How the newest condition-based monitoring technology improves motor uptime, lifespan, and efficiency

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The newest condition-based monitoring technology for motors and rotating equipment offers advantages over previous methods, being simpler to install, adapting to more applications, and delivering significantly improved detection rates with earlier failure detection. This, in turn, helps lower total-cost-of-ownership (TCO) by up to 50 percent and shorten the payback period compared to other monitoring methods. Let’s have a closer look at this new technology.

I’ve also written a post that explores the need for industrial organizations to implement predictive maintenance strategies for managing their stock of motors. This approach will help reduce downtime, improve efficiency, reduce costs, and get more life from rotating equipment. However, it requires the support of new condition-based monitoring.

The emergence of motor current signature analysis as a new condition-based monitoring technology

A new technology for motor condition monitoring has emerged in recent years that has many advantages over the vibration, oil, acoustic, and thermal monitoring techniques mentioned in a previous post. Motor current signature analysis (MCSA) measures minor fluctuations in both the current draw and supply voltage of the power lines feeding a motor or other rotating equipment. These electrical ‘signatures’ can provide early indications of upcoming failures with increased sensitivity and accuracy over other methods. The technology can diagnose specific failure modes or their initiating root causes, whether they are mechanical or electrical.

One of the biggest advantages of MCSA is that its sensors do not need to be placed on the motor – they can be installed in the motor control cabinet (MCC). This is a clean, dry location where sensors are protected from dirt, moisture, and wear, while separated from harsh environments. This helps improve the reliability of the entire monitoring system. An MCC is typically easy and safe to access, often containing the power lines for multiple motors. This fact, along with the ability to upload data to the cloud using 4G cellular communications, further reduces the time and cost to install MCSA sensors for a complete production line, while providing easier scalability.

Sensor data is aggregated to a central, cloud-based asset management system, which can include the support of expert services. A set of machine learning algorithms first makes a model of ‘normal’ motor behavior with an associated normal motor current signature. If a motor operating behavior begins to drift out of the normal range, anomalies are detected and classified through recognized variations in the motor current signature. These sensing technologies and analytical methods can be used to detected and diagnose a broad range of potential failure modes including stator shorts, bearing degradation, loose rotor bars, coupling misalignment, mechanical or electrical imbalance and more.

condition-based monitoring

Predicting failures earlier, and with greater accuracy

These methods allow prediction of both known and unknown failure patterns, while providing a longer lead time in failure prediction and delivering over 90 percent accuracy. Failure modes or causes can be detected from weeks to up to five months in advance, depending on the type of potential failure. This enables maintenance teams to order spare parts and schedule a repair when it will least impact operations. In addition, MCSA failure analysis can also give clues to electrical conditions that are happening upstream of the motor that may be causing the issue. This can include power quality anomalies.

Over 95 percent of the total cost of ownership of an electric motor is the cost of the electricity it consumes. Issues such as voltage unbalance reduce efficiency, while properly maintained motors consume up to 15 percent less electricity. As MCSA technology monitors both current and voltage, it can provide metrics on energy consumption of individual motors, as well as power factor. This insight can help facility teams make decisions to lower energy usage and reduce environmental footprint.

In summary, MCSA delivers significantly higher performance and a greater scope of application than other motor monitoring technologies. An asset management system that includes MCSA capability will monitor all motors 24/7, sending notifications via mobile device or desktop when an upcoming failure is detected. This creates a complete, reliable, accurate, and easy-to-use condition-based monitoring solution that is highly scalable. It can also help reduce the number of regular inspections needed by enabling a predictive maintenance strategy.

For more information

As part of our complete motor management solutions portfolio, EcoStruxure Asset Advisor for Electrical Distribution now includes the condition-based monitoring of rotating equipment assets using  MCSA technology. Our fully integrated and certified solution includes data acquisition devices installed inside the MCC connected to the cloud using the customer’s network or via a dedicated 4G cellular uplink, with the complete architecture adhering to strict cybersecurity guidelines. The solution offers alarms, integrated customer dashboard, and the support of our expert-staffed service bureau. Also, learn about Schneider Electric asset performance management best practices or try our asset performance management ROI calculator.

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