrate ESA into regular maintenance schedules, we enable a more resilient, efficient and sustainable industrial environment.
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