PowerNode: Motor Health Management
Electrical machines play a vital role for the modern industrial world. The impact of unplanned downtime due to breakage of these electrical motors is estimated to be more than $30 billion USD1 each year.
With more than 100 years of engineering experience with motors, generators, and control equipment, GE brings physics-based analytics and advanced machine learning algorithms to detect evolving faults within electrical motors and helps identify future issues to support customers with avoiding failures and resolving faults in advance.
PowerNode: Motor Health Management services leverage the latest in condition-based asset health monitoring to deliver high-accuracy monitoring of critical motors. GE’s advanced health algorithms, based on Electrical Signature Analysis (ESA) and machine learning, provide early detection of electrical, mechanical, or thermal abnormalities before they become critical failures that bring plant processes to an unexpected halt.
Main benefits include:
1 GE Power. (2016). Electrical Rotating Machine APM Overview. https://www.ge.com/news/sites/default/files/GEA33604%20Motor_Fleet_APM_Paper_0.pdf.
Unexpected motor failures decrease plant throughput, increase plant downtime, and can decrease production quality. Current solutions involving scheduled preventive maintenance or sensor-based condition monitoring are expensive.
GE’s Motor Health Management increases uptime and reduces OPEX by implementing prognostics-based equipment insights based on data provided by existing protection relays and meters. No additional sensors are needed.
Our on-site and cloud-based monitoring elements monitor equipment and provide an Equipment Health Dashboard with the remote connectivity and accessibility that enables this connection.
Motor Health Management Managed Services provides detailed insights into alarms and anomalies. Our team of experienced data analysts, subject matter experts and service engineers will provide recommendations for action when an incipient motor fault is detected.
PowerNode: Motor Health Management uses Electrical Signature Analysis (ESA) and machine learning (ML) to predict failures.
The GPG Controller located at the industrial premises automatically triggers periodic oscillographies in the motor IEDs if the motor is running. Additional data (temperatures, vibration, electrical data) can also be automatically retrieved if available.
Oscillographies are transferred to the Service Portal through a secure remote connection.
PowerNode: Motor Health Management supports GE and non-GE IEDs. For non-GE IEDs, an evaluation will need to be carried out.
Motor data received from the industrial site is processed and stored in the Service Portal infrastructure.
When a potential fault is detected, the analytics engine automatically opens a case to be reviewed by our managed services team.
The Service Portal also provides a web interface to customers and the managed services team where they can see the asset status overview and details for each monitored asset.
The managed services center receives all potential failures detected by the service portal. A team of experts validates the data, provides recommendations to address the detected problem(s), and supports the site maintenance team.
GE’s PowerNode Motor Health Management uses a cloud-based application to store and display data for analytics and monitoring.
Overview of the location of all monitored sites and assets of a company. Locations of an asset with potential issues will be highlighted in orange or red.
View the status of an asset by navigating to a specific zone. Assets can be organized into four hierarchical levels for easy access.
View current and historical data for each asset and failure type to validate a potential motor failure.
Monitor the performance of your assets with a set of dashboards that display the status of the assets by failure type, and a confusion matrix that displays the failure detection accuracy.
Being part of artificial intelligence, ML algorithms can improve automatically through experience and using data.
GE’s ML algorithms can automatically detect and classify healthy and unhealthy motor operating conditions (unsupervised clustering).
The algorithms consider multiple parameters derived from the current and voltage readings (frequency, power, speed, rate-of-change, etc.) to increase accuracy of pure ESA analytics.
The managed services provided by GE are the core value of Motor Health Management. These services save the customer the unnecessary pain of being exposed to the analytic algorithms while they are still in the process of being fine-tuned, thus avoiding unnecessary mis-operations. They also provide recommendations with regards to the detected failures in the form of prescriptive analytics.
Electrical motors operate under different load conditions depending on the application. A continuous improvement process can adapt failure detection to your specific operating conditions.
PowerNode: Motor Health Management solution uses advanced diagnostics and prognostics to ensure you can plan your actions before the asset fails, avoid unplanned downtime, and reduce O&M costs.
No additional sensors are required. The system uses protection and control relay data and existing communication infrastructure to minimize cost of deployment and installation impact.
Our managed services team will accurately interpret the results and guide you in making the right decisions.