Electrical Signature Analysis: The Key to Accurate Predictive Maintenance in Industrial Motors

In industrial settings, predictive maintenance is essential to keep machines running smoothly and prevent costly failures. Electrical signature analysis (ESA) is a critical technology in this field, enabling more accurate fault detection in even hard-to-reach electric motors. ESA is essential in processes where the cost of downtime can be high.

ESA methods are critical to the functionality of PowerLink, GRT’s motor status monitoring toolkit. Specifically, PowerLink uses intelligent current and voltage sensors and digital twins to capture signals from electronic devices and process those signals via predictive analytics. This toolkit is an ideal instrument for asset maintenance and control.

This article demonstrates how PowerLink works through the basic principles of ESA in the context of electric motors. We also consider the five key features of PowerLink enabled by ESA, which are:

  1. Current and voltage measurement
  2. Signal processing
  3. Data storage
  4. Digital twin
  5. Smart analysis

Basic Principles of ESA in Electric Motors

In 1985, the Oak Ridge National Laboratory (ORNL) developed electrical signature analysis for unique electric motor applications. Later, the method was applied to a broader range of machines. Its unique value proposition is that it detects faults in electrical machines very early, while they are still small and easy to fix. This is done by monitoring the motor’s electrical characteristics while running.

ESA technology has many benefits, but its main advantage is its low cost. The hardware necessary for implementing the system on an industrial scale is very affordable, and the method can be used to detect faults in even hard-to-reach motors.

Another critical advantage of electrical signature analysis is that it does not require the machine to be shut down for maintenance. In the case of motors, ESA — or Motor current signature analysis (MCSA) in this context — takes advantage of electric motor features by which a motor can act as a transducer while in operation. This makes it ideal for use in industrial settings, where downtime can be very costly.

Most importantly, ESA-enabled devices can acquire vast amounts of diagnostic data, even from a single transducer that is distant from the motor itself. It detects signals from the motor’s input electrical line rather than attaching to, or even residing within, the motor itself.

Faults that ESA can detect in an industrial motor include:

  • Bearing faults
  • Broken rotor bars
  • Air-gap eccentricity
  • Mechanical faults (e.g., with belts, couplers, alignment)
  • And others

Now, ESA is growing in its acceptance within the industrial community. The benefits of electrical signature analysis are becoming more widely understood, and the technology is being applied to an increasing number of machines and settings.

Five Key PowerLink Capabilities That ESA Supports

Next, we will take a closer look at how PowerLink uses these principles for next-generation predictive capabilities. The following five features are key to PowerLink’s success.

1. Current and Voltage Measurement

In the context of ESA, current and voltage measurement involves the acquisition of electrical signals from an industrial motor while it is in operation. These signals are then processed to extract features that can be used for predictive maintenance.

PowerLink uses intelligent sensors to capture these electrical signals. The sensor is a non-intrusive device that clamps onto the motor’s input electrical line, allowing PowerLink to take measurements without disrupting the motor’s operation.

With PowerLink, users can install advanced instruments for measuring line currents of electric motors very quickly. These instruments do not require special mounting so they can fit within an MCC or next to a motor without issue.

2. Signal Processing

Signal processing is the second key feature of PowerLink. This is the stage at which electrical signals are converted into a form that can be analyzed for predictive maintenance purposes.

PowerLink processes raw line current data for further transmission, storage, and analysis within the system. It uses proprietary algorithms to process electrical signals from industrial motors, and these algorithms will extract features quickly, indicating the motor’s health.

3. Data Storage

The processed data is then stored in a database for further analysis. PowerLink uses modern tools and methods to store motor data for analysis and logging. This includes storing data in a secure, cloud-based database. Analysis can take place on-site or remotely, as needed.

4. Digital Twin

A digital twin is a digital representation of a physical object or system. In the context of industrial motors, a digital twin can be used to simulate the electrical signals that are produced by a motor. Using a digital twin is critical to modern methods of monitoring and predicting outcomes associated with motor health.

PowerLink uses digital twins to provide users with an accurate representation of an industrial motor’s electrical signals. The created structure provides timely insights and actions for energy consumption and demand flexibility. This simulation can be used to detect faults before they occur. In addition to detecting potential failures, it enables more accurate predictions of overall motor health and performance.

5. Smart Analysis

The smart analysis process is the final step leading to the critical maintenance decision-making for which operational leaders are responsible. Fortunately, decision-makers can determine a motor’s condition and predict potential faults or performance issues without shutting the motor down. In this case, the insights they need are accessible at any time, whether their analysis is prescheduled or not.

PowerLink uses smart analysis to provide users with predictions about an industrial motor’s health. This is accomplished by analyzing the electrical signals of the motor over time. PowerLink can help decision-makers predict when a fault is likely to occur and recommend steps for corrective action.

An Essential Tool in Your Predictive Capabilities Tool Belt

Modern predictive capabilities have transformed industrial processes, enabling better predictive maintenance, greater efficiencies, reduced costs, and greater flexibility. In this context, ESA has become a critical function of modern industrial success.

PowerLink is a tool that uses ESA for these purposes, and it’s an essential part of any inventory of predictive capabilities. PowerLink is quickly becoming the standard for electric motor analysis thanks to its low cost and easy installation.

Support Your Operational Health with PowerLink

Discover how PowerLink helps you visualize the real status of your electric motors and then extend their life and efficiency through proper predictive maintenance. Contact us directly and learn how easy it is to get the greatest possible value out of your electric motors.

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